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IN DEGREE PROJECT MECHANICAL ENGINEERING,SECOND CYCLE, 30 CREDITS
, STOCKHOLM SWEDEN 2021
Design and Evaluation of a
Sustainable Energy System for
AETCR Llanogrande, Colombia
CAROLINE ALGARP
HANNA SIMSON
KTH ROYAL INSTITUTE OF TECHNOLOGY
SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT
Master of Science Thesis
Department of Energy Technology
KTH 2021
Design and Evaluation of a Sustainable Energy
System for AETCR Llanogrande, Colombia
TRITA-ITM-EX2021:186
CarolineAlgarp
HannaSimson
Approved Examiner
AndersMalmquist
Supervisor
AndersMalmquist
IndustrialSupervisor Contactpersons
CarolinaRodríguezRodelo
NéstorFernández
2021-06-30
Abstract
After many years of conflicts and civil wars between the guerilla group called FARC and the government
of Colombia, a peace agreement was signed in 2016. The peace agreement included six cornerstones, and
in this study the third one was in focus. It included ending the hostilities and promoting the laying down
of arms, in exchange of a chance for the ex-combatants to reintegrate into society. Special reintegration
villages were formed, also called AETCR’s today, and ARN was the presidential agency that managed
the villages. In the reintegration process, the ex-combatants were provided with work opportunities and
education, and a stable and functioning energy system was of great importance to ease the reintegration.
The purpose of the study was thereof to propose a sustainable energy system for AETCR Llanogrande,
that would ensure energy stability for the ex-combatants to reintegrate into the life of civilians. The aim
and objectives were to maximize the social benefits, reduce the environmental footprint and minimize the
economical costs. Two research questions were formed, regarding what would be the best energy system
when focusing on the objectives separately and what would be the best design for all three combined.
The study was a pre-study based on a previous project at the Royal Institute of Technology, and was
performed with a qualitative research method, with both inductive and deductive approaches as well as
a field study. The field study was supervised by the ARN Administrator and Engineer Mr. Fernández,
who was also one of the contact persons in AETCR Llanogrande. Information regarding the AETCR
was provided by both Mr. Fernández and the ARN Coordinator Carolina Sofía Rodríguez Rodelo. The
available renewable energy resources were evaluated, and it was concluded that wind power was not a
feasible option for energy production. Although, the solar resources were good and biomass was available.
With all the attained information regarding the AETCR, several scenarios were formulated; one for Business
As Usual, one that included a Modest Implementation of Technologies, one that was Off-Grid, one with
a Social Development with a Constant Population, and one with an Increased Energy Demand with a
Growing Population. A literature study was performed for the different technologies; solar, micro-hydro,
biodigesters, generators and energy storage. The field study for hydro was performed, and it was concluded
not to be feasible.
A load curve was created for the AETCR, with varying daily demands for the different scenarios. The
electricity system was simulated in HOMER Pro, where the weather data was collected from PVGIS. Based
on the technology research, the fixed dome biodigester was recommended and calculations regarding the
biogas production were performed in MATLAB. The economics were also evaluated for both systems,
where the net present cost (NPC) was the prioritized factor. The lifetime emissions were also calculated
for both systems along with the renewable fraction (RF) in the electricity mix. For the electricity system it
was concluded that polycrystalline panels, with the grid and the generator, as well as Li-Ion batteries or no
batteries was the most beneficial combination, both concerning the economics and the environment. The
size of the system however, was flexible in terms of what requirements were desired for the AETCR, such
as the RF and self-sufficiency for example. The chosen biodigester design was the chinese design with a
diameter of 4.8 m. This was the recommended system for all of the scenarios when looking at both the
economical and environmental aspects. The social impact was not possible to measure, and it was instead
discussed.
Finally, a recommended combined system was proposed. The electricity system consisted of 36.8 kW
of polycrystalline PV panels, 20.5 kW inverter capacity, no batteries and a total RF of 83.2%. Combined
with the previously mentioned biodigester which produced 140,300 m3 of biogas in a year, the total NPC
was 724 kUSD and the lifetime emissions were 585.4 tonnes CO2-eq, concluding in a NPC increase of
7,000 USD and a reduction of 374.3 tonnes CO2-eq. A sensitivity analysis was also performed to evaluate
the effects of the various input parameters. In conclusion, the combined system was deemed possible
to implement and that it would support the reintegration of the inhabitants of AETCR Llanogrande in a
sustainable way.
Resumen
Tras numerosos años de conflictos y guerras civiles entre el gobierno de Colombia y un grupo de guerrilleros
llamado FARC, en 2016 se firmó un acuerdo de paz entre ambas partes. Este tratado incluye seis piedras
angulares, siendo la tercera de ellas el foco de atención de este estudio. Esta promueve el fin de las
hostilidades y la dejación de las armas, a cambio de una oportunidad para que los excombatientes se
reintegren en la sociedad colombiana. Con este fin, se formaron aldeas especiales de reintegración, también
llamadas actualmente AETCR, y la ARN era la agencia presidencial encargada de gestionarlas. En el
proceso de reintegración, los excombatientes reciben oportunidades de trabajo y educación, por lo que
se hace evidente la necesidad de proveer de un sistema energético estable y continuado para facilitar
dicha reintegración. El propósito del presente estudio es proponer un sistema de suministro energético
sostenible para el AETCR Llanogrande, que garantice la estabilidad energética para que los excombatientes
se reintegren en la vida de los civiles. Los objetivos son maximizar los beneficios sociales, reducir la
huella medioambiental y minimizar los costes económicos. Se formularon dos preguntas de investigación,
relativas a cuál sería el mejor sistema energético si se abarcasen los objetivos por separado y cuál sería el
mejor diseño para los tres combinados.
El presente estudio se basa en un estudio preliminar llevado a cabo en un proyecto anterior del Royal
Institute of Technology, y se realizó con una metodología de investigación cualitativa, con enfoques tanto
inductivos como deductivos, así como un estudio de campo. El estudio de campo fue realizado a través
del Administrador e Ingeniero de la ARN, el Sr. Fernández, quien también fue una de las personas de
contacto en el AETCR Llanogrande. La información sobre el AETCR fue proporcionada tanto por el
Sr. Fernández como por la coordinadora de la ARN, Carolina Sofía Rodríguez Rodelo. Se evaluaron los
recursos energéticos renovables disponibles y se concluyó que la energía eólica no era una opción viable
para la producción de energía. Sin embargo, se observó una elevada disponibilidad de recurso solar y de
biomasa en la zona. Con toda la información obtenida sobre el AETCR, se formularon varios escenarios;
uno denominado Business As Usual, uno que incluía una Modest Implementation of Technologies, uno que
era Off-Grid, uno con un Social Development with a constant population, y uno con una Increased Energy
Demand with a growing population. Se realizó un estudio bibliográfico para las diferentes tecnologías:
solar, microhidráulica, biodigestores, generadores y almacenamiento de energía. Se realizó un estudio de
campo para la hidroeléctrica y se concluyó que no era viable.
Se creó una curva de carga para el AETCR, con demandas diarias variables para los diferentes escenarios.
El sistema eléctrico se simuló en HOMER Pro, donde los datos meteorológicos se recogieron del programa
PVGIS. Sobre la base de la investigación tecnológica, se recomendó el biodigestor de cúpula fija y se
realizaron cálculos sobre la producción de biogás en MATLAB. También se evaluaron los aspectos econó-
micos de ambos sistemas, siendo el Valor Actual Neto el factor priorizado. También se calcularon las
emisiones a lo largo de la vida útil de ambos sistemas junto con la fracción renovable en el mix eléctrico.
Para el sistema eléctrico se concluyó que los paneles policristalinos, con la red y el generador, así como
las baterías de iones de litio o sin baterías, era la combinación más beneficiosa, tanto en lo que respecta a
la economía como al medio ambiente. Sin embargo, el tamaño del sistema era flexible en función de los
requisitos que se deseaban para la AETCR, como la RF y la autosuficiencia, por ejemplo. El diseño del
biodigestor elegido se basa en un diseño chino con un diámetro de 4.8 m. Este fue el sistema recomendado
para todos los escenarios al considerar tanto los aspectos económicos como los medioambientales. No fue
posible medir el impacto social, por lo que se realizó una discusión más detallada.
Finalmente, se propuso un sistema combinado. El sistema eléctrico consistía en 36.8 kW de paneles
fotovoltaicos policristalinos, 20.5 kW de capacidad del inversor, sin baterías y una fracción renovable total
del 83.2%. Combinado con el biodigestor mencionado anteriormente, que producía 140,300 m3 de biogás
en un año, el VAN total era de 724 kUSD y las emisiones a lo largo de la vida útil de la instalación eran de
585.4 toneladas de CO2-eq, concluyendo en un aumento del VAN de 7,000 USD y una reducción de 374.3
4
toneladas de CO2-eq. También se realizó un análisis de sensibilidad para evaluar los efectos de los distintos
parámetros de entrada. En conclusión, se consideró que el sistema combinado era posible de aplicar y que
apoyaría la reintegración de los habitantes de AETCR Llanogrande en la sociedad colombiana de forma
sostenible.
5
Sammanfattning
Efter många år av konflikter och inbördeskrig mellan gerillagruppen FARC och Colombias regering, under-
tecknades år 2016 ett fredsavtal. Fredsavtalet innehöll sex huvudpunkter, och i den här studien var det den
tredje som var i fokus. Den punkten innefattade bland annat att den fientlighet som pågått skulle upphöra
och att man skulle främja nedläggningen av vapen i utbyte mot en chans för de före detta medlemmarna
att återintegreras i samhället. Särskilda byar som i dag kallas för AETCR:s, bildades för återintegreringen
och ARN var det presidentiella organ som förvaltade byarna. I återintegreringsprocessen tillhandahölls
de före detta medlemmarna med både arbetsmöjligheter, utbildning och ett permanent hem, och därav var
ett stabilt och fungerande energisystem av stor betydelse för att kunna underlätta återintegreringen. Syftet
med studien var att föreslå ett hållbart energisystem för AETCR Llanogrande, som skulle kunna garantera
ett stabilt energisystem för att underlätta återintegreringen. Målen var att maximera de sociala fördelarna,
minska det miljömässiga fotavtrycket samt att minimera de ekonomiska kostnaderna. Två forskningsfrågor
formulerades, nämligen vad som skulle vara det mest fördelaktiga energisystemet när man fokuserar på
målen separat och vad som skulle vara den mest fördelaktiga utformningen för de tre målen kombinerat.
Studien var utformad som en förstudie baserad på ett tidigare projekt vid Kungliga Tekniska Högskolan
och genomfördes med en kvalitativ forskningsmetodik. Metodiken innehöll både induktiva och deduktiva
tillvägagångssätt, samt en fältstudie som övervakades av ARN:s administratören och ingenjören Néstor
Fernández, som också var en av kontaktpersonerna på plats i AETCR Llanogrande. Information om
AETCR tillhandahölls av både Néstor Fernández och ARN:s samordnare Carolina Sofía Rodríguez Rodelo.
De tillgängliga förnybara energiresurserna utvärderades, varav slutsatsen blev att vindkraft inte var ett
aktuellt alternativ för energiproduktion. Solresurserna var dock goda och det fanns biomassa tillgänglig.
Med hjälp av den erhållna informationen gällande Llanogrande så utarbetades flera scenarier: Business
As Usual, Modest Implementation of Technologies, Off-Grid, samt Social Development with a constant
population och Increased Energy Demand with a growing population. En litteraturstudie genomfördes
för de olika teknikerna: solkraft, vattenkraftverk, bioenergi, generatorer och energilagring. Efter den
utförda fältstudien gällande förutsättningarna att implementera vattenkraft konstaterades det att detta inte
var genomförbart.
Elbehovet uppskattades timvis för ett genomsnittligt dygn i byn, med varierande dagligt behov för de olika
scenarierna. Elsystemet simulerades i HOMER Pro, där väderdata hade samlats in från PVGIS. Baserat på
literaturstudien rekommenderades en fixed dome digester, och beräkningar av biogasproduktionen utfördes
i MATLAB. De ekonomiska aspekterna utvärderades också för båda systemen, där NPC var den prioriterade
faktorn. Utsläppen under projektets livstid beräknades också för båda systemen tillsammans med den
förnybara andelen (RF) i elektricitetsmixen. Slutsatsen för elsystemet var att polykristallina paneler, med
tillgång till el-nätet och generatorn, samt Li-Ion-batterier eller inga batterier var den mest fördelaktiga
kombinationen, både när det gäller ekonomiska och miljömässiga aspekter. Storleken på systemet var dock
flexibel med avseende på de önskemål och krav som Llanegrande vill uppfylla, såsom till exempel RF och
självförsörjning. Den valda biodigester var den kinesiska designen med en diameter på 4.8 m. Detta var
det rekommenderade systemet för alla scenarier när man ser till både de ekonomiska och miljömässiga
aspekterna. De sociala konsekvenserna var inte möjliga att mäta, och var istället diskuterade.
Slutligen föreslogs ett rekommenderat kombinerat system. Elsystemet bestod av 36,8 kW polykristallina
solcellspaneler, 20,5 kW inverterkapacitet, inga batterier och en total andel RF på 83,2%. I kombination
med den tidigare nämnda biodigesteranläggningen, som producerade 140,300 m3 biogas under ett år, var
den totala NPC 724 kUSD och utsläppen under livstiden 585.4 ton CO2-eq. Detta resulterade i en ökning
av NPC på 7,000 USD och en minskning av utsläppen med 374.3 tonnes CO2-eq. En känslighetsanalys
utfördes också för att utvärdera effekterna av de olika ingående parametrarna. Slutsatsen var att det
kombinerade systemet var möjligt att genomföra och att det skulle stödja återintegreringen av invånarna
i Llanogrande på ett hållbart sätt.
Acknowledgement
We would like to thank our two contact persons on site in Colombia who has been retrieving information for
us that we could not access ourselves. First of all we have the ARN Coordinator Carolina Sofía Rodríguez
Rodelo who has helped us with information regarding the AETCR and their projects. Next we have the
ARN Administrator for AETCR Llanogrande and Engineer Néstor Fernández. He has been of great help
with fast replies regarding information about the AETCR, specifications on already installed technologies,
several field measurements for potential technological implementations and other relevant questions that
has emerged. He also sent us pictures of the current energy system, the surroundings and the stream for the
potential hydro implementation. Without the two of them, this thesis would not have been performed with
such an in depth analysis.
We would also like to thank Ingela Råberg for helping us create the biodigester figures, and Nestor Ruiz
Crespo for proof-reading the abstract presented in Spanish.
And last but not least, we would like to thank our examiner Anders Malmquist for great support and
feedback throughout this master thesis.
Division of Work
Caroline Algarp
Main responsibilities:
• The parts handling the generator, biodigester and biogas system calculations.
• The overall layout of the report.
Hanna Simson
Main responsibilities:
• The parts handling solar power, inverters, batteries and the simulations for the electrical system.
• Contact with both examiner and contact persons in Colombia.
All results were analysed and discussed in cooperation, in order for the best possible combined system to
be found. Both were equally responsible in the micro-hydro evaluation. The collaboration worked perfectly
throughout the thesis, with open communication and good workload division.
Table of Contents
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Aim and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.2 Scope and Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Methodology 4
2.1 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Key Performance Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3 Sustainable Development Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.4 Softwares . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4.1 PVGIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4.2 HOMER Pro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4.3 MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3 Case Study 9
3.1 Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 AETCR Llanogrande . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.3 Available Energy Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3.1 Solar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.3.2 Hydro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.3.3 Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.4 Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4 Technologies 18
4.1 Solar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4.1.1 Photovoltaic Panels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.1.2 Solar Thermal Collectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.1.3 Photovoltaic Thermal Collectors . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.1.4 Inverter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.2 Micro-Hydro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.3 Biodigester . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.3.1 Fixed Dome Digester . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.3.2 Floating Drum Digester . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.3.3 Balloon Digester . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.4 Generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.4.1 Upgrading Biogas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.5 Battery Energy storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5 Approach 31
5.1 Estimated Load Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.1.1 Estimated Load Curves for IED and PGE . . . . . . . . . . . . . . . . . . . . . . 31
5.2 Baseline HOMER Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.3 Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.3.1 Recommended Choice of Biodigester . . . . . . . . . . . . . . . . . . . . . . . . 33
5.3.2 Biogas Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.4 Economical Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.5 Environmental Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.6 Social Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.7 Combined Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
6 Results 41
6.1 Base Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.1.1 Business As Usual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.1.2 Modest Implementation of Technologies . . . . . . . . . . . . . . . . . . . . . . . 42
6.1.3 Off-Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.2 Social Development with a Constant Population . . . . . . . . . . . . . . . . . . . . . . . 52
6.2.1 Increased Electricity Demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
6.2.2 Increased Access to Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6.3 Increased Energy Demand with a Growing Population . . . . . . . . . . . . . . . . . . . . 55
6.3.1 Population Growth - Electricity . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.2 Population Growth - Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
6.4 Recommended Combined Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . 60
7 Sensitivity analysis 63
7.1 Electricity System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
7.2 Biogas System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
8 Discussion 72
8.1 Electricity System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
8.2 Biogas System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
8.3 Recommended Combined Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . 76
8.4 Social aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
8.5 Sustainability analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
8.6 Further Improvements and Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
9 Conclusion 81
References 82
A Appendix 93
A.1 Conditions for AETCR Llanogrande . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.1 Generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.2 AETCR Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.3 Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
A.1.4 Hydro Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
A.2 Hydro Power Measurement Manual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
A.3 Demand Curve Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
A.4 Yield Factor for Biogas Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
A.5 Biogas System Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
A.5.1 Increased Access of Biomass - Hemisphere Design . . . . . . . . . . . . . . . . . 105
A.5.2 Increased Access to Biomass - Chinese Design Savings . . . . . . . . . . . . . . . 106
A.5.3 Population Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
List of Figures
2.1 All goals included in the Sustainable Development Goals. [15] . . . . . . . . . . . . . . 6
2.2 Goal 7. [16] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3 Goal 8. [17] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.4 Goal 11. [18] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.1 Total energy consumption by sector. [24] . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 Total energy consumption by source. [24] . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.3 Electricity generated by source. [24] . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.4 Map of Colombia. [34] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.5 Map of Llano Grande. [34] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.6 Overview of AETCR Llanogrande. [37] . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.7 The average monthly global irradiance on a horizontal plane with a 5 degree tilt angle in
2015. [19] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.8 Existing PV panels in AETCR Llanogrande. [8] . . . . . . . . . . . . . . . . . . . . . 14
3.9 The three streams close to AETCR Llanogrande. [37] . . . . . . . . . . . . . . . . . . 15
3.10 The stream close to AETCR Llanogrande. . . . . . . . . . . . . . . . . . . . . . . . . 15
4.1 The yearly amount of produced electricity from solar power in Colombia. [52] . . . . . 18
4.2 Visualization of the different types of irradiance on a plane. [53] . . . . . . . . . . . . . 19
4.3 The three most common types of PV panels, displaying monocrystalline, thin-film and
polycrystalline panels in the same order as mentioned. [54] . . . . . . . . . . . . . . . 19
4.4 The basic layout of a flat plate thermosiphon. [64] . . . . . . . . . . . . . . . . . . . . 21
4.5 Efficiency of flat plate and evacuated tube collectors depending on the temperature difference
of the ambient temperature and the wanted temperature of the water. [67] . . . . . . . . 22
4.6 Design of a fixed dome digester. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.7 Design of a floating drum digester. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.8 Design of a balloon digester. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.9 PSA upgrading process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.10 Membrane permeation upgrading process. . . . . . . . . . . . . . . . . . . . . . . . . 29
5.1 The estimated daily demand curve of AETCR Llanogrande. . . . . . . . . . . . . . . . 31
5.2 The diameter for the two fixed dome digester designs. [128] . . . . . . . . . . . . . . . 35
6.1 Total renewable fraction vs NPC for all simulations, MIT. . . . . . . . . . . . . . . . . 43
6.2 Total renewable fraction vs NPC, zoomed in on the recommended cases, MIT. . . . . . 43
6.3 Renewable fraction vs emissions, MIT. . . . . . . . . . . . . . . . . . . . . . . . . . . 44
6.4 NPC vs emissions, MIT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
6.5 Total renewable fraction vs NPC for both poly- and monocrystalline PV panels, MIT. . . 45
6.6 Total renewable fraction vs emissions for both poly- and monocrystalline PV panels, MIT. 45
6.7 Total renewable fraction vs NPC for both LA and Li-Ion batteries, MIT. . . . . . . . . . 45
6.8 Total renewable fraction vs emissions for both LA and Li-Ion batteries, MIT. . . . . . . 45
6.9 Produced biogas for hemisphere and chinese design, MIT. . . . . . . . . . . . . . . . . 48
6.10 Initial capital cost for the biodigester. . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
6.11 Savings for the construction year for hemisphere and chinese design, MIT. . . . . . . . 48
6.12 Savings after the first year for hemisphere and chinese design, MIT. . . . . . . . . . . . 49
6.13 NPC for the project lifetime for hemisphere and chinese design, MIT. . . . . . . . . . . 49
6.14 Decrease of CO2 emissions depending on the diameter for hemisphere and chinese
design, MIT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.15 Renewable fraction vs NPC, Off-Grid. . . . . . . . . . . . . . . . . . . . . . . . . . . 51
6.16 Renewable fraction vs emissions, Off-Grid. . . . . . . . . . . . . . . . . . . . . . . . . 51
6.17 Renewable fraction vs NPC for all cases, IED. . . . . . . . . . . . . . . . . . . . . . . 53
6.18 Renewable fraction vs emissions for all cases, IED. . . . . . . . . . . . . . . . . . . . . 53
6.19 Produced biogas, IAB, chinese design. . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.20 NPC over the project lifetime, IAB, chinese design. . . . . . . . . . . . . . . . . . . . 55
6.21 Reduction of CO2 emissions, IAB, chinese design. . . . . . . . . . . . . . . . . . . . . 55
6.22 The total renewable fraction plotted against the NPC for all cases, PGE. . . . . . . . . . 56
6.23 The total renewable fraction plotted against the emissions for all cases, PGE. . . . . . . 56
6.24 Produced biogas, PGB 15%, chinese design. . . . . . . . . . . . . . . . . . . . . . . . 58
6.25 Savings for the construction year, PGB, chinese design. . . . . . . . . . . . . . . . . . 59
6.26 Savings after the first year, PGB, chinese design. . . . . . . . . . . . . . . . . . . . . . 59
6.27 NPC for the project lifetime, PGB, chinese design. . . . . . . . . . . . . . . . . . . . . 59
6.28 Decrease of CO2 emissions for the biogas system, PGB, chinese design. . . . . . . . . . 59
6.29 Schematics of the recommended combined system. . . . . . . . . . . . . . . . . . . . . 62
7.1 How a change of ±20% on the capital costs affects the NPC. . . . . . . . . . . . . . . 64
7.2 How a change of ±20% on the replacement costs affects the NPC. . . . . . . . . . . . 64
7.3 How a change of ±20% on the O&M costs affects the NPC. . . . . . . . . . . . . . . . 65
7.4 How a change of ±8% and ±2% on the performance of the PV panels and the inverter
affects the NPC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
7.5 How a change of ±20% on the allowed minimum state of charge affects the NPC. . . . 66
7.6 How changes on the price of electricity bought and sold to the grid affects the NPC. . . 67
7.7 How a change of ±20% on the price of diesel and the GHI affects the NPC. . . . . . . 67
7.8 How a change of ±20% on the emissions for each technology affects the lifetime emissions. 68
7.9 How a change in performance of the PV panels and inverter affects the lifetime emissions. 68
7.10 How a change of ±20% on the SoC affects the lifetime emissions. . . . . . . . . . . . 68
7.11 How a change of ±20% on the GHI affects the lifetime emissions. . . . . . . . . . . . 69
7.12 Changes in retention time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
7.13 Changes in biogas production. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
7.14 Changes in savings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
7.15 Changes in NPC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
7.16 Changes in emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
A.1.1 The generator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.2 The generator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.3 Days with precipitation in Llanogrande. [40] . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.4 Days with cloud cover in Llanogrande. [40] . . . . . . . . . . . . . . . . . . . . . . . . 93
A.1.5 Average daily global irradiance in Llanogrande from January til March. [19] . . . . . . 94
A.1.6 Average daily global irradiance in Llanogrande from April til June. [19] . . . . . . . . . 94
A.1.7 Average daily global irradiance in Llanogrande from July til September. [19] . . . . . . 94
A.1.8 Average daily global irradiance in Llanogrande from October til December. [19] . . . . 94
A.1.9 Surroundings of the stream. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A.1.10 Measure of the length. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A.1.11 Measure of the width. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
A.1.12 Measure of the depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
A.5.1 Produced biogas, IAB, hemisphere design. . . . . . . . . . . . . . . . . . . . . . . . . 105
A.5.2 Savings for the construction year, IAB, hemisphere design. . . . . . . . . . . . . . . . . 106
A.5.3 Savings after the first year, IAB, hemisphere design. . . . . . . . . . . . . . . . . . . . 106
A.5.4 NPC for the project lifetime, IAB, hemisphere design. . . . . . . . . . . . . . . . . . . 106
A.5.5 Reduction of CO2 emissions, IAB, hemisphere design. . . . . . . . . . . . . . . . . . 106
A.5.6 Savings for the construction year, IAB, chinese design. . . . . . . . . . . . . . . . . . . 107
A.5.7 Savings after the first year, IAB, chinese design. . . . . . . . . . . . . . . . . . . . . . 107
A.5.8 Produced biogas, PGB 5%. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
A.5.9 Produced biogas, PGB 10%. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
A.5.10 Produced biogas, PGB 15%, hemisphere design. . . . . . . . . . . . . . . . . . . . . . 108
A.5.11 Savings for the construction year, PGB, hemisphere design . . . . . . . . . . . . . . . . 109
A.5.12 Savings after the firts year, PGB, hemisphere design . . . . . . . . . . . . . . . . . . . 109
A.5.13 NPC for the project lifetime, PGB, hemisphere design . . . . . . . . . . . . . . . . . . 109
A.5.14 Reduction of CO2 emissions, PGB 5%. . . . . . . . . . . . . . . . . . . . . . . . . . . 110
A.5.15 Reduction of CO2 emissions, PGB 10%. . . . . . . . . . . . . . . . . . . . . . . . . . 110
A.5.16 Reduction of CO2 emissions, PGB 15%, hemisphere design. . . . . . . . . . . . . . . . 110
List of Tables
3.1 Percentages of cooking fuels used in urban and rural areas. [28] . . . . . . . . . . . . . 10
4.1 Specifications for average poly- and monocrystalline PV panels. [58][59][60][61][55] . 20
4.2 Characteristics of a typical hybrid inverter. [77][78][79] . . . . . . . . . . . . . . . . . 23
4.3 Characteristics of LA and Li-Ion batteries. [110][111][112][113][105] . . . . . . . . . 30
5.1 Characteristics of the existing technologies. [8][44] . . . . . . . . . . . . . . . . . . . . 32
5.2 Technology specifications for new implementations in the HOMER model. [44][116] . . 33
5.3 Data regarding manure, proportions of waste and different VS ratios. [120][121][122] . 34
5.4 Density for biogas calculations. [124][125][126][127] . . . . . . . . . . . . . . . . . . 35
6.1 System set up and important parameters, BAU. . . . . . . . . . . . . . . . . . . . . . . 42
6.2 Important parameters for the recommended electricity systems, MIT. . . . . . . . . . . 46
6.3 Amount of manure, waste and VS for each resource, MIT. . . . . . . . . . . . . . . . . 47
6.4 Volume of the digester. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
6.5 Retention time and yield factor, MIT. . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
6.6 Parameters for the recommended combined energy systems, MIT. . . . . . . . . . . . . 50
6.7 Important parameters for the recommended systems, Off-Grid. . . . . . . . . . . . . . . 51
6.8 Parameters for the recommended combined energy systems, Off-Grid. . . . . . . . . . . 52
6.9 The resulting peak demand and yearly demand for the increased electricity demand
scenario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
6.10 The increased electricity demand’s effect on the chosen economical systems. . . . . . . 53
6.11 The increase of livestock due to the increased biomass. . . . . . . . . . . . . . . . . . . 54
6.12 Retention time and yield factor for the chinese design, IAB. . . . . . . . . . . . . . . . 54
6.13 The resulting peak demand and yearly demand for the population growth scenario. . . . 56
6.14 The demand increase of a growing populations effect on the systems, PGE. . . . . . . . 57
6.15 Amount of waste and VS from waste, PGB. . . . . . . . . . . . . . . . . . . . . . . . . 57
6.16 Retention time and yield factor, PGB, chinese design. . . . . . . . . . . . . . . . . . . 57
6.17 Recommended combined energy system. . . . . . . . . . . . . . . . . . . . . . . . . . 61
6.18 The effects of a social development on the recommended electricity and biogas system. 61
6.19 The effects of an increased demand with a growing population on the recommended
electricity and biogas system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.1 Important characteristics of the three systems used in the sensitivity analysis. . . . . . . 63
7.2 Output values for the original case that were used as a comparison when varying parameters. 69
A.1.1 Route 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
A.1.2 Route 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
A.1.3 Route 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A.1.4 Route 4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A.1.5 Route 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A.1.6 Calculated measurement results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A.3.1 The hourlu values for the different demand curves. . . . . . . . . . . . . . . . . . . . . 103
A.4.1 Yield factors for biogas production, by temperature and feedstock retention time. . . . . 104
A.5.1 Retention time and yield factor for hemisphere design, IAB. . . . . . . . . . . . . . . . 105
A.5.2 Retention time and yield factor, PGB. . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
List of Equations
5.1 New PV area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.2 Total amount of manure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.3 Total amount of waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.4 Total amount of biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.5 Total amount of water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.6 Total amount VS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.7 VS in the slurry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.8 Vp, hemisphere design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.9 Vp, chinese design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.10 Vp, chinese design, flat bottom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.11 Retention time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.12 Amount of biogas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.13 Comparison between produced biogas and current cooking demand . . . . . . . . . . . 36
5.14 New amount of biomass, IAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.15 Percentage VS in biomass. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.16 New amount of VS, IAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.17 New number of livestock, IAB. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.18 New number of inhabitants, PGB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.19 New number of gas bottles, PGB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.20 New cooking demand, PGB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.21 NPC of biogas system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.22 Cost of the new amount of needed LPG bottles. . . . . . . . . . . . . . . . . . . . . . . 38
5.23 Economical cash flow of the biogas system. . . . . . . . . . . . . . . . . . . . . . . . . 38
5.24 NPC for the entire biogas system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.25 Total renewable fraction of the electricity system. . . . . . . . . . . . . . . . . . . . . . 38
5.26 CO2-eq emissions from the PV panels throughout the lifetime of the electricity system. 39
5.27 CO2-eq emissions from the generator throughout the lifetime of the electricity system. . 39
5.28 CO2-eq emissions from the grid throughout the lifetime of the electricity system. . . . . 39
5.29 CO2-eq emissions from the batteries throughout the lifetime of the electricity system. . 39
5.30 CO2-eq emissions from the entire electricity system throughout its lifetime. . . . . . . . 39
5.31 CO2-eq emissions from LPG. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
5.32 Reduction of CO2-eq emissions compared to LPG. . . . . . . . . . . . . . . . . . . . . 40
5.33 NPC for the combined system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.34 CO2-eq emissions for the combined system. . . . . . . . . . . . . . . . . . . . . . . . 40
Nomenclature
AC Alternating Current
AETCR Antiguos Espacios Territoriales de
Capacitación y Reincorporación
Former Territorial Spaces for Training and
Reincorporation
ARN Agencia para la Reincorporación y la
Normalización
The Agency for Reincorporation and
Standardization
BAU Business As Usual
CH4 Methane
CO2 Carbon dioxide
CSP Concentrated Solar Power
DC Direct Current
DHI Diffuse Horizontal Irradiance
DNI Direct Normal Irradiance
DoD Depth of Discharge
EPM Empresas Públicas de Medellín
ETCR Espacios Territoriales de
Capacitación y Reincorporación
Territorial Spaces for Training and
Reincorporation
EU European Union
FARC Fuerzas Armadas Revolucionarias de
Colombia
Revolutionary Armed Forces of
Colombia
GHG Greenhouse Gas
GHI Global Horizontal Irradiance
H2 Hydrogen
H2S Hydrogen sulfide
HOMER Hybrid Optimization of Multiple
Energy Resources
IAB Increased Access to Biomass
IED Increased Electricity Demand
JRC Joint Research Centre
KPI Key Performance Indicator
KTH Royal Institute of Technology
Kungliga Tekniska Högskolan
LA Lead-Acid
LCOE Levelized Cost of Energy
LF Load Following
Li-Ion Lithium-Ion
LPG Liquefied Petroleum Gas
MATLAB Matrix Laboratory
MIT Modest Implementation of Technologies
MSc Master of Science
MSW Municipal Solid Waste
NH3 Ammonia
NPC Net Present Costs
NREL National Renewable Energy
Laboratory
O&M Operation and Maintenance
PGB Population Growth - Biomass
PGE Population Growth - Electricity
PIN Personal Identification Number
PSA Pressure Swing Adsorption
PTAP Planta de Tratamiento
de Agua Potable
Drinking water treatment plant
PTN Puntos Transitorios de Normalización
Transitional Normalization Points
PV Photovoltaic
PVGIS Photovoltaic Geographical Information
System
PVT Photovoltaic Thermal
RF Renewable Fraction
SDG Sustainable Development Goal
SF Safety Factor
SoC State of Charge
ST Solar Thermal
STC Standard Test Conditions
UN United Nations
VS Volatile Solids
ZVTN Zonas Veredales Transitorias
de Normalización
Transitional Rural Normalization
Zones
1 Introduction
By looking at the near history of Colombia, an understanding of how this master thesis about a pre-study for
a small-scale polygeneration system in a village in Colombia has been developed. In the following section
called Background, information about the conflict, peace agreement and several invested organisations is
presented, and in the section Problem Description, the aim and objective of this master thesis research is
presented along with the scope and limitations.
1.1 Background
After Colombia became independent from Spain in the 1800’s, it was minted with civil wars between the
large political parties throughout the century. After a few decades of a calmer ambience in the beginning
of the 1900’s, violent fights between the different political groups broke out again in 1948 when one
of their leaders was killed. These went on for 10 years before a system as to how the power should
be divided between the different parties was agreed upon. But as the political fronts now stood united,
the discontent within the population grew and after many years of vexation with the Colombian parties
and their politics, parts of the population decided to take matters into their own hands. This lead to the
creation of several guerilla organizations, with one of these groups being the Revolutionary Armed Forces
of Colombia (FARC), or Fuerzas Armadas Revolucionarias de Colombia in Spanish. FARC was initiated
during the 1960’s in order to, among other things, depose the regime and fight for social reforms of mainly
the agricultural sector. The conflicts between the guerillas and the government claimed the lives of several
hundred thousand people, both from FARC and the paramilitary, but also of many civilians. [1]
In order to put an end to the conflict, a peace agreement called the Final Agreement was negotiated and
signed by FARC and the government in 2016. The Final Agreement, or the Acuerdo Final, was built on six
cornerstones [2][3]:
1. Towards a New Colombian Countryside: Comprehensive Rural Reform.
2. Political participation: A democratic opportunity to build peace.
3. End of Conflict.
4. Solution to the Illicit Drugs Problem.
5. Agreement regarding the Victims of the Conflict: “Comprehensive System for Truth, Justice, Repara-
tions and Non-Recurrence”, including the Special Jurisdiction for Peace; and Commitment on Human
Rights.
6. Implementation, Verification and Public Endorsement.
In short, item 1 includes eradication of poverty, promotion of equality and decreasing the differential
between rural and urban areas, striving for a higher quality of life and well-being for the rural population.
Item 2 aims for a wider concept of democracy, political inclusion and participation, as well as diversification
on the political scene to further enrich the debates. Item 3, which is also the one in focus in this project, is
made up of three sub parts; to end the hostilities and promote the laying down of arms, reincorporation of
the former combatants into the social, economical and political life of a civilian, and lastly security against
criminal organisations involved in for example homicides, massacres or attacks on political movements.
Item 4 addresses the promotion of new approaches ensuring to handle the illicit drugs problem from a
perspective that is both gender- and equity-based as well as considering the public health and general
human rights. Item 5 aims to bring justice to the victims of the conflicts and fight against impunity. This
through the means of for example clarification of the circumstances, aid in the search for missing loved ones
and repairing injury to both entire territories, groups of people and individuals. The final item, item 6, aims
1
to maintain and promote the implementation and enforcement of the peace agreement, also functioning as a
forum to bring resolutions to any disputes. The European Union (EU) has been part of the negotiations and
are also part of the final clause, along with the other countries involved, and are entitled to help with the
implementation. Furthermore, both UNESCO and UNDP are involved in helping with the reincorporation.
[2]
The Agency for Reincorporation and Normalization (ARN), or Agencia para la Reincorporación y la
Normalización in Spanish, is a presidential agency that is involved in the realization of item 3 of the
peace agreement and the process of reintegration into society. ARN has been active since 2003 in advising
demobilized individuals who wants to revert to the life of a civilian. The agency formulates that their
mission is to [4]:
"Lead and coordinate the design and implementation of the reintegration and reincorporation
public policy, as well as its territory management, contributing to the peaceful coexistence, the
culture of legality, reconciliation and sustainable development."
In order to provide the people following the reintegration route a good chance of becoming part of the
society again, access to geographical spaces with housing was organized with the main purpose to maintain
the ceasefire between FARC and the government, and also to prepare the former FARC members for
reintegration into a civilian life [5]. This was done in compliance with item "3.1 - Agreement between
the National Government and the FARC-EP on the Bilateral and Definitive Ceasefire and Cessation of
Hostilities and the Laying down of Arms" in the final agreement [2]. These zones were created between
December 2016 and February 2017 and there were two types called ZVTN and PTN, where ZVTN stands
for Transitional Rural Normalization Zones or Zonas Veredales Transitorias de Normalización in Spanish,
and PTN stand for Transitional Normalization Points or Puntos Transitorios de Normalización in Spanish.
They were operated for about 8 months until all of the former FARC members, who followed the first
process, got their citizenship, the right of free movement and the option of not participating any further in
the reintegration. After this, in August 2017, the zones were transformed into Territorial Spaces for Training
and Reincorporation (ETCR), or Espacios Territoriales de Capacitación y Reincorporación in Spanish, all
in accordance with item "3.2 - Reincorporation of the FARC-EP into civilian life – in economic, social and
political matters – in accordance with its interests" of the Final Agreement. The ETCR’s were thought
to be more permanent, although not fully, and with this transformation came efforts on implementing for
example robust housing solutions, education, productive projects, health and reintegration. [6][7]
As the ETCR villages had been active for 24 months in August of 2019, they were yet again transformed.
This time into AETCRs, or Former Territorial Spaces for Training and Reincorporation and Antiguos
Espacios Territoriales de Capacitación y Reincorporación in Spanish. This meant that the villages lost
their temporary status and is now a permanent home for those who wishes to stay. Today, there are 24
active AETCRs that are all managed by ARN and they are working on how to handle difficulties with
sustainability that has arisen with the transition into permanent communities. The sustainability applies to
both the economical and social reintegration route, and should furthermore be part of the implementations
mentioned in the previous paragraph. Even solutions regarding the access to public services, limitations
on accessibility to the villages and risks related to the nature of the geographical areas are part of the
implementation. A major part of maintaining a sustainable community is the requirement of an energy
system that can provide a secure and reliant electricity supply. This energy system should be resilient to the
climate and prerequisites of the location, but also built to ensure that all activities related to the reintegration
could be performed without interruptions and without harming the surrounding environment and wildlife.
[7]
2
1.2 Problem Description
In this study, one of the AETCR villages was chosen to be further investigated, namely AETCR Llanogrande.
As mentioned in the previous section, a secure energy system is of great importance to create good prerequi-
sites for reintegration. However, the grid in Colombia, and AETCR Llanogrande, suffers from power
outages that usually lasts less than 8 hours, but sometimes up to a day and a half according to the ARN
Administrator and Engineer Néstor Fernández [8]. Even though they are not very frequent and only happen
once every one or two months on average, it creates issues for providing the energy that is necessary for the
steps of the reincorporation route, and is what lays the base for the purpose of this study. Furthermore, the
aim and objectives followed by the scope and limitation are presented in this section.
1.2.1 Aim and Objectives
The aim of this study is to propose several sustainable energy systems for AETCR Llanogrande that
are reliable and resilient to the prerequisites of the geographical location. The system should aid in the
reintegration of the former combatants in the sense that it should improve the quality of life through energy
security while ensuring that all the productive projects can be performed. The systems should also aim to
maximize the social benefits, while considering the economical and environmental aspects.
The study is divided into three objectives, where the energy system should:
• Be designed in a way that minimizes the economical costs while still fulfilling the requirements of
the village.
• Aim to reduce the environmental footprint in terms of emissions and to minimize the ecological
impact of the location in a sustainable way.
• Maximize the social benefits in terms of integrating the former combatants into the life of a civilian
in a sustainable way.
Based on the objectives above, two research questions were formulated:
1. What is the best design for an energy system that focuses on each of the three objectives separately?
2. What is the best design for an energy system that combines all of the objectives?
1.2.2 Scope and Limitations
In order to create a sustainable energy system, the only energy sources considered for implementation are
renewable. More specifically involving solar, micro-hydro and biomass. To counteract the fluctuation of the
available energy supplied from renewables, energy storage must also be considered. Different combinations
of the available technologies will be investigated and evaluated based on the three chosen objectives. No
economical boundary has been set for the implementation, but it is however of great importance to propose
a system that is economically feasible.
The system should be designed to withstand the prerequisites of the specified location, based on both
energy availability and potential difficulties caused by the environment that could affect the system. Due to
lack of physical measurements, the proposed design was based on simulation softwares and mathematical
formulas. All on site measurements on the location will be performed by locals.
3
2 Methodology
This chapter includes the sections Method, where the approaches and research methods are introduced.
The parameters that will be used for evaluating the different systems created under this project are listed
in section Key Performance Indicators, and how this master thesis research is connected to the sustainable
development goals is discussed in section Sustainable Development Goals. The softwares used in this
research are also presented and explained in the section called Softwares.
2.1 Method
This project was based on a previous study of the AETCR Llanogrande in Colombia, made by MSc students
taking the polygeneration course named MJ2503, Small-scale Polygeneration at the Royal Institute of
Technology (KTH) in Stockholm, Sweden [9]. The report written in that course regarding the village
AETCR Llanogrande was what laid the base for this master thesis research, where a further theoretical
investigation was performed. The approach used was a qualitative approach, where the data was obtained
through literature research as well as field studies. Both a deductive and inductive approach was used.
Deductive since a hypothesis of an improved energy system was developed and new confirmations could
be preformed, and inductive due to the field study where observations of a certain pattern was confirmed
which then led to a theory. The study was performed remotely, and the additional local information that
was not included in the previous report about AETCR Llanogrande [9], was provided from the contact
persons in Colombia working for ARN, Coordinator Carolina Sofía Rodríguez Rodelo [10] and ARN
Administrator and Engineer Néstor Fernández [8]. The required measurements in the surrounding area
of AETCR Llanogrande were provided by Mr. Fernández since it was not possible to perform them first
hand. The contact with the ARN representatives in Colombia was kept constant during this study, to collect
needed local information. When the measurements within the field study were obtained by Mr. Fernández,
a cross sectional research method was used. This method is often used when different samples are taken
during the same period of time [11], and in this case the measurements were performed at several positions
in the same day.
A pre-study, including the technologies that were presented in the previous report of AETCR Llanogrande
[9] was preformed. Furthermore, an in-depth study regarding new implementations of technology and a
recommendation considering the choice of equipment was presented. How the different technologies were
operating as well as the factors of greatest interest for future installations are mentioned in this report.
Several scenarios were modelled and each scenario was compared to a base case scenario which represented
the current energy situation in AETCR Llanogrande. The different energy fields that were considered for
future implementations were solar, wind, micro-hydro, biogas producing technologies and energy storage.
Investigations of how an increase of the population, energy demand and access to biomass in AETCR
Llanogrande affects the energy system was performed, as well as scenarios where the energy system is
either self-sufficient or connected to the grid. The weather data for the location was downloaded from
PVGIS, and MATLAB was used for system calculations. All simulations regarding the electricity system
were conducted through HOMER Pro to find the most suitable system.
The results were analysed based on the three objectives; economical, environmental and social. A sensitivity
analysis was also made in order to examine the reliability of the results. The results of the most suitable
energy system for each objective are presented, but also a combined energy system where all objectives are
considered.
4
2.2 Key Performance Indicators
In order to compare the different scenarios and energy systems, a few Key Performance Indicators (KPIs)
were chosen for each of the different objectives. These KPIs were chosen based on their ability to show the
performance of the system.
Economical
1. Net present cost (NPC)
The NPC consists of the present value of all the costs over the lifetime of the system. The costs
include the cost of all initial system components, the cost of any component replacement and the cost
of maintenance. [12]
Secondary Economical KPIs
2. Initial Capital Cost
The initial capital cost includes the investment costs for major initial purchases that are meant to last
for a longer period of time [13]. The initial capital cost for the entire energy system was calculated for
each of the scenarios, where the initial capital cost for each of the technologies were added together.
Environmental
3. The renewable fraction in the electricity mix
Depending on the design of each of the scenario’s energy system, various amounts of the different
technologies were used. This entailed a varying amount of renewable energy in the final electricity
mix of the village. Through the software HOMER Pro and the average amount of renewables used in
the grid, the renewable fraction (RF) was estimated.
4. The amount of reduced CO2 emissions from cooking.
The CO2 emissions from cooking mainly comes from the use of LPG. By using biogas, the current
LPG demand could be reduced or removed, which entails in a reduction of CO2 emissions. The
reduction are estimated based on how many gas bottles that has to be bought each month.
Secondary Environmental KPIs
5. The amount of CO2 emissions throughout the usable lifetime of the electricity system
Through calculations of the total electricity production throughout the usable lifetime of the system,
the total amount of CO2 emissions were estimated where the emissions for each technology was
summed up.
5
2.3 Sustainable Development Goals
The United Nations (UN) has developed a blueprint concerning the Sustainable Development Goals (SDGs),
that should be reached by 2030. In short, the UN summarizes that the SDGs are about "peace and prosperity
for people and the planet, now and into the future" [14]. The SDGs are presented as 17 goals, holding a
total of 169 targets that should all be achieved to create a better and more sustainable future. The goals are
put in place in order to address the global challenges that Earth and its inhabitants experience, for example
regarding climate change, environmental degradation, inequality, poverty, peace and justice. The goals are
all interlinked in the sense that you cannot fully achieve one without also handling at least a few others, and
nor should one goal be fulfilled through neglecting to achieve another. The 17 goals are displayed in Figure
2.1 below. [14]
Figure 2.1: All goals included in the Sustainable Development Goals. [15]
However, in this study the focus was on only three of these goals. Namely the ones presented here below
in Figure 2.2, Figure 2.3 and Figure 2.4, where the goals are summarized in short next to each figure. The
SDGs were chosen based on the aims and objectives presented in Section 1.2.1 and the connection to the
study is also presented below.
Figure 2.2: Goal 7. [16]
The first SDG that was directly connected to this
study was goal number 7 - Affordable and clean
energy. This goal has its focus on ensuring affordable,
reliable, sustainable and modern energy, which was
also one of the objectives in this study. The world has
become more aware of the environmental situation
and has started to make progress towards Goal 7,
with a larger share of renewable energy sources in the
electricity sector. [16]
Within SDG 7 there are 5 different targets, where target 7.A embraced this study and is defined as follows:
"7.A By 2030, enhance international cooperation to facilitate access to clean energy research
and technology, including renewable energy, energy efficiency and advanced and cleaner fossil-
fuel technology, and promote investment in energy infrastructure and clean energy technology."
[16]
6
Figure 2.3: Goal 8. [17]
The second connected SDG is number 8 - Decent
work and economic growth. By having a sustainable
and inclusive economic growth aiding in the
development of reaching a better environment, more
descent jobs and living standard [17]. In this study
one of the objectives was to created new jobs, but
a focus of increase the living standard was also
included in this research.
Figure 2.4: Goal 11. [18]
The last connected SDG is Goal number 11 -
Sustainable cities and communities. The goal is
mainly focusing on that new urban regions are
planned and built in a more sustainable and safe way
[18]. This was also considered in this study since the
investigation of the energy system was performed by
looking at future scenarios. Those scenarios handles
the possibility of a growing population and energy
demand, but also how the energy system needs to be
built to manage expansions in a sustainable way.
7
2.4 Softwares
In this section, all the used softwares are presented and described. The various softwares used for data
collection, simulations and calculations are PVGIS, HOMER Pro and MATLAB.
2.4.1 PVGIS
PVGIS, or Photovoltaic Geographical Information System, is a software that is developed by the European
Commission Joint Research Centre (JRC) that is built for solar research assessments. PVGIS provides an
interactive tool that supplies both monthly, weekly and hourly data of global solar irradiance, temperatures,
wind speeds and sun height as well as several different performance calculation services [19]. The data is
not on site measured data but estimations based on satellite pictures and highly advanced algorithms. The
average error has however been concluded to be only a few percentage units when compared to measured
data. The fact that the tool is based on satellites pictures allows for data to be collected almost anywhere
on the globe. This is a major advantage with projects involving remote places that are most likely lacking
large series of measured data, thereof making the error a reasonable trade-off. In this project, PVGIS was
the main source used for data collection concerning the solar resource. [20]
2.4.2 HOMER Pro
HOMER Pro, or Hybrid Optimization of Multiple Energy Resources Pro, is a microgrid software built to
design both on- and off-grid distributed generation systems that is developed by the National Renewable
Energy Laboratory (NREL). HOMER evaluates both the technical and economical parts of a project. The
technological part considers both the electrical and thermal demand of the project and finds technological
combinations that covers it based on available technologies and the prerequisites of the chosen location. As
it evaluates the technologies, it also evaluates the economical aspect of the project, both presenting initial
investment costs, the net present cost and the summarized cost for each technology while also searching for
the lowest possible cost. HOMER Pro was used to simulate the sizing of the entire energy system. [21]
2.4.3 MATLAB
MATLAB is an acronym of Matrix Laboratory, which is a software initially built as a matrix calculator that
over the years has been developed into a great mathematical tool for engineers and scientists. It can be
used for e.g. calculations, visualisation, iterative analysis and design processes. MATLAB was utilized to
perform the calculations regarding both biomass and hydro power. [22]
8
3 Case Study
This study was as mentioned specifically looking at AETCR Llanogrande in Colombia. In this chapter, an
overview of the energy situation in Colombia is presented, including political strategies, energy generation
and consumption as well as cooking conditions. Also, all necessary information attached regarding the
specified location is stated in Section AETCR Llanogrande, where the main focus has been on the available
energy resources and the demand of the village.
3.1 Colombia
Colombia is located in northern South America and bordering the five countries Panama, Venezuela, Brazil,
Peru and Ecuador. Colombia has a population of 49.1 million people, with 81.4% of the total population
living in urban areas and the remaining part living in rural areas. 97% of the population in Colombia has
access to electricity, and the 3% without electricity live in rural areas. [23]
In 2018 the total electricity consumption in Colombia was 71.9 TWh, and the energy consumption by sector
and the energy consumption by source are presented in Figure 3.1 and Figure 3.2. The sectors consuming
most of the energy in the country are transport, industry and residential, and the source that generate the
largest part of the consumed energy is oil products with 146 TWh. [24]
Figure 3.1: Total energy consumption
by sector. [24]
Figure 3.2: Total energy consumption
by source. [24]
Colombia has good opportunities to use hydro as an energy source and in 2019 an installed capacity of
12,258 MW was producing electricity along the rivers [25]. As can be seen in Figure 3.3, the largest share
of the generated electricity is from hydro with 59.9 TWh. Thereafter is natural gas with 11.6 TWh and coal
with 4.5 TWh. [24]
Figure 3.3: Electricity generated by source. [24]
9
Colombia has plans on developing their power transmission network, since the national interconnected
system only covered 48% of the country’s area, including 96% of the population in 2017. The network is
connected with the neighboring countries, Ecuador, Peru and Venezuela, and plans to expand the network
has been announced, for example regarding connections with Panama. In 2015 more than 60% of the
electricity market was represented by three companies, Emgesa S.A., ISAGEN and Empresas Publicas
de Medellin (EPM), which are also the three main actors when it comes to the electricity generation in
Colombia [26].
15,000 Colombians die each year due to air pollution, and approximately 7,000 of those deaths are caused
by cooking and heating with solid fuels [27]. As can be seen in Table 3.1, the most common cooking
fuel in urban areas are liquefied petroleum gas (LPG), while firewood and LPG are mainly used in rural
regions [28]. Another thing that improves the living standard is clean water. In 2015, 3% of the Colombian
population lacked access to clean drinking water [29]. It corresponds to 1.4 million people, all living in
rural regions [30]. The same year, 84% of the population had access to basic sanitation services [29].
Table 3.1: Percentages of cooking fuels used in
urban and rural areas. [28]
Cooking fuel Urban [%] Rural [%]
LPG 90.9 45
Electricity 4.5 2.7
Firewood, straw 1.9 49.3
Kerosene 0.2 0.2
Coal, lignite 0.1 0.9
No cooking in household 2.5 1.7
Colombia has policies regarding how to improve the energy situation in the country. One of the policies
is the national energy plan named Plan Energético Nacional Colombia: Ideario Energético 2050. This
national energy plan was established in 2015, where the political energy goal until 2050 was presented.
The aim is to reach the internal and external energy demand as effectively as possible, with a minimal
environmental impact. Several scenarios of how the energy sector could be developed until 2050 were also
introduced in the plan, aiming to install reliable energy sources for a more sustainable future. [31]
In addition, the government of Colombia has established a law, law 1715, that encourage companies to
invest in renewable energy technology. The law was sanctioned in 2014 and gives non-conventional energy
projects the opportunity to apply for subsidies for renewable equipment in rural areas. Renewable energy
technology has not been financially feasible in Colombia, and this law gives companies a chance to chose
a more sustainable alternative for energy supply. However, the Colombian government still has other laws
that counteracts law 1715. One example is law 1117, which concerns the needed fuels for energy services
in rural areas. The law subsidises the transportation of fuel as well as the needed fuel for generating the
electricity. This law is an obstacle when it comes to choosing the renewable alternatives since the fossil
fuels are subsidised. [32]
10
3.2 AETCR Llanogrande
One of the 24 AETCR villages that ARN is managing is called AETCR Llanogrande and it is positioned at
the coordinates 7.07538◦, -76.24351◦. The AETCR is located around 1,490 m above sea level on a canyon
in the area of Chimiadó close to a nature reserve [8]. AETCR Llanogrande shares space with a village called
Llano Grande which can be seen in Figure 3.4 and Figure 3.5. Llano Grande is located in the northwestern
part of Colombia and is a part of the municipality of Dabeiba, which is in the western sub-region of the
department of Antioquia [33].
Figure 3.4: Map of Colombia. [34] Figure 3.5: Map of Llano Grande. [34]
AETCR Llanogrande has a total area of 3,840 m2 and at the time of this study there are 20 buildings in that
area, which can be seen in Figure 3.6. 17 of those buildings are households and the other buildings consists
of a nursery, library and recreational area [33]. The AETCR had potential to grow, but further information
regarding the extent of how much was not available. The average monthly electricity demand of the village
was 11,550 kWh and according to Mrs. Rodríguez Rodelo more electricity was consumed at night, but no
electricity measurements were performed after 6 pm. The high nightly electricity demand may be related
to the 49 streetlights with 100 W reflectors. The village also had a 177 kVA diesel generator that operated
during power outages [8]. The diesel generator consumed around 8 l of diesel before 6 pm, and between
9 - 10 l after that time [10]. The average amount of emissions for diesel is 2.69 kgCO2-eq/l [35]. Pictures
of the generator can be seen in Appendix A.1.1. The AETCR is connected to the grid which was supplied
by Empresas Públicas de Medellín (EPM) and the price was 3,920 USD ($14,000,000 COP) for 3 months
which is equivalent to 0.113 USD/kWh [8]. According to Mr. Fernández the grid connection was stable
and the power outages were estimated to total around 40 hours per year, where a power cut usually last for
2 - 8 hours, but on rare occasions up to a day and a half. The CO2 emissions from the Colombian grid was
estimated to be 0.11 kgCO2-eq/kWh [36]. No information could be found regarding the selling price of
electricity to the grid and it was assumed to be half the buying price, namely 0.0565 USD/kWh.
11
Figure 3.6: Overview of AETCR Llanogrande. [37]
The 17 households had access to several household technologies, e.g. TV, laundry machines, fans, electrical
ovens and stoves, and refrigerators, but they also had other household appliances for family or personal
use. There was no existing fixed telephone service in AETCR Llanogrande, however there were two
inhabitants that offered a PIN service, i.e. internet service [10]. The internet was limited and according
to Mrs. Rodríguez Rodelo only rated as a 2 on a scale of 5. The fuel used for cooking was LPG and the
average monthly consumption of gas was one 40-pound (18 kg) LPG gas bottle per family of 3. ARN was
providing the AETCR with gas since there was no existing gas network [8]. The LPG cost was 1,340 USD
(or 5,000,000 COP) and the average amount of emissions emitted from LPG is 1.7 kgCO2 for 1 l of LPG
[38].
The water used in the village was collected from a water source 2 km from the AETCR, in the mountain
area. A drinking water treatment plant (PTAP), Planta de Tratamiento de Agua Potable in Spanish, was
implemented in order to increase the water purification capacity [10]. The PTAP required no electricity,
but Mr. Fernández stated that the plant was under reconstruction and it was possible that the PTAP would
require electricity in a later state. There were also 8 septic well tanks in the village, with the purpose to
separate the gray and black waste water, where each tank accommodated 4,500 l of water [10]. The water
was discharged through a drain into the mountain area when it had passed the septic well tanks and the
sludge was not further used. The PTAP required maintenance once every six months, where a company
certified final disposition of the equipment [8]. Hot water, which would mainly be used for comfort, was
not a priority in AETCR Llanogrande according to the contact persons.
3.3 Available Energy Resources
In order to properly dimension the energy system, the available resources of the location needed to be
evaluated. Since one of the objectives was to create a sustainable society, the only potential new installments
of energy would produce their power from renewable energy sources. The initial resources considered are
solar, wind, hydro and biomass.
However, the data collected from PVGIS [19] as well as from the Global Wind Atlas [39] and Meteoblue
[40], along with the findings in the base study [9] unanimously concluded that the wind speeds are below
2 m/s during most of the year, and even below 1 m/s almost half the year. Most wind turbines needs wind
speeds of at least 3 m/s to start rotating and create small amounts of electricity. In rare cases the cut-in
wind speed is as low as 2 m/s for small scale turbines [41], but the small amount of produced electricity at
that speed can not be justified when it comes to the cost of the investment. Hence, wind turbines was not a
12
feasible option for the location and it was not included in any further evaluations. The available resources
were therefore limited to solar, hydro and biomass.
3.3.1 Solar
AETCR Llanogrande is located in a zone of humid equatorial climate, or a tropical rainforest climate,
which is defined to experience stable warm temperatures and a high relative humidity with small variations
throughout the year [42]. The average daytime temperature is usually somewhere between 20◦C and 22◦C,
with peaks of up to 28◦C, whereas it during the nights can drop as low as 13◦C [19][43]. The relative
humidity is usually around 95% [19]. There is on average 14 days each month that are partly cloudy,
meaning that there is between 20% to 80% cloud cover. The majority of the remaining days have an
overcast, or a cloud cover over 80% [40]. Diagrams displaying the cloud cover can be seen in Appendix
A.1.2. According to Mr. Fernández, there is also a daily presence of fog in the AETCR. Even though
there are clouds and fog, the solar irradiation is still quite high. The estimated average monthly global
irradiance in 2015 on both a horizontal plane and with the optimal tilt angle, estimated to be 5 degrees in
PVGIS, can be seen in Figure 3.7 [19]. Hourly data for several years was also collected, where the average
daily irradiation for each month can be seen in Appendix A.1.3. Furthermore, as with all renewable energy
sources the resources are fluctuating and often not very stable, varying from hour to hour and day to day.
The sun for example is only available during the days, with its highest values around midday, whereas no
energy production at all is possible during the night. The amount of irradiation also varies greatly between
days and sometimes seasons.
Figure 3.7: The average monthly global irradiance on a horizontal plane
with a 5 degree tilt angle in 2015. [19]
After consultations with Mrs. Rodríguez Rodelo, it was concluded that the buildings are transitory and
movable at any time, and that the roofs thereof would not be able to carry the weight of any solar panels.
However, there were available ground areas within the AETCR that could be utilized, as well as potential
space in the surrounding community if the landowners could benefit from the installation. [10]
13
Figure 3.8: Existing PV panels in
AETCR Llanogrande. [8]
Six solar panels which can be seen in Figure 3.8 were
already installed in the AETCR, and according to
Mr. Fernández the panels were efficient and had been
installed 3 years ago [8]. The solar panels were of the
brand Jinko Solar, and were manufactured in China.
They are polycrystalline panels with efficiencies of
16.5%, the weight of one panel was 19 kg and
the dimensions were 992 x 1,650 x 40 mm [44].
Moreover, one panel had a power output of 270 W
at standard test conditions (STC) with an irradiance
of 1,000 W/m2 [8]. During the time this report was
written, the market price of the panels were 270 USD
each ($957,600 COP). However, as will be mentioned
in Section 4.1, the market price for solar panels has
seen major decreases over the last 10 years, thus the
purchase price for these panels were most probably
higher than the mentioned price [44].
At the time of this report being written there were 4 batteries installed in the existing system, although no
further information about capacity nor type was attained.
3.3.2 Hydro
As mentioned before, the AETCR is located in an area of tropical rainforest climate, meaning that it is hot
and wet during all months and the average precipitation is between 2,000 and 10,000 mm per year [45].
In the area of AETCR Llanogrande there are heavy rainfalls throughout the whole year, and the monthly
average precipitation is 281.5 mm [40]. The precipitation for each month is presented in Appendix A.1.2.
In the region of the AETCR a dry season occurs from January to April each year, which affects the water
flow rate of the rivers in the area [10].
According to the base study [9], there were two rivers close to the AETCR, where possibilities to use
the rivers for energy production were mentioned but no existing hydro power was installed. With further
investigation of the area an additional river was found, and through conversations with Mr. Fernández, it
was clarified that the rivers were more in the size of streams, at least during the dry season occurring during
the creation of this report. The locations of the streams can be seen in Figure 3.9 and the only stream that
was evaluated in this research was the one on the right side of the AETCR. This due to the other two streams
being located in a mountain area with limited availability, whereas the necessary measurements were not
possible to obtain [8]. A requirement for any potential hydro power installments was that the equipment
placed in the water had to be covered, since cattle could pass freely through the rivers and could otherwise
attain injuries. [9]
14
Figure 3.9: The three streams close to AETCR Llanogrande. [37]
To be able to estimate the electricity that the streams could generate, measurements regarding the flow in
the river was supervised by Mr. Fernández. A measurement manual made by Turbulent [46] was sent to
Mr. Fernández as a guideline. The manual can be found in Appendix A.2, in both English and Spanish.
The measurements were performed on the stream in the natural reserve area close to the AETCR, as can be
seen in Figure 3.10. The surroundings were less demanding at the site in the figure, although accessibility
was still limited due to rough terrains consisting of falls as high as 15 m and plenty of vegetation. The
equipment that was used was a steel measuring tape, an empty airtight plastic bottle and a stopwatch. To
secure the reliability of water flow measurements, five different places were selected along the stream and
the measurements were repeated three times at each place. The depth along the stream was varied since the
terrain consisted of many rocks. Thereof, the depth was measured at three different points: in the beginning,
in the middle and at the end of each selected route. An average of the water flow was calculated for each
route, where the highest measured flow was 50 l/s and the lowest 20 l/s. These values represented the water
flow during the dry season that occurred at the time of the measurements. According to Mr. Fernández the
water flow during the dry season was reduced to around 50% of the flow during rain season, which resulted
in the lowest and highest water flows being 40 l/s and 100 l/s during the rain season. The average water
flow of the stream was then estimated to 35 l/s during the dry season and 70 l/s during the rain season.
The average flow speed of the water was measured to be around 0.6 m/s on average during dry season,
whereas it was assumed to be twice that during rain season, namely 1.2 m/s. These presented values were
the averages of all routes, where all the collected data from the measurements as well as pictures of the
measurements of the stream can be found in Appendix A.1.4.
Figure 3.10: The stream close to AETCR Llanogrande.
15
3.3.3 Biomass
The majority of the biomass that could be collected in AETCR Llanogrande was wet biomass from animal
manure. The AETCR had 1,000 laying hens which were included in the collective projects with ARN
and the inhabitants of the AETCR [10]. The inhabitants also had their own productive projects within
livestock, and knowingly there were 200 hens and 10 bovines in the area. However, more personal projects
were under development and the projects were; five with laying hens, two with broiler chickens and five
with pig farming [9][33]. Since it was personal projects, information of exact numbers of animals was not
available, but all the livestock projects in the area could be possible sources to generate biomass for biogas
and electricity production [8].
Besides the livestock projects there were some planned agriculture projects that could potentially generate
biomass in the future. One of the collective projects currently under implementation was vegetable produc-
tion in micro tunnels [33]. The area for agriculture was however not estimated and therefore not considered
in this research [10]. Other personal agriculture projects were; one with bananas, two with lulo and one
with coffee [33].
Another biomass source is the household waste. The estimated non sorted domestic waste from AETCR
Llanogrande was 5 tonnes per month [10]. A compost project lead by Mr. Fernández was under development,
where education of the importance to sort waste was in focus. Other personal productive projects were
within services and commerce. Those projects were the following; one restaurant, one music group, one
cabinet maker, one bakery, one store, one miscellany and one PIN service (as mentioned earlier) [33]. From
most of the services waste can be collected and used as biomass.
3.4 Scenarios
In order to further extend the reliability of the study, various scenarios were presented and evaluated. The
first scenario was designed to be a base scenario including three different variations. The second scenario
was focused on evaluating the effects of a social development with a constant population, while the last
scenario evaluated a potential population growth. The current energy system, including the accessible
resources needed to cover the energy demand mentioned in Section 3.2, was included in the simulations of
all scenarios. Although, the grid connection was excluded in the Off-Grid scenario.
1. Base Scenario
The Base Scenario consisted of three different sub-scenarios, which are presented below. The current
electricity demand of 11,550 kWh per month was kept constant for each of the three sub-scenarios.
1.1 Business As Usual (BAU)
The first sub-scenario was based on the prerequisites of the current situation in AETCR Llano-
grande and designed accordingly, along with the installed technologies and usage of the grid. It
was mainly used as a starting point for evaluation of the impact from the implemented changes
in the other scenarios. No new installments were considered.
1.2 Modest Implementation of Technologies (MIT)
The second sub-scenario evaluated the implementation of more renewable energy technologies,
where the changes to the existing system were not too major. It was designed to supplement the
existing system and could represent a first step in becoming more self-sufficient. Furthermore,
implementing more renewable technologies would increase the renewable energy fraction and
decrease the negative impact on the environment. In this sub-scenario, all available biomass in
the AETCR was assumed to be collected and used to produce biogas, primarily to replace the
demand of LPG for cooking and secondly to be converted into electricity.
16
1.3 Off-Grid
In the third sub-scenario AETCR Llanogrande was assumed not to be connected to the grid,
in order to evaluate a potential energy system where the village has become self-sufficient.
Cases with and without the generator were considered and the same prerequisites considering
the biomass as in the MIT sub-scenario were assumed.
2. Social Development with a Constant Population
In accordance with a developing society with an improving standard of living, the energy consumption
is most likely increasing as well. This scenario was divided into two sub-scenarios where the
population was kept constant. One focused on an increased electricity demand and the other on
an increased access to biomass. The two sub-scenarios were calculated separately, but analyzed both
separately and collectively, and compared to the BAU scenario.
2.1 Increased Electricity Demand (IED)
The sub-scenario aimed to evaluate the energy systems characteristics in the case of an electricity
demand increase. In this sub-scenario it was assumed that a 10%, 20% and 30% increase were
all plausible, whereas an extreme case of a 50% increase was also added for analytical and
evaluation purposes.
2.2 Increased Access to Biomass (IAB)
In consistency with the increases in the IED sub-scenario, the total biomass was increased with
10%, 20%, 30% and 50%. The purpose of this sub-scenario was to substitute the demand of
LPG for cooking into biogas, and potentially using the overproduction of biogas for electricity
production.
3. Increased Energy Demand with a Growing Population
Since more people could move to the AETCR, and the settled families might continue to grow,
another potential scenario was built on a population growth. A growing population would result in an
increased energy demand, and an evaluation of how this would affect the requirements on the energy
system was needed.
3.1 Population Growth - Electricity (PGE)
This sub-scenario aimed to evaluate the effects on the electricity demand in case of an increasing
population. The electricity demand curve was increased through increasing the population by
5%, 10% and 15%. The demand per capita was kept constant, whereas the demand would be
increased due to the higher number of inhabitants requiring electricity.
3.2 Population Growth - Biomass (PGB)
In this sub-scenario, the aim was to evaluate how an increased population affected the biogas
system. The population increased with the same percentage as in the PGE sub-scenario, 5%,
10% and 15%. With more inhabitants the LPG demand increased as well as the amount of
waste in the AETCR. However, the amount of manure was kept constant since the numbers of
livestock remain equal as in the MIT sub-scenario.
17
4 Technologies
The following chapter introduces the different technologies which may be appropriate to install to provide
energy to AETCR Llanogrande. For electricity generation solar power with a further investigation of
different types of photovoltaic panels, thermal collectors, photovoltaic thermal collectors and inverters was
performed, and an evaluation of the possibilities to install micro-hydro is included. A research regarding
biodigester technologies, diesel generators and how to upgrade the produced biogas for operation in a
converted diesel generator is included in this chapter. Last but not least an energy storage section focusing
on battery energy storage is presented as well.
4.1 Solar
When looking at all the commonly used resources on Earth that could be used for energy production, solar
energy is by far the largest resource available. The amount of energy that reaches the surface of this planet
per hour from the sun alone, is many times more than all the other resources combined and enough to
cover the entire energy demand of this planet for a whole year. Collecting that energy and transforming
it into usable energy to meet the demand has been both quite expensive and rather inefficient, foremost
considering electricity production, making the market penetration more difficult. Especially in developing
countries where the financial resources needed to implement it may not be possible to provide. Although,
the technologies are constantly developing and major improvements have been seen just over the last 10
years. The global capacity weighted averages of the total installed cost for solar power projects decreased
with almost 80% between 2010 and 2019, going from around 4,700 USD/kW down to 995 USD/kW. During
the same years, the Levelized Cost of Energy, or LCOE, went down with 82%, from 0.378 USD/kWh to
0.068 USD/kWh on utility-scale projects [47]. Furthermore, when looking at the electricity market in
for example Sweden, the electricity price for solar power produced electricity has decreased with 89%
over the last 10 years, showing that the technology development and the availability has experienced great
improvements [48]. There are however of course variations in costs depending on what type of technology
is used and the size of the project. [49][50]
The decrease in costs has created a vast increase in the amount of installed capacity throughout the world,
aiding towards further cost reductions and more research. The price is expected to keep decreasing, although
not as fast as previous years [51]. In accordance with the worldwide increase of new installments, the
implementation of solar power in Colombia has been becoming extensively more popular and feasible as
well. The country has gone from 9 GWh of produced electricity in 2016 to 132 GWh in 2019, an increase
of almost 15 times as much generation [52]. In Figure 4.1 below, the increase in electricity production over
the last 20 years can be seen.
Figure 4.1: The yearly amount of produced electricity
from solar power in Colombia. [52]
18
There are three radiation components from the sun that could be utilized, and that is the direct normal
irradiance (DNI), the diffuse horizontal irradiance (DHI) and the global horizontal irradiance (GHI). The
DNI is the amount of irradiation from the beams that hits a surface perpendicularly. If the surface of a solar
panel is not perpendicular to the beams, losses will occur along with the magnitude of the incidence angle.
The DHI is the irradiance that has been scattered in the atmosphere but yet managed to reach a horizontal
surface. The DHI irradiance does not have a set direction in which it travels, but is going in all directions.
The GHI is the combined irradiance from both the DNI and DHI on a horizontal surface, where the DNI is
recalculated with the incidence angle. The GHI is usually the component evaluated when looking at solar
power systems. This is displayed in Figure 4.2 below.
Figure 4.2: Visualization of the different types of irradiance on a plane. [53]
There are several different ways to collect the solar energy, with the most common ones being through
photovoltaic (PV) panels, solar thermal (ST) collectors, photovoltaic thermal (PVT) collectors and concen-
trated solar power (CSP). CSP was however not taken into account in this study, due to the technology
being very expensive and not suitable for small-scale projects. An introduction to the technologies can be
seen in the subsections below.
4.1.1 Photovoltaic Panels
The most common way of utilizing solar energy was through PV panels, which in essence consist of
semi-conducting materials that transforms the irradiation of the sun into direct current (DC) electricity.
There are several types of PV panels as well, all with varying efficiencies, voltages, currents, sizes and
costs to mention a few. Three of the most commonly used types are monocrystalline, polycrystalline and
thin-film panels. The three types are displayed in Figure 4.3 below.
Figure 4.3: The three most common types of PV panels, displaying monocrystalline, thin-film and
polycrystalline panels in the same order as mentioned. [54]
The monocrystalline and polycrystalline panels are quite similar in a sense, being made from silicon and
having a resembling design. The main difference between the two was the way they are produced, where
the monocrystalline was made with one silicon crystal per cell, whereas the polycrystalline one had several.
19
This entails that the process for the monocrystalline one was more advanced, time-consuming and hence
more expensive. The average costs for the two panels can be seen in Table 4.1. Due to the more difficult
process, the emissions from production were larger for the monocrystalline than the polycrystalline, but the
efficiency was also higher. A study made by A. Louwen et al. concluded that the harmonized greenhouse
gas (GHG) emissions for a mono- and polycrystalline system would be around 25·10−3 kgCO2-eq/kWh
and 20·10−3 kgCO2-eq/kWh respectively [55]. In this study, the inverter emissions were included in the
the emissions for the PV panels. The results of similar studies regarding GHG-emissions for PV panels
could however be greatly affected by where the panels were produced, where they were used, the way the
study was performed as well as depending on what aspects of the PV panel’s lifetime that was included.
These factors plays a major part when it comes to the results, since the environmental footprint for the
electricity from the grid and certain parts of the process or system being left out or included could affect
the estimation greatly.
The thin-film panel worked by the same principles, but could be made from several different materials and
was usually lighter than the mono- or polycrystalline panels, as well as flexible. Although, the efficiency
was quite a lot lower than for the other types. And even though thin-film panels were usually quite a lot
cheaper, the low efficiency would entail a much larger area of panels in order to produce the same amount of
electricity. AETCR Llanogrande however, does not have an unlimited land area available, since the village
was quite small and a large share of the surroundings are part of a natural reserve. Furthermore, the lifetime
of the panels were not as long, meaning the replacement costs would increase. Due to this, thin-film panels
were not considered a good option and they were excluded from any further evaluation. [56]
The efficiency of both a PV panel and a PV system depends on many different parameters, for example
the efficiency of the individual cells, the amount and type of solar irradiation, the amount of shade and dirt
on the cells, the temperature of the cells (where a higher temperature decreases the efficiency) and several
types of losses on module and system level [57]. Some of the most important characteristics for mono- and
polycrystalline PV panels can be seen in Table 4.1 below, where the O&M costs stands for the operation
and maintenance costs.
Table 4.1: Specifications for average poly- and monocrystalline
PV panels. [58][59][60][61][55]
Polycrystalline Monocrystalline
Efficiency [%] 13-16 15-20
Investment Cost [USD/kW] 3,555 3,585
Replacment Cost [USD/kW] 430 460
O&M Cost [USD/kW/year] 107 108
Lifetime [years] 25 25
Emissions [kgCO2-eq/kWh] 20·10−3 25·10−3
4.1.2 Solar Thermal Collectors
Another way of utilizing solar energy is through transforming it into heat, which could then be used for
heating of domestic hot water or to provide cool air through an absorption chiller for example. This could
be done through a solar thermal collector, where the irradiation heats up the surface which in turn heats up
a fluid that is circulating through the collector. There were many different available versions on the market,
but the most common ones for residential purposes were flat plate- and evacuated tube collectors [62][63].
The flat plate collector consisted of a dark surface that absorbs the solar irradiation and heats a working
fluid located in tubes under the surface, which through the heat exchange also worked as a cooler through
carrying heat away. The working fluid then heats up the water desired to be heated through yet another
heat exchanger. There are two types; one that has an open-loop system and one that has a closed-loop
system. The open-loop, or direct, system circulates the water that should be heated straight through the
collector, either through a pump or through using the natural buoyancy of water of different temperatures.
20
The closed-loop, or indirect, system had a working fluid that was usually circulated through the flat plate
with a pump and then heats up the domestic hot water through a heat exchanger. This system was most
commonly used in colder climate where pure water suffers the risk of freezing and supplements needs to
be added to prevent it. The flat plate collector could heat the water in a range of 30-80◦C. [62][64]
The evacuated tube collector worked by the same principle as the flat plate, with tubes in connection to
an absorbing surface, although the design was quite different. Here the absorber and tubes were placed
inside evacuated tubes, where the vacuum provided good prerequisites to avoid major heat losses. The
collector could both be an open-loop and a closed-loop system. The evacuated tubes were all connected to
a manifold tube at the top, where the heat was either exchanged (if it is a closed-loop system) or collected
(in an open-loop system). The vacuum and the prevented heat losses enables the evacuated tube collector
to reach much higher water temperatures, in a range of 50-200◦C. [62][65]
One of the most common systems for both flat plate and evacuated tube collectors was a thermosiphon
system, either driven by natural buoyancy or a pump. The storage tank where the hot water was kept should
be placed right above the collector. A basic thermosiphon system is displayed in Figure 4.4.
Figure 4.4: The basic layout of a flat plate thermosiphon. [64]
When looking at the availability of technologies in Colombia, it could be seen that the most common
type was the evacuated tube collectors, pressurized by gravity. These collectors averaged a cost of around
350-400 USD/100 l of installed capacity [66]. However, since the gravity driven collectors and storage tanks
needs to be placed above the point of usage in order to build up enough pressure to function properly, that
was not necessarily a good option in AETCR Llanogrande, due to the inability of utilizing roof space. More
suitable alternatives that could handle higher water pressures and where a pump could be used instead of
gravity were more expensive, somewhere between 400 and 500 USD/100 l of installed capacity [66]. Even
though many advantages promoted the evacuated tube collector, the average lifetime of a flat plate was
20-25 years, which is almost double the lifetime of an evacuated tube that lasts around 15 years. This was
mainly due to the evacuated tube collectors being a much newer technology that had yet to be refined. The
efficiencies of the two different thermal collectors varies depending on the difference between the ambient
temperature and the temperature of the water in the collector. The flat plate has a higher efficiency in
warmer climates where the temperature difference was smaller, whereas the evacuated tube collector works
better in colder climates with higher temperature differences. An example of how the efficiency varies
can be seen in Figure 4.5 below, where the efficiency is displayed on the y-axis and the x-axis shows the
temperature difference. The green line represents the flat plate and the red one the evacuated tube.
21
Figure 4.5: Efficiency of flat plate and evacuated tube collectors depending on the temperature difference
of the ambient temperature and the wanted temperature of the water. [67]
4.1.3 Photovoltaic Thermal Collectors
The PVT collectors are a mix of PV panels and ST collectors, also often called hybrid solar collectors.
When looking from above, it commonly looks similar to a normal PV panel, but beneath the surface a
working fluid is passed through tubes and heated through a heat exchanger. The heat absorbed by the fluid
also functions as a cooler of the cells, since the heat is transported away from the surface, thus increasing
the electrical efficiency of the panel. Although, since the purpose of the PVT collector is partly to collect
heat, the temperature on the surface will increase and in turn lower the electrical efficiency. The overall
efficiency of the hybrid collector was a combination of both the thermal and electrical one, which reached
numbers as high as almost 90% during peak hours on some collectors [68]. However, they most commonly
reached a combined efficiency of around 40-70%, which was generally lower than having one PV panel
and one solar thermal collector installed [69][70]. This was mainly due to the two technologies working
in different ways, where the PV cells want as much irradiation as possible but not the heat, and the solar
thermal collector wants the heat generated by the irradiation.
There were two main types of PVT collectors, glazed and unglazed. The glazed one was characterized
by having a glass cover above the PV cells, working as an insulator to better retain the collected heat. This
improved the thermal efficiency, but lowered the electrical one since not as much irradiation reaches the PV
cells and the temperature increase in the cells was higher. Studies show that the glazed PVT was commonly
more efficient than the unglazed one, since the glazing affects the thermal efficiency in a positive way to
a larger extent than the electrical efficiency in a negative way. This was however dependent on testing
conditions and the characteristics of the collector [71].
4.1.4 Inverter
An inverter was a necessary part of a PV system where the produced electricity was converted from direct
current (DC) into alternating current (AC) in order for the residents to utilize it. A typical inverter had
an efficiency that usually ranged from 95-98% [72]. There were three main types of inverters; grid-tied,
off-grid and hybrid. A grid-tied inverter was used when the system was connected to the grid, and no
batteries were needed. The inverter keeps track of the production during the day, utilizes the demand
for own consumption and then sells the rest to the grid. The grid was then used when the production of
electricity did not cover the demand, and functioned as a battery bank for this type of system. The off-grid
inverter was used when the system was not connected to the grid and the overproduction of electricity
needed to be stored in batteries in order for the supply to meet the demand even when the production was
low. The inverter then controls whether the power should be directly supplied to the connected load or if
it should be used for charging the batteries. The hybrid inverters on the other hand could handle both a
grid connection and batteries, balancing the coverage of instant demand, charging of batteries, and selling
22
overproduction to the grid while also using the grid as a backup when needed. [73]
There were also several types of inverters that were designed for various amounts of panels. There were the
microinverters which only handled one panel, the string inverter which handled several panels connected
in strings, and the central inverter which was designed to handle the entire production of the system. The
string inverters has been a very common inverter for usage of non-utility size systems, since they were
rather cheap and did not need to be able to handle very large capacities. It was however not optimal to
use where the installations were prone to be exposed to partial shadowing, for example on a rooftop. If
one of the panels in a string experienced shadowing and stopped producing electricity, all of the connected
panels would also stop producing which could cause large losses. An inverter that instead worked very
well in these types of conditions was the microinverter, which had become more and more common. Since
each panel then had an individual inverter, the panels were working irrespective of each other and only the
panel experiencing partial shadowing would have production losses. This means that the system had the
prerequisites of a larger production and smaller overall losses in those conditions. The microinverter was
however a lot more expensive than the string inverter measured as specific cost. The third type, the central
inverter, was generally used for utility size solar power where the spot was carefully selected and did not
experience partial shadowing. It was a cheaper option for large and reliable systems but was not optimal
for smaller systems. Partly because maintenance was quite advanced and needed to be done by someone
who has had special training, which was not optimal for remote places. [74][75][76]
The AETCR is grid connected but experiences outages and aims to be more self-sufficient, whereas batteries
were also considered in the system model. Specifications regarding the batteries can be seen in Section 4.5.
Furthermore, considering the extra costs of installing microinverters and the more advanced maintenance
of the central inverters, a hybrid string inverter was chosen to be evaluated for the location. In Table 4.2
below, some typical characteristics for hybrid inverters are displayed. The price per kW depends on the
capacity of the unit, a larger capacity will induce a lower kW price.
Table 4.2: Characteristics of a typical hybrid
inverter. [77][78][79]
Hybrid Inverter
Efficiency [%] 95-98
Investment Cost [USD/kW] 160-290
Replacement Cost [USD/kW] 160-290
O&M Cost [USD/kW/year] 50
Lifetime [years] 10
4.2 Micro-Hydro
The field study of the stream close to the AETCR showed that the average flow during dry and rain season
was 35 and 70 l/s respectively, with flow speeds of 0.6 and 1.2 m/s. As research regarding the available
micro hydro technologies on the market was carried out, it became clear that the flow volume and speed
were not large enough to make an installation feasible. Neither from an economic, sustainable, nor energy
production point of view. Even when looking at the implementation of small turbines, most designs require
water flows that are a lot larger than the available one. Some very small turbines were found that could
actually be implemented. However, considering the size of the demand and the small amount of energy
the turbines would produce, it was yet again deemed not to be a feasible investment. Furthermore, the
possibility of an installation causing more harm to the environment than it would aid in the production of
clean energy was imminent. Hence, hydro was onwards not considered for implementation.
23
4.3 Biodigester
Biogas has been used for both domestic and agricultural applications for many years, and the benefits of
using biogas has been discovered and developed in order to be applied in a larger scale, i.e. industries. The
use of biogas has been varying depending on which country it was utilized in. The biogas production in the
United States has been used for electricity and heat production, while almost all biogas produced in China
has been used for cooking. In recent years the interest of using biogas as a fuel in the transport sector has
increased, since it can reduce the greenhouse gas (GHG) emissions, which is an environmental advantage
[80]. In AETCR Llanogrande the main purpose was to use the biogas as a cooking fuel instead of LPG,
and secondarily for electricity production through a generator. An additional advantage of using biogas
as a cooking fuel, beyond the mitigated emissions, was that the expenses could be reduced compared to
purchasing LPG [81].
The composition of biogas contains methane (CH4), carbon dioxide (CO2) and small quantities of other
gases, and when producing biogas a process called anaerobic digestion is used, where an oxygen-free
environment is utilized to break down the organic material [82]. The process consists of four main steps;
hydrolysis, acidogenesis, acetogenesis and methanogenesis [9]. The purpose of hydrolysis is to break
down organic compounds into smaller organic compounds in order to make the digestion for the anaerobic
bacteria easier. The compounds are further broken down in the next step called acidogenesis, and in
this stage volatile fatty acids, alcohols, CO2, ammonia (NH3), hydrogen sulfide (H2S) as well as other
byproducts are produced. In the third step acetogenesis, the acetogens creates acetic acid, CO2 and
hydrogen (H2) from products that was produced in acidogenesis. The final stage of anaerobic digestion
is methanogenesis, where methanogenic microorganisms create CH4, CO2 and water from the products
from previous steps [9][83]. In order to perform the anaerobic digestion, a biodigester was investigated in
this research. It is an airtight system in which the organic material is decomposed with naturally occurring
micro-organisms and most of the produced biogas comes from crops and animal manure. However, the
different feedstocks used for production of biogas has a wide range and it could be represented by the
following four categories [82]:
• Crop residues:
Residues from the harvest of different crops; soybean, rice, sugar beet, coffee bean, maize, wheat
oilseeds. Not crops grown for food or feed.
• Animal manure:
From livestock; cattle, pigs, hens, sheep.
• Organic fraction of Municipal Solid Waste (MSW), including industrial waste:
Green waste; paper, wood etc., and food. This includes industry waste, e.g. food-processing industry.
• Wastewater sludge:
Semi-solid organic matter, e.g. sewage gas from wastewater treatment plants.
The production of biogas results in neutral CO2 emissions [84], which is environmentally beneficial since
the same amount of emission will be released into the atmosphere regardless of the biogas production. By
providing energy from biogas the emitted GHG emissions are reduced compared to the amount of emissions
that would be emitted by burning other fuels. The CH4 emissions are also reduced due to the reduction of
the CH4 in animal excrement in the biodigester. Another advantage was that the slurry from the digester
could be used as a fertiliser in agriculture, meaning that the commercial production of fertiliser which had
a high energy consumption, could be reduced. [85]
In the previous report about AETCR Llanogrande [9], there were three types of small-scale biodigester
technology considered; Underground dome (fixed dome), plastic bag (balloon type) and plastic-drum type.
The chosen technology in that report was the plastic bag type, since it had a large capacity, a low investment
24
cost and it was easy to construct [9]. Other parameters that were investigated in the old study were durability
and insulation, where both parameters were rated lower for the plastic bag type than for the other two
types. The lifetime of the technologies, which affects the investment cost over a period of time, was not
investigated in the previous report [9]. Therefore it was determined that a new investigation would be
performed, since the aim of the research was to make the energy system of AETCR Llanogrande more
sustainable and reliable while still minimizing the costs. The fixed dome digester and the balloon digester
were further investigated in the new investigation, while the plastic-drum digester was excluded due to
the low capacity of the design. With future perspectives of a growing population as well as the increased
capacity due to the developing society, the removed alternative was instead replaced by the alternative
of implementing a floating drum digester, which used the same working process but had a more robust
construction than the plastic drum digester [85]. The three types are further evaluated in the coming
sections.
4.3.1 Fixed Dome Digester
The fixed dome digester technology was developed in China and thereafter other similar constructions of
the fixed dome digester has taken form in other countries e.g. India and Tanzania. In Figure 4.6 the fixed
dome digester is shown, and as can be seen the construction is mainly underground, where the pit is lined
with bricks or concrete. The feedstocks enter the digester through an inlet pipe and the slurry in the digester
is discharged through the outlet pipe, where it is gathered in a displacement tank. The biogas is produced
under pressure, however the pressure is not kept constant during the process. This is due to the gas stored
under the dome and the varying in height between the slurry level in the displacement tank and the digester
[86]. The slurry in the displacement tank flows back to the digester when the biogas is collected [85]. This
type of digester is suitable for colder climates since the construction is underground, which generates earth
cover insulation that keeps the temperature inside the digester almost constant [87].
Figure 4.6: Design of a fixed dome digester.
The investment cost for a fixed dome digester between 4 and 13 m3 was in a range of 900 - 1,600 USD and
the preferred substance are animal manure and/or vegetable waste [88]. Further, a list of the advantages and
drawbacks of the fixed dome digester is presented below.
Advantages [88]:
• Long lifetime, around 15 - 20 years.
• High durability.
• Good insulation.
• A small area is needed, since the
technology is placed underground.
Drawbacks [88]:
• Difficult to build in mountainous areas
due to the bedrock.
• High technical skills is required for con-
struction.
25
4.3.2 Floating Drum Digester
As mentioned earlier, the floating drum digester is a more robust construction than the plastic drum digester
that was investigated in the previous report of AETCR Llanogrande [9][85]. As can be seen in Figure 4.7
the major part of the construction is underground. The digester is usually made of bricks, and the floating
drum, which position depends on the gas volume in the digester, is above the ground and made of steel
[86]. However, in newer constructions the floating drum can be made of plastic, this due to a reduction
of the implementation cost [85]. Feedstocks and water are mixed together in the mixing pit and reaches
the digester through the inlet pipe. When new feedstocks are added into the digester, the slurry moves out
through the outlet pipe. The biogas is collected in the drum, which moves up and down along the central
guide pipe. The movement of the drum depends on how much biogas that is stored, and the pressure inside
the drum can be regulated through the weight on the drum. [85]
Figure 4.7: Design of a floating drum digester.
The advantages and the drawbacks of the floating drum digester are listed below. The preferred substance
is the same as for the fixed dome digester, animal excrements and/or vegetable waste [88]. However, the
investment cost is higher, between 1,500 to 1,800 USD for a 16 m3 digester [86].
Advantages [88][86]:
• Long lifetime, around 15 years.
(Drum lifetime only 5 years)
• The pressure can remain constant due to
the weight on the drum.
• Complications in the digester construc-
tion does not lead to bigger issues in
operation and gas yield.
Drawbacks [88]:
• Difficult to build in mountainous areas
due to the bedrock.
• High technical skills is required for
construction.
• Require continuous maintenance to
avoid damages
4.3.3 Balloon Digester
The balloon digester is commonly used i rural areas, since it is easy to implement, relatively cheap and a
well known technology [88]. The balloon digesters are frequently used in countries in South America and
the design can be seen in Figure 4.8. The digester is made of a plastic bag with two pipes at either ends,
one for adding feedstock and one to remove slurry. The biogas is produced, stored and collected through a
pipe at the top of the bag [85]. The pressure in the bag can be increased by adding weight on the bag, but
to avoid damages on the plastic bag it has to be performed carefully. The plastic bag also needs protection
from the solar irradiance and animals. [88]
26
Figure 4.8: Design of a balloon digester.
Compared to the other two designs the preferred substance is only animal excrements and the investment
cost varies between 400 to 800 USD for a digester with a volume between 5 to 20 m3 [86][88]. The
following list presents the advantages and drawbacks of the balloon digester.
Advantages [88]:
• Well known technology in rural areas
and commonly used in Colombia.
• Easy to implement.
Drawbacks [88]:
• Short lifetime (2-5 years).
• Needs large space for installation.
• Require protection to avoid damage.
• Difficult to repair.
4.4 Generator
As was mentioned in Section 3.2, AETCR Llanogrande had a diesel engine driven generator of 177 kVA
that operated during outages, corresponding to around 40 hours per year. The power output from the
generator was estimated to be between 140 to 177 kW depending on the power factor, which was unknown,
but commonly has a range from 0.8 to 1.0 [89]. The average price of diesel per liter (from November 2020
to February 2021) in Colombia was 0.6 USD (2.3 USD per gallon), which was equal to 2,191 Colombian
Peso (COP) [90].
A generator converts mechanical (kinetic) energy, produced from an engine, into electrical energy [91].
It is possible to convert a diesel engine driven generator to operate with biogas, and two methods are
Mechanical Modification and Installation of Ignition. The first mentioned fully operates with biogas and
almost all diesel consumption is removed, while the second option operates with a dual fuel mode, meaning
that it is possible to operate with both liquid and gaseous fuels [92]. Almost all diesel engines can be
converted and operated in a dual fuel mode. The advantage of the dual fuel mode is that the engine can
operate with a gas that has a low heating value [93]. To be able to operate successfully with biogas in a diesel
engine, three parameters had to be adjusted. The first parameter was the spark ignition system. Instead of
the fuel injection nozzle, a spark plug and appropriate guide tube had to be added in the cylinder head [94].
The second parameter was connected to the compression ratio that had to be reduced. It could be achieved
by either creating a recessed bowl in the piston head through milling, reducing the length of the connection
rod or inserting the plate into the piston head [92]. The last parameter was to add a biogas carburetor to
reduce the pollution. This could be performed by inserting an exhaust gas analyzer sampling tube into the
exhaust pipe, which made it possible to adjust the oxygen in the exhaust gas with a gas metering screw. To
avoid thermal stress in the engine it was important to have a cool down period where the amount of biogas
fed into the engine was gradually reduced [94]. Studies showed that engines operating with biogas had a
higher output power then pure diesel engines, and another advantage was the reduction of diesel [95]. Other
benefits of the converted diesel engine was that it operated with a higher efficiency than other gas engines
to a lower investment cost [93].
An estimated cost for the conversion of the engine has not been found. Anyhow, the cost for a biogas
27
generator varies from 4,000 to 20,000 USD with an output power of 50 to 200 kW [96]. This cost
only included the generator, not the transportation costs, installation costs or any taxes for import of the
generator. The average lifetime of a generator was between 10,000 to 30,000 hours, and the time of
replacement depended on how many hours the generator operated per year [97]. For a 55 kW generator
located in a villages in Costa Rica the estimated O&M price was between 0.9 to 1.7 USD/operating hour
[98]. Studies regarding the amount of emissions emitted from a diesel driven generator compared to a
biogas driven generator showed that the emissions were lower from the engine operating on biogas [92].
From 1 l of diesel, around 2.6 kg of CO2 is emitted [99].
4.4.1 Upgrading Biogas
When a diesel generator operates with biogas, one of the most important parts is the composition of the
biogas. The amount of methane should be at least 80%, meaning that the produced biogas from the
biodigester has to be cleaned and upgraded before it can be used in the diesel engine [100]. There are
several methods to clean biogas and remove impurities, such as CO2, in the gas. The most common method
used was scrubbing. The different types of scrubbing were: amine scrubbing, pressure swing adsorption
(PSA), membrane permeation, water scrubbing and organic physical scrubbing [101]. The two types most
suitable for small scale operations were PSA and membrane permeation. The upgrading process of PSA
used active carbon as the adsorber material. Adsorption occurs in two vessels, and when the adsorber
is close to saturation the vessels are switched. The purification of the raw biogas was achieved when the
pressure decreased. The configuration often consisted of four columns, as can be seen in Figure 4.9. During
the process one of the vessels was depressurizing, hence there was a continuous flow of cleaned biogas. The
drawback was that the raw biogas had to be cleaned from hydrogen sulfide (H2S), and dried before entering
the column. To remove H2S an additional pre-clean step might be necessary to implement. [102]
Figure 4.9: PSA upgrading process.
The second upgrading process suitable for small scale operations was membrane permeation. Hollow
polymeric fibers were widely used in upgrading processes, since they often are made from cellulose and
synthetic polymers. The membrane is sensitive to liquids, oils and impurities, and to not harm the membrane
low concentrations of H2S are separated with CO2. High levels of ammonia (NH3) or volatile organic
compounds can also affect the lifespan of the technology and a filter is often used to minimize the impurities.
In Figure 4.10, three steps of the process are shown. If more steps are added to the process a further
reduction of recycled gas and methane gas (CH4) will occur, but the energy intensity will increase. [102]
28
Figure 4.10: Membrane permeation upgrading process.
No prices for the different upgrading processes were found, but the cost for a small scale system is higher per
Nm3/hour than a large scale system. The costs were between 2,430 to 7,291 USD/Nm3/hour for a system
with a capacity of 1,000 Nm3/hour of raw biogas compared to less than 2,430 USD/Nm3/hour for systems
larger than 1,000 Nm3/hour [103]. N in Nm3/hour stands for Normal and means that the measurements
were performed at standard temperature and pressure.
4.5 Battery Energy storage
When dealing with energy systems containing a large amount of renewables, it is important to have some
sort of energy storage that would help to stabilizing the fluctuating energy output, that is a common
phenomenon with renewable energy sources. Batteries would in this case help store the electricity produced
during the day when the supply of solar power is large while the demand is small, in order to utilize it for
example later in the evening when the supply is small, if any, and the demand is usually large. Two of
the most commonly used batteries when it comes to renewable energy systems are Lead-Acid (LA) and
Lithium-Ion (Li-Ion). LA batteries has been on the market for a long time, meaning the technology is
mature and that the price could be kept low. Li-Ion batteries however was a newer technology that was
not as mature and still experiencing high costs. Although the price had decreased substantially over the
last couple of years. Another big difference between the two batteries was the Depth of Discharge (DoD),
which is a percentage measuring how much of the battery potential that could be utilized. The DoD had
been showed to have a significant effect on the lifetime of a battery, where a larger DoD entailed a larger
degradation rate in both capacity and power. The capacity is the measure of how much energy the battery
can hold and the power is the amount of power the battery can provide. These factors will naturally degrade
throughout the life of the battery, but a poorly chosen DoD will accelerate the process. [104][105]
The lifetime emissions of the batteries were also evaluated, where the LA battery had an average of around
28.4 kgCO2-eq/kWh of capacity [106][107][108] and the Li-Ion battery was usually somewhere between
61-106 kgCO2-eq/kWh of capacity [109]. A mean value of 83.5 kgCO2-eq/kWh was estimated for the
Li-Ion battery. Some important characteristics of the batteries can be seen in Table 4.3 below.
29
Table 4.3: Characteristics of LA and Li-Ion
batteries. [110][111][112][113][105]
Lead-Acid Li-Ion
Capacity [kWh] 1 1
Capital Cost [USD/kWh] 295 600
Replacement Cost [USD/kWh] 130 440
O&M Cost [USD/kW] 11 10
Lifetime [years] 3 10
DoD [%] 40 60
Emissions [kgCO2-eq/kWh] 28.4 83.5
As can be seen in the table, the costs of a Li-Ion battery were much higher than the ones for a LA battery.
Although this does not necessarily mean that LA was a less expensive option. Due to the short lifetime and
the much smaller DoD they would entail that the replacement cost instead increases over the lifetime of the
system, as well as more batteries being needed in order to cover the same demand. As the technology is
developed, some newer Li-Ion batteries can even handle a DoD of 80%, in rare cases even 100%, which
even further raises the cost effectiveness of the battery. However, the batteries able to handle larger DoD’s
usually also comes with a larger cost as well.
The LA batteries generally need more maintenance than the Li-Ion ones. This was due to most versions
of them being filled with a fluid, where the water slowly evaporates as the battery temperature increases
as it charges. The water then needs to be refilled before it reaches a level that is too low and could cause
damage on the plates [105]. Refilling of the batteries is however maintenance that can be done by someone
on-site since the only thing to consider is to fill up the right amount, meaning the maintenance cost could
still be kept low. The phenomenon of the battery both experiencing temperature increases as well as the
gas release when it charges comes with a demand of it being placed somewhere with ventilation, where the
gas can cause no harm and the risks for overheating are minimized. Li-Ion batteries however are essentially
maintenance free and basically just require a look-over every now and then, in order to ensure there is no
damage on the battery nor the cables and such around it [112]. Furthermore, the remoteness of the AETCR
and the increasing costs of the logistics that comes with that, is another reason why a less frequent need of
replacing the equipment most probably is a better choice with less expenditures in the long haul. Although,
both batteries are considered viable choices in further investigations.
30
5 Approach
In this chapter the approach on how the estimations, simulations and calculations for the electricity and
biogas systems were performed are presented. The baseline for the HOMER model is explained in detail,
the recommended type of biodigester along with calculations for the amount of biomass as well as the
equations used for estimating the biogas production and LPG demand are also presented. Furthermore,
the equations used for evaluating the systems’ economical and environmental impact both separately and
combined are presented, along with the approach on evaluating the social impact of the combined energy
system.
5.1 Estimated Load Curve
There was no available information regarding the distribution of the demand throughout an average day in
the AETCR and an estimated load curve was created. The average of purchased electricity on a monthly
basis was however known, and the daily consumption was found to be 380 kWh. The estimated curve was
then based on the shape of the load curves of two remote microgrid villages, one in the North [114] and
one in the centre of Colombia [115]. Neither of the locations fully matched all prerequisites of the AETCR,
and a combination of the two was thereof considered. The load curves of the villages were converted
into percentages symbolising the hourly size of the load, where for example the peak load of 4 kW would
represent 100% entailing that an hourly load of 2 kW would be 50%. The two curves were combined by
finding an hourly average of the percentages, which was then weighted against the new value of the peak
load. The hourly demand of AETCR Llanogrande was then estimated by converting the percentages into
kW, where the sum of the hourly kW load throughout the day would equal the 380 kWh daily demand.
The resulting load curve is presented in Figure 5.1 below. More detailed calculations can be seen in the
MATLAB file called Demand_Curve_Calc and a table with the results can be seen in Appendix A.3.
Figure 5.1: The estimated daily demand curve of
AETCR Llanogrande.
5.1.1 Estimated Load Curves for IED and PGE
For the two scenarios looking at the possibility of both an increased electricity demand and a population
growth, new load curves had to be created. They were created in the same way as the base load curve, but
based on a larger daily average. For the IED demand curves, the daily average was simply increased by
10%, 20%, 30% and 50%, whereas the new curves could be found. For the PGE scenario on the other hand,
the average daily demand per person was found. The number of people in the village was then increased
by 5%, 10% and 15%, where the number was always rounded up to the closest integer. The new number of
people was then multiplied with the average daily demand per person and the new total daily demand was
31
found. The new load curves were then estimated by the same principles as the base, and IED ones, where
more precise calculations and results can be seen in the attached MATLAB file Demand_Curve_Calc and
the table in Appendix A.3.
5.2 Baseline HOMER Model
First the prerequisites of the location in terms of weather data, coordinates and the load curve were added
into the HOMER program. After the basic settings of the location, the already existing technologies were
added, namely the existing PV panels, the generator and the grid. The already installed PV panels were as
mentioned in Section 3.3.1 manufactured by Jinko Solar, model JKM270PP-60. The size of one panel was
992 x 1,650 mm with a capacity of 270 W [44]. Depending on the power factor, the generator could have
a power output in the range of 141.6 - 177 kW and due to lack of information regarding the generator’s
performance and condition, a capacity of 140 kW was assumed and considered in the model. To evaluate
options where the generator would be decommissioned, the option of having 0 kW of installed capacity
was added as well. The information added concerning the grid was both a buy and sell price, as well as
characteristics regarding the stability. The characteristics were all based on information provided by Mr.
Fernández, along with assumptions regarding the variability of the repair time. The capital costs for the
already installed technologies were set to zero, whereas the replacement and O&M costs were added in the
simulations. The replacement cost for the solar panels were however neglected, since it was assumed that
they would not be replaced in case of something unexpected happening and the panels would break or be
damaged. This due to the possibility of them not being connected to the other implemented panels, and it
being a rather small installed capacity. Furthermore, the existing batteries were neglected in the HOMER
model. This due to lack of information regarding their capacity, type and remaining lifespan. Most likely
the batteries were of a LA type, since that has been one of the most common types of batteries in connection
to PV systems and they were installed a few years back. Thereof, they would most probably not be in good
shape at the time of the potential implementation, due to their short average lifetime. It was hence assumed
the batteries could be excluded from the simulations. The specifications of the technologies can be seen in
Table 5.1. All the specifics concerning the generator and inverter were not known, and a HOMER program
was set up in order to estimate the unknown characteristics. A more specific estimation of the usage of the
generator was found through entering the attained information regarding the grid outages. The installed
capacity of the inverter was also estimated.
Table 5.1: Characteristics of the existing technologies. [8][44]
PV Panels Generator Grid
Installed Capacity [kW] 1.65 140 Buying price [USD/kWh] 0.1130
Efficiency [%] / Power Factor [-] 16.8 0.8 Selling price [USD/kWh] 0.0565
Capital Cost [USD/kW] - - Mean Outage Frequency [1/year] 8
Replacement Cost [USD/kW] - 800 Mean Repair Time [hour] 6
O&M Cost [USD/year] / [USD/op.hour] 107 1.32 Repair Time Variability [%] 200
Lifetime [years] / [hour] 20 15,000 Emissions [kgCO2-eq/kWh] 0.11
Fuel Price [USD/l] - 0.6
Emissions [kgCO2-eq/kWh] / [kgCO2-eq/l] 20·10−3 2.69
The next step of the HOMER model was to integrate the other technologies considered for implementation.
As presented in Section 4.1, both a poly- and monocrystalline PV panel would be evaluated. The polycrystal-
line panel was for simplistic reasons chosen to be of the same type as the ones already installed on site. The
characteristics were common for the available models, the brand was available on the market in Colombia
and according to Mr. Fernández they were functioning well. As for the monocrystalline panel, it was for
the same reasons chosen to be of the same brand. Namely the Jinko Solar Eagle PERC60, with the same
size of 992 x 1,650 mm and a capacity of 300 W [116]. The inverter was designed in HOMER as 1 kW
units, whereas if implemented in the AETCR it would in fact be one or a few units with a larger capacity.
The inverter was chosen to be a SolaX X3-hybrid10. It was chosen due to it being a hybrid string inverter,
32
the temperature interval and maximum height above sea level suits the location, it had an efficiency within
the interval of the average, and the ability to utilize the batteries as a power source even during black outs
[117]. The capital and replacement costs of the inverter were assumed to be the mean of the presented costs
in Section 4.1.4. The DoD of the batteries were added in HOMER as the state of charge, or SoC, which
represents the opposite of the percentage. For example, a 60% DoD equals a 40% SoC. The specifics added
in HOMER can be seen in Table 5.2. In the table, poly represents the polycrystalline panel and mono the
monocrystalline panel.
Table 5.2: Technology specifications for new implementations in the HOMER model. [44][116]
Poly Mono Inverter LA Li-Ion
Capacity per Unit [W] 270 300 1,000 Capacity per Unit [kWh] 1 1
Efficiency [%] 16.8 18.33 97 DoD [%] 40 60
Investment Cost [USD/kW] 3,555 3,585 225 Investment Cost [USD/kWh] 295 600
Replacement Cost [USD/kW] 430 460 225 Replacement Cost [USD/kWh] 130 440
O&M Cost [USD/kW/year] 107 108 50 O&M Cost [USD/kWh/year] 11 10
Lifetime [year] 25 25 10 Lifetime [year] 3 10
Emissions [kgCO2-eq/kWh] 25·10−3 20·10−3 - Emissions [kgCO2-eq/kWh] 28.4 83.5
Area per Unit [m3] 1.64 1.66 -
The system was simulated with a load following strategy (LF). The LF strategy lets the generator produce
just enough energy to cover the demand when needed and does not interact with the batteries concerning
charging. Once the basic HOMER model was created, it could easily be changed in order to fulfill the
specific requirements of the various scenarios. This included changes in the load, available technologies
and some variances in their specifics. The total area of the new panels was also calculated for all the
presented systems, excluding the area of the already existing panels. The area was calculated as Equation
5.1 below, similarly for both the poly- and monocrystalline panels.
PV Area =Width ·Height · Installed Capacity · 1000
Panel Capacity(5.1)
Where the Installed Capacity is the total capacity of the new panels measured in kW, and the Panel Capacity
is the maximum power of the specific type of panel measured in W. Namely 270 W for the polycrystalline
panel and 300 W for the monocrystalline panel.
5.3 Biomass
Within this subsection, a motivation regarding the recommended choice of biodigester along with how to
calculate the amount of produced biogas are presented.
5.3.1 Recommended Choice of Biodigester
It was possible to implement each one of the three evaluated biodigester alternatives in AETCR Llanogrande,
but the design to recommend for implementation was the fixed dome digester. The recommendation was
mainly based on the sustainability of the digester, and a fixed dome digester was more reliable in terms of
durability. Durability is specifically important in remote places where maintenance is not always available.
Less land area was required since the equipment was placed underground, which also has a positive impact
on the insulation capability due to the temperature stability that occurs. The lifetime of the fixed dome
biodigester was longer than the other two alternatives (20 years), which results in a lower investment cost
during a period of time compared to the balloon digester with its lifetime of 5 years. The two drawbacks
mentioned was connected to the construction of the digester, i.e. difficult to build and requires high technical
skills. The first mentioned was hard to avoid and regarding this issue a balloon digester was a better
alternative. The second drawback concerning the technical skills was more like an advantage since the
33
purpose was to educate and create job opportunities within the biogas production.
The reason why the floating drum digester was not recommended was due to the high investment cost.
The drum has to be replaced every five years and it requires continuous maintenance to avoid any damages.
The most commonly built digester in Colombia, the balloon digester, has a short lifetime resulting in a
higher investment cost due to the frequent replacement of components. It also requires more space and
protection from animals, which was not optimal for the AETCR since there was not that much land area
available and livestock moves around freely. Therefore, it was not considered a good option, and it was not
further investigated in this project.
5.3.2 Biogas Calculations
Calculations of the biogas production requires data regarding the amount of livestock manure from different
animals, volatile solids (VS) ratios, and proportions of waste based of type and densities. The total amount
of biomass and the total amount of VS in the biomass had to be known in order to calculate the extracted
biogas. The remaining part of the biomass when water content and inorganic matter have been removed is
VS [118]. In Table 5.3 below the amount of manure, proportions of waste per type and the different VS
ratios are presented. As can be seen in the table the waste is divided into three categories; fruit, vegetable
and other waste. This is due to the different VS ratios in the waste. The yearly food waste in Latin America
was measured to 223 kg/person [119] and was used to estimate the food waste from the unsorted waste of
AETCR Llanogrande.
Table 5.3: Data regarding manure, proportions of waste and different VS ratios. [120][121][122]
Livestock Manure VS ratio Waste Proportions of waste VS ratio
[kg/day/animal] [%] [%] [%]
Bovines 32.2 10.8 Fruit 16.4 10.3
Hens 0.07 17.9 Vegetable 25.8 4.7
Broiler chickens 0.09 20.0 Other waste 57.8 89.0
Pigs 4.9 8.8
The total amount of manure [kg/day] was calculated with Equation 5.2, where n is the different types of
livestock. The Number of livestock was varied in some of the scenarios, which was also the case for the
Total food waste [kg/day] in Equation 5.3, where the total amount of waste [kg/day] for each category
was calculated based on the collected unsorted waste. In the last mentioned equation, m is the different
types of food waste. A safety factor, SF , of 20% was assumed and added into the calculations to ensure
that the amount of available biomass was not over estimated but also that it was possible to collect that
amount of biomass. The Manure from each livestock as well as the Proportions of waste was kept constant
for all scenarios
Total manure = SF ·
∑
(Number of livestock ·Manure)n (5.2)
Total waste = SF ·
∑
(Proportions of waste · Total food waste)m (5.3)
The total amount of biomass [m3/day] was calculated with Equation 5.4. By removing the density in the
equation the total biomass in kg per day could be calculated as well. The optimum ratio between biomass
and water was 3:1 [123] and Equation 5.5 was used to calculate the total amount of water [kg/day] needed
to be inserted into the digester.
Total biomass =Total manure
Density manure+
Total waste
Density waste+
Total water
Density water(5.4)
34
Total Water =Total manure + Total waste
3(5.5)
The densities used in the calculation can be viewed in Table 5.4 and was applied due to the unit conversion.
Table 5.4: Density for biogas calculations.
[124][125][126][127]
Density [kg/m3]
Manure 1,030
Waste 300
Water 1,000
Biogas 1.15
The total amount of VS [kg/day] was calculated with Equation 5.6 and was based on the total VS from
manure and food waste. The sum of VS manure and VS waste was calculated in the same way as for the
sum of the Total manure and Total waste but with the VS ratios instead of the Manure and Total food waste.
The SF was however not included since it was already applied for the total manure and total waste. The VS
ratio is displayed in Table 5.3 above.
Total V S =∑
(V S manure)n +∑
(V S waste)m (5.6)
When the total amount of VS as well as the total amount of biomass was known, the initial concentration
of VS in the slurry [kg/m3] was estimated with Equation 5.7.
V S in slurry =Total V S
Total biomass(5.7)
The fixed dome digester was the recommended design to implement. The volume of the digester [m3]
depends on the diameter, and in this research several diameters has been examined to find the most suitable
volume for biogas production in AETCR Llanogrande. The diameters under evaluations was in a range
from 2 to 5 m with steps of 0.2 m and has been tried for two different designs of the fixed dome digester.
The two different designs were the hemisphere and the chinese design. The hemisphere design consisted
of a hemisphere with a flat bottom, while the chinese design was more complex with a hemisphere on the
top of a cylinder with a curved or flat bottom. The layout for both designs can vary due to the hand made
construction process and in Figure 5.2 a draft of how the two designs can be built is displayed. The figure
shows the cross sectional view from the side for each of the two designs. [128]
Figure 5.2: The diameter for the two fixed dome digester designs. [128]
35
The volume of the whole plant (Vp) for the two designs was calculated with Equation 5.8 and 5.9, which
was retrieved from Measuring small-scale biogas capacity and production written by IRENA [128]. For the
hemisphere design the necessary measure was the diameter, D, whereas for the chinese design a standard
plant design was developed due to several types of constructions layouts. According to IRENA the equation
for the chinese design was developed by the Biogas Training Centre in Sichuan, China. However, if the
chinese design has a flat bottom, a height (L) should also be included to calculate the plant volume, and
then the equation looks like Equation 5.10. Furthermore, the gas storage volume (Vg) is 35% of Vp, while
the digester volume Vd is the remaining 65% for both designs. [128]
Vp, hemisphere =2
3· π ·
(
D
2
)3
(5.8)
Vp, chinese =D3
2.2368(5.9)
Vp, chinese−flat bottom = π ·
(
D
2
)2
· L (5.10)
The last factor needed to be known for calculations of the amount of produced biogas was the yield factor,
which was the ratio indicating how much biogas that could be produced from the biomass. The yield factor
correlates with the retention time and the average temperature at the location. The retention time [days]
is calculated with Equation 5.11 and should be between 30 and 50 days to optimize the biogas production
[129]. As mentioned earlier in the report, the average temperature in the area of AETCR Llanogrande was
19.45 °C. A suitable digester temperature should be 20 to 35 °C [130], which indicated that a heater might
be needed in order for the system to reach the optimal temperature. This could be performed by using a heat
exchanger or the thermal energy from solar power [131][132]. The values of the yield factor was retrieved
from the earlier mentioned small scale biogas report from IRENA [128] and can be found in Appendix A.4.
Retention time =Vd
Total Biomass(5.11)
By using Equation 5.12 the amount of biogas [m3/day] that could be extracted from the collected biomass
was determined. This equation was also retrieved from the report by IRENA [128].
Amount of Biogas =Y ield factor · Vd · V S in slurry
1000(5.12)
The purpose of a biodigester implementation was to have the opportunity to remove or reduce the use of
LPG in the AETCR. Through Equation 5.13 it was possible to evaluate which biodigester would be the most
suitable to fulfill the demand. This was done by calculating the difference between the produced amount of
biogas and the current cooking energy demand.
Difference = Amount of Biogas − Current cooking demand (5.13)
The Current cooking demand measured in kg LPG per month was converted into m3 of biogas per month for
the comparison with the originally produced biogas amount. 1 kg of LPG was estimated to be approximately
2.1 m3 of biogas [133], meaning that one gas bottle corresponded to 38 m3. If the amount of produced
biogas was more than the required demand for cooking, the remaining biogas would be converted to
electricity. In an electrically powered generator, 1 m3 of biogas is converted to 2 kWh electricity [134].
36
5.3.2.1 Increased Access to Biomass
For the IAB sub-scenarios the access to biomass was increased, and the new amount of biomass [kg/day]
was calculated with Equation 5.14, where the current available biomass was multiplied with the increased
percentage of biomass.
New amount of Biomass = Total biomass · Percentage increase (5.14)
Equation 5.15 was used to determine the percentage of VS in the biomass and that percentage was used to
calculate the new amount of total VS with Equation 5.16.
Percentage V S in Biomass =Total V S
Total biomass(5.15)
New amount of V S = Percentage V S in Biomass · Total biomass (5.16)
Since the increase of biomass was directly connected to the manure from the livestock, the new numbers of
livestock needed to produce the certain amount of manure could be calculated. By calculating the increased
amount of available manure [kg/day] and removing the safety factor (SF) of 20%, the total produced manure
from the livestock could be determined. Thereafter the increased numbers of livestock could be calculated
by using Equation 5.17.
New numbers of livestock =Total manure
Manure(5.17)
5.3.2.2 Population Growth - Biomass
For the PGB sub-scenario the number of persons living in the AETCR was increased. Through Equation
5.18 the new number of inhabitants was calculated and the value was rounded up to closest integer.
New number of Inhabitants = Current Inhabitants · Percentage increase (5.18)
As the population grew, the amount of food waste increased. The total food waste [kg/day] was then
calculated by multiplying the numbers of inhabitants with the estimated food waste per person. The cooking
demand increased as well due to more inhabitants in the AETCR. The currently used LPG was multiplied
by the increased percentage in order to calculate the new cooking demand. The new demand resulted in
a new number of gas bottles which was determined with Equation 5.19 where New amount of LPG in kg
was divided with the weight of the gas in one gas bottle. The number of gas bottles was rounded up to the
closest integer.
Number of gas bottles =New amount of LPG
One gas bottle(5.19)
When the number of LPG bottles was estimated the amount of LPG based on how many gas bottles that
must be purchased was determined. The new cooking demand [m3/month] was calculated with Equation
5.20 where the same convertion factor as earlier was used, namely 2.1 m3 of biogas per 1 kg LPG.
New cooking demand = Number of gas bottles · 2.1 (5.20)
For the PGB sub-scenario, the increase of biogas was only connected to the increased waste since the
amount of manure was kept constant.
37
5.4 Economical Impact
The NPC of the electricity system was presented in HOMER for each of the simulated systems. It was
calculated by summarizing the yearly total discounted cash flows over the lifetime of the project. The cash
flows includes the capital costs, replacement costs, O&M costs, the cost of buying electricity from the grid,
and fuel costs. It also includes revenues considering the electricity sold to the grid and the salvage value.
The summarized capital costs for the various technologies at the beginning of the project is what is called
Initial Capital further on in the report [135]. The NPC for the electrical system will further on be referred
to as NPCelectricity.
For the biogas system, the yearly cost [USD] for the potential implementation was calculated with Equation
5.21. The costs included in the biogas system were the investment, INVdig, and the O&M cost of the
biodigester, O&Mdig, the upgrading, UPGgen, and O&M cost for the generator, O&Mgen, as well as the
converter cost for the conversion between biogas and electricity, Convbio to el, if applicable.
Costbiogas yearly = INVdig +O&Mdig + UPGgen +O&Mgen + Convbio to el (5.21)
Another factor of the economical part for the biogas system was the reduction of costs along with the
reduction of LPG. The reduction was connected to the amount of gas bottles needed to cover any remaining
cooking demand and with Equation 5.22 the new cost for the needed gas bottles could be found.
LPG Costnew = Number of gas bottlesnew ·Bottle cost (5.22)
With Equation 5.23 the cash flows [USD/year] connected to the biogas implementations were calculated.
The NPC of the biogas system was subtracted with the income or savings from the produced biogas to
determine how much money that could be saved by replacing the LPG with biogas.
Cash flowbiogas yearly = Costbiogas yearly − LPG costnew (5.23)
Furthermore, the NPC for the biogas, NPCbiogas, could be calculated as the total costs of the biogas system
and LPG usage, where the costs for each of the years were summed up over the lifetime, k, of the project.
It was calculated with Equation 5.24 as can be seen below.
NPCbiogas =∑
(Costbiogas yearly + LPG costnew)k (5.24)
5.5 Environmental Impact
When assessing the first KPI for the environmental impact, the parameter of evaluation was the RF of the
system. For the electrical system, there were renewable fraction results that were presented in HOMER.
However, they only considered the fraction of renewables in the installed system, and not the fraction in the
electricity mix. Hence, adjustments were made once the simulations were done. The new total renewable
fraction was calculated as displayed in Equation 5.25, where RFsys is the presented RF in HOMER, RFelmix
is the known RF in the electricity mix of the grid and the electricity demand is the total yearly average. Some
overproduction could be part of the simulations, however only the demand and the amount sold to the grid
was included in the utilized electricity.
Total RF = RFsys +RFelmix ·Electricity Purchased from Grid
Electricity Demand+ Sold Electricity to Grid(5.25)
38
In order to evaluate the secondary environmental KPI concerning the CO2 emissions throughout the usable
lifetime of the energy system, the total amount of emissions was calculated for each of the simulated
systems. The emissions were estimated separately for the electrical and biomass parts and then summarized
for the entire energy system.
As for the electricity system, each of the considered technologies were evaluated separately, both the
existing and potential installments, and then summarized for all of the equipment. The calculations could be
explained through Equations 5.26 - 5.30 presented below. The emissions from the two types of PV panels
were both calculated through Equation 5.26, where the data for each of them was estimated individually.
The EmPV [kgCO2-eq/kWh] is the estimated CO2-eq per produced kWh throughout the panels lifetime,
the ProdPV [kWh] is the yearly average production and LifetimePV [years] is the expected lifetime of the
panel.
EmissionsPV = EmPV · ProdPV · LifetimePV (5.26)
The emissions from the generator was calculated by looking at the average emissions for 1 l of diesel,
Emgen [kgCO2-eq/l], the amount of spent fuel per year, Fuelgen [l/year], and the lifetime of the generator,
Lifetimegen [years].
Emissionsgenerator = Emgen · Fuelgen · Lifetimegen (5.27)
The emissions related to the grid were estimated through the emissions per kWh, Emgrid [kgCO2/kWh],
the amount of bought electricity from the grid, Prodgrid [kWh], and the entire lifetime of the project,
Lifetimegrid [years].
Emissionsgrid = Emgrid · Prodgrid · Lifetimegrid (5.28)
The battery emissions however were not estimated based on the throughput, but as a lump sum based on
the capacity of the batteries, Embatt [kgCO2/kWh]. To find the total amount it was then multiplied with
the total installed capacity, Capbatt [kWh], and the number of times the batteries would have to be replaced
throughout the project lifetime, Replacementsbatt [-]. In this case the replacements throughout the lifetime
of the project were estimated to 9 times for the LA batteries and 3 times for the Li-Ion batteries.
Emissionsbattery = Embatt · Capbatt ·Replacementsbatt (5.29)
The total amount of CO2-eq emissions for the entire electricity system was then estimated by calculating
the sum for all of the equipment present in each proposed system, seen in Equation 5.30 below. The i in the
equation symbolizes the different technologies.
Emissionstotal =∑
( Emissions )i (5.30)
As was mentioned in Section 4.3 the biogas production is CO2 neutral and do not provide any GHG
emissions. Therefore the environmental impact of the biogas system was set to zero. However, the LPG
used for cooking emits CO2 and the amount of emissions due to LPG per month was calculated with
Equation 5.31. As stated in Section 3.2, 1 liter (or 0.55 kg) LPG emits 1.7 kg CO2, and one gas bottle
contains 18 kg LPG.
CO2 emissionscurrent/new = Numbers of gas bottlescurrent/new ·18
0.55· 1.7 (5.31)
39
By replacing LPG with biogas a reduction of CO2 occurs due to the smaller number of LPG gas bottles
needed to cover the cooking demand, and the difference between the current and new systems emitted CO2
was calculated with Equation 5.32.
CO2 reduction = CO2 emissionscurrent − CO2 emissionsnew (5.32)
5.6 Social Impact
The evaluation of the social impact due to an implementation of a renewable energy system would be
based on the results from the economic and the environmental aspects of this project. The social impact
was therefore only discussed for several important matters, where some was directly connected to the
inhabitants of the AETCR Llanogrande.
How the upgraded energy system could potentially affect the everyday life for the inhabitants, the knowledge
about sustainability and the opportunities for jobs and education would be discussed. Another factor
that would be discussed in terms of the social impact was the question of who was going to pay for the
implementation of the new equipment.
5.7 Combined Energy System
For this project a recommended combined energy system would be chosen in order to be a guideline for a
feasible implementation of a new energy system in Llanogrande. As for the biogas system the recommended
system would be chosen based on the largest amount of produced biogas where the diameter had a retention
time within the optimal range of 30 to 50 days. The recommended electrical system would be chosen based
on the NPC where the total NPC would remain almost the same as for the current energy system. A
simulated electrical system would be chosen with a cost that corresponds to the remaining cost when the
cost of the potential biodigester is removed from the NPC for the current system.
When evaluating the entire system, combining the potential electrical and biogas implementations, a new
NPC as well as the total amount of emitted CO2 emissions was calculated by summing up the one estimated
for the electrical system with the one calculated for the biogas system. With Equation 5.33 and Equation
5.34 was the NPC and CO2 emissions calculated for the lifetime of the project which was 25 years.
NPC system lifetime = NPCelectricity +NPCbiogas (5.33)
CO2 emissionssystem lifetime = CO2 emissionselectricity + CO2 emissionsbiogas (5.34)
40
6 Results
In this section, results for all scenarios are presented. This includes results where the electricity and biogas
systems are presented separately as different systems, and then in a combined system. For the electrical
system the results were simulated in HOMER Pro and further analysed in order to evaluate the systems.
The results presented in figures for the electricity system that includes the RF of the system, are based on
the total RF (including the grid) and not the RF of the electricity system. The amount of PV panels in the
base system that is presented in Business As Usual is included in all systems, the generator is included if
not mentioned otherwise. Although, the already installed PV panels are not included in the tables where
any chosen electricity or combined systems are presented, in those tables only the new installments of PV
and inverters are shown. This excludes of course the presented data for the BAU system, which displays the
existing system. For the results of the electrical system, not all systems are included in the figures. Systems
that are not feasible for the location, such as huge amounts of installed PV has been cut out for the purpose
of more understandable figures. The excluded systems can however be seen in the Excel file Collected
data from HOMER along with the collection of data for all simulated systems. As for the biogas system
the results were calculated through MATLAB and the code can be seen in the attached MATLAB files
Biogas_Matlab_code. All the mentioned calculated results as well as outputs from HOMER Pro regarding
the electricity systems are presented as yearly values, except for the NPC and the total emissions. In the
figures for the biogas system, the values of produced biogas and the emitted CO2 emissions displayed are
monthly values, while all the displayed costs are yearly values, except for the NPC which displays the
costs throughout the lifetime of the project. In the combined energy system tables however, all the values
connected to the biogas system is displayed for the lifetime of the project.
6.1 Base Scenario
Within the Base Scenario three sub-scenarios were included; Business As Usual (BAU), Modest Implemen-
tation of Technologies (MIT) and Off-Grid. The BAU scenario was a fixed system based on the knowledge
about the AETCR, whereas the MIT and Off-Grid systems were chosen based on the desired outcome out
of many proposed systems from both HOMER Pro and the calculated biogas estimations. For the electricity
systems simulated in HOMER Pro, the results were what laid a foundation for both the MIT and Off-Grid
scenario. In all sub-scenarios of this section, the total yearly demand was 138,700 kWh. The biogas system
was implemented in MIT, where all available biomass was used for biogas production. For the MIT and
Off-Grid sub-scenarios both an economical and environmentally prioritizing system are presented.
6.1.1 Business As Usual
The first system to be presented is the one called Business As Usual, or BAU. As mentioned in Section
3.4 this reflected on the current situation in the AETCR and was the starting point of the evaluation. The
existing system consisted of the PV panels (onwards referred to as PV Old in tables and graphs), a generator,
an inverter, the grid and a LPG demand. From the baseline setup in HOMER Pro that is explained in Section
5.2, a BAU scenario was created based on the knowledge about the AETCR. This was done partly in order
to find the RF of the electricity system, the NPC, the information related to production of both the PV
panels and the generator, as well as an estimated inverter size. It also estimates the power outages in length
and frequency based on the attained information. Partly also as mentioned in Section 5.2 to lay a base for
the sub-scenario simulations. The BAU system does not only include the electrical system, but also the gas
used for cooking, which corresponded to 56% of the total NPC. The NPC and emissions for the usage of
LPG throughout the lifetime of the project were also included. The total NPC in this case is the cost of
meeting the energy demand of the AETCR throughout the lifetime of the project as the system looks today,
including both O&M costs, purchased electricity from the grid and bought fuel. The specifics of the BAU
system can be seen in Table 6.1.
41
In the table below and throughout the tables in the result section of this report, many abbreviations can
be seen. In order to facilitate the understanding of the results some of the abbreviations are presented here
and they will be continuously presented throughout the section. Prod. means production, Gen. means
generator, Op. means operation, Tot. means total, El. means electricity and refers to the electricity system
except when mentioned in combination with the demand, Dem. means demand, Sys. means system, and
last but not least, Purch. means purchased.
Table 6.1: System set up and important parameters, BAU.
PV Old [kW] Old PV prod. [kWh] Inverter [kW] Generator [kW] Gen. prod. [kWh]
1.65 2,000 0.8 140 1,200
Gen. op. [hours] Gen. op. cost [USD/year] Gen. O&M [USD] Gen. fuel [l] Fuel cost [USD]
34 19,600 6,300 435 260
Tot. prod. [kWh] Peak el. dem. [kW] Sys. RF [%] Tot. RF [%] Grid purch. [kWh]
3,200 23.7 0.9 76.5 126,200
LPG purch. [kUSD] Gas Bottles [no./month] NPC old el. [kUSD] Tot. NPC [kUSD]
405 33 312 717
Emissions LPG [tonnes CO2] Emissions el. [tonnes CO2-eq] Emissions tot. [tonnes CO2-eq]
555.1 404.6 959.7
6.1.2 Modest Implementation of Technologies
The sub-scenario called Modest Implementation of Technologies (MIT) is divided into three sections;
Electricity System, Biogas System and Combined Energy System. For the two first mentioned sections the
results of the simulations and calculations are presented and analysed, whereas the third section presents
the recommended combined system for implementation. For the electrical and combined energy system
sections both an economically and environmentally prioritizing system are presented as well.
6.1.2.1 Electricity System
The simulated systems proposed by HOMER Pro based on the current situation in AETCR Llanogrande
are presented in this section. The figures presents the results for all the simulated systems which are
marked in blue and referred to as Standard Case in the legend, whereas the chosen MIT systems are
marked by a yellow and green dot and labeled MIT, economical and MIT, environmental for economical
and environmentally prioritizing systems. The motivation regarding the choice of the chosen system is
found at the end of this section, whereas the highlighted dots are already added in the figures for reference.
Most of the dots shown in the figures are actually several dots, or systems, that are close to each other in
output specifics but differ in the types of technologies used. A categorization of the patterns seen in the
figures and which components that are included in them will be presented. Due to the clustered systems
that could be observed in for example Figure 6.1, a zoomed in version is presented for clarification and
separation of the different chosen systems and can be seen in Figure 6.2. This was done in order to properly
motivate the choice of the systems.
The two figures below, Figure 6.1 and Figure 6.2, presents the results for the MIT simulations in terms
of the total RF and the NPC. Systems placed at the far right of the figure entails high self-sufficiency, or
off-grid systems when placed around 99-100% RF, with the NPC growing along with the independence.
Looking at the results seen in Figure 6.1 however, the lower trendline that starts in the bottom left corner
and slowly rises while dividing into two, are systems with either poly- or monocrystalline panels, with
a generator and none to only a few kWh of installed battery capacity. As it is seen dividing, the lower
trendline instead represents a larger implementation of Li-Ion batteries with the generator. The upper part
is a continuation on the implementation of PV panels with the generator and none or a few batteries. The
trendline located above the ones mentioned on the other hand, that starts around 82% RF and 800 kUSD in
NPC represents systems without the generator and a large installed capacity of Lead-Acid (LA) batteries.
42
These systems are represented on that trendline until around 93% RF. The next coming cluster looking
like it would belong to the trendline at around 95% RF is instead showing systems with a large amount of
installed PV, including the generator, but with no to a very small amount of batteries. The cluster above it
however, is yet again back to the large amount of PV, no generator and a large LA battery capacity. The two
upper clusters both have in common that a lot of electricity is sold to the grid, most probably due to the large
amount of PV panels. The cluster seen between the trendlines at 93% RF consists of systems with large
amounts of PV, the generator and no batteries. The two dots located slightly above the bottom trendline at
94% represents systems with larger amounts of PV, no generator and Li-Ion batteries. The top left dot is a
system without any new installments of PV, no generator and a very large amount of LA batteries. Almost
all electricity is bought from the grid and stored in the batteries when necessary. The throughput of the
batteries was however very small, indicating that the batteries were only charged to be used during power
outages.The systems displayed at 100% RF does not include the generator, is off-grid and includes a large
amount of batteries. The upper dots are with LA batteries, while the lower are with Li-Ion batteries. The
two dots slightly to the left of the 100% ones, are systems that are also off-grid but including the generator.
The battery amount is slightly lower, but still large, and the LA is yet again the upper dot and the Li-Ion the
lower.
Figure 6.1: Total renewable fraction vs NPC for all
simulations, MIT.Figure 6.2: Total renewable fraction vs NPC, zoomed
in on the recommended cases, MIT.
In the second figure, Figure 6.2, all of the shown systems includes the generator and a smaller amount of
installed PV of around 4.5 - 5.5 kW. The lower points, including the chosen ones, includes no batteries.
The two points in the middle includes 1 kWh of LA battery capacity, and the top ones include 2 kWh
of Li-Ion battery capacity. The dots to the left includes polycrystalline panels, and the dots on the right
monocrystalline.
In Figure 6.3 however, the RF and how the lifetime emissions varies with it is presented. The trendline
starting at the far left represents the systems with a generator and little to no batteries. As it divides
around 85% RF, systems with a larger amount of Li-Ion batteries and the generator is part of the trendline
continuing downwards, whereas the systems with few or no batteries continues upwards. When the lower
trendline reaches around 93% RF the systems are mixed between Li-Ion systems with and without the
generator. The most upper trendline starting around 82% is represented by systems with a large amount
of LA batteries and no generator, that merges with the systems with the generator and little to no batteries
around 95% RF. At the far left there are two clusters of four dots each, where the upper one is represented by
off-grid LA systems, with the generator to the left and without it to the right. The lower one is represented
by off-grid Li-Ion systems, where the left ones are with the generator and the right ones are without it.
43
Figure 6.3: Renewable fraction vs emissions, MIT. Figure 6.4: NPC vs emissions, MIT.
It was also of interest to look at the relation between the economical and environmental impacts of the
systems, namely the NPC plotted against the emissions of the systems. This is displayed in Figure 6.4
above. Seen in the figure is for starters the trendline starting at the far left part, which consists of systems
with a generator and no or a few batteries. As the trendline is divided, the upper part is a continue of the
start of the trendline, whereas the part continuing lower on the emissions scale is represented by systems
with Li-Ion batteries and the generator. When the trendline reaches a cluster of six dots in groups of two, the
group on the left is the Li-Ion systems with the generator, and the other two are systems with Li-Ion batteries
but no generator. The trendline starting at approximately 420 tonnes CO2-eq and 750 kUSD represents the
systems with LA batteries and no generator. The no generator LA systems then merges with the generator
and no batteries systems around a NPC of 1,000 kUSD. There are two clusters of four dots each that are
separated from the other systems at both 1,750 kUSD and 2,200 kUSD. Both clusters are off-grid systems,
where the ones with lower NPCs are systems with Li-Ion batteries, the left ones with generator and the right
ones without it. The cluster to the right are systems with LA batteries, following the same pattern as the
other cluster with the generator on the left and no generator on the right.
Since there were two types of panels included in the simulations, the difference between implementing
them had to be evaluated as well. Both the economical and environmental impact were evaluated, and this
was done by looking at Figure 6.1 and 6.3 again, but this time with the two types of panels in different
colors. In Figure 6.5 the total renewable fraction (RF) can be seen plotted against the NPC again. It can be
seen that the difference between the two is not that large, although when looking at the individual results
from HOMER Pro it was seen that the monocrystalline systems were slightly more expensive. This can
be seen in the attached Excel file called Collected data from HOMER. However, in Figure 6.6 the installed
capacity of the PV panels can be seen plotted against the lifetime emissions again. It is here clear to see that
the monocrystalline panels would generally provide more lifetime emissions than the polycrystalline ones.
44
Figure 6.5: Total renewable fraction vs NPC for both
poly- and monocrystalline PV panels, MIT.Figure 6.6: Total renewable fraction vs emissions for both
poly- and monocrystalline PV panels, MIT.
Furthermore, there were two types of batteries included and a similar comparison as for the PV panels
was done. In Figure 6.7 the renewable fraction can be seen plotted against the NPC of the electricity
system. The figure clearly shows that the systems including Lead-Acid (LA) batteries were more expensive
to implement, seen to the lifetime of the project, than the systems with Lithium-Ion (Li-Ion) batteries.
Moreover, when looking at the results presented in Figure 6.8 it is also clear to see that the systems with
LA batteries were not only more expensive, but also creators of larger lifetime emissions than the Li-Ion
batteries. An observation worth mentioning regarding the difference of the LA and Li-Ion systems, is that
systems that seems similar between the two when it comes to the RF presented here for example, are in
fact not that similar. The LA systems usually requires a lot more installed capacity, either in terms of PV or
batteries in order to cover the same demand. This can be seen in more detail when looking at the specifics
of all systems in the attached Excel file Collected data from HOMER containing all the simulated systems.
Figure 6.7: Total renewable fraction vs NPC for both LA
and Li-Ion batteries, MIT.
Figure 6.8: Total renewable fraction vs emissions for both LA
and Li-Ion batteries, MIT.
Two systems had to be chosen as recommended for the MIT sub-scenario, one prioritizing the economical
aspect and one prioritizing the environmental aspect. When choosing a system to recommend for a modest
implementation, a few important characteristics to be fulfilled by the system had to be established. In this
case, it was the NPC, initial capital and emissions that should be kept low, while still increasing the RF
of the system and the self-sufficiency and resilience of the AETCR’s electricity system. There were also
constraints regarding the limitations of available land areas to utilize for PV panels. When comparing the
45
NPC and the RF it was decided to choose a system having a system RF of 5%, concluding in a total RF of
77.4%. For a system like that, the NPC and initial capital could still be kept quite low.
There were six potential systems fitting that description, whereas three were with polycrystalline and three
were with monocrystalline panels. Each of the panels then had three versions; no batteries, one LA battery
or two Li-Ion batteries. The batteries would increase both the NPC and the initial capital by a few thousand
dollars, whereas the total gain in production would be a couple hundred kWh per year at best. The LA
battery would lead to increased emissions, whereas the Li-Ion batteries would actually lead to lowered
lifetime emissions of around 0.5 tonnes CO2-eq. Batteries could be good in order to enhance the resilience
of the system towards power outages, but since the already installed generator is in place and has more
than the needed capacity to handle an outage, batteries are not needed for that purpose. All in all, it was
deemed an unnecessary cost to invest in batteries when prioritizing the economical aspect of the system,
since the cost of buying the equivalent amount of energy from the grid would only be around one third
of the price the batteries would add to the NPC. For the environmentally prioritizing system however,
this was considered a good investment since the emissions were mitigated. Coming down to choosing
between poly- and monocrystalline PV panels, it was clear that the monocrystalline ones were both a bit
more expensive and worse when it comes to lifetime emissions. Comparing the land area needed for the
different panels it however showed that the monocrystalline panels would require a smaller land area due
to the higher efficiency and production. Although, the difference was not major. In this case the total area
for the monocrystalline systems with and without Li-Ion batteries and the polycrystalline with and without
batteries were 28.8 m2, 26.6 m2, 32.0 m2 and 29.3 m2 respectively, in the same order as mentioned. Hence,
the polycrystalline panel was chosen for both recommended systems. Some important specifics of the
chosen systems can be seen in Table 6.2 below. In the table, the PV prod. is only the yearly production for
the new installments of PV panels, whereas the Tot. prod. is all the production from both the old and new
PV panels, as well as the generator. In the table below, some more abbreviations are mentioned, namely:
Batt. meaning battery, Cap. meaning capacity and Ini. meaning initial.
Table 6.2: Important parameters for the recommended electricity systems, MIT.
Economical Recommendation
PV Capacity [kW] PV prod. [kWh] PV Area [m2] Tot. prod. [kWh] Sys. RF. [%] Tot. RF. [%]
4.8 5,800 29.3 9,000 5.0 77.4
Batt. Cap. [kWh] Inverter Cap. [kW] Grid purch. [kWh] Ini. Capital [kUSD] NPC [kUSD] Emissions sys. [tonnes CO2-eq]
- 4.3 130,500 18 331 391.9
Environmental Recommendation
PV Capacity [kW] PV prod. [kWh] PV Area [m2] Tot. prod. [kWh] Sys. RF. [%] Tot. RF. [%]
5.3 6,400 32.0 9,600 5.4 77.5
Batt. Cap. [kWh] Inverter Cap. [kW] Grid purch. [kWh] Ini. Capital [kUSD] NPC [kUSD] Emissions sys. [tonnes CO2-eq]
2 3.7 130,100 21 334 391.4
6.1.2.2 Biogas System
In the MIT sub-scenario a biodigester was under consideration, and all available biomass in the AETCR
was assumed to be collected and used to produce biogas. As was mentioned in Section 3.3.3, the available
biomass in AETCR Llanogrande came from 1,000 hens, 200 broiler chickens, 10 bovines, but also from
parts of the 5 tonnes unsorted collected waste each month. Data previously presented in Section 5.3.2,
namely the amount of manure from each livestock, proportions of waste and the VS ratio for each resource,
were used to calculate the total amount of manure, waste and VS. The results can be seen in Table 6.3
below.
46
Table 6.3: Amount of manure, waste and VS for each resource, MIT.
Livestock Number of Amount of Amount VS Waste Amount of Amount VS
livestock [no.] manure [kg/day] [kg/day] waste [kg/day] [kg/day]
Bovines 10 322.0 34.9 Fruit 12.3 1.3
Hens 1,000 68.0 12.2 Vegetable 19.4 0.9
Broiler chickens 200 17.2 3.4 Other waste 43.4 38.7
Sum 1,210 407.2 50.5 Sum 75.1 40.9
As can be seen in the table, the total amount of manure was estimated to 407.2 kg/day, and the total waste
was 75.1 kg/day which corresponded to 46.6% of the unsorted waste each day. With a safety factor of
20% the total amount of manure and waste was 325.8 kg/day and 60.1 kg/day respectively. With the
biomass:water ratio of 3:1, 530 kg/day of biomass would be inserted in the digester, which is equivalent to
0.65 m3/day. The amount of VS from manure was 50.5 kg/day and VS from waste 40.9 kg/day, meaning
that the total amount of VS biomass was 91.4 kg/day. The initial concentration of VS was then calculated
to 140 kg/m3, which was a constant number for the two sub-scenarios MIT and IAB.
In Table 6.4, the volumes of the whole plant (Vp), gas storage (Vg) and digester (Vd) are presented. The
hemisphere design had a smaller volume for each diameter compared to the chinese design. The largest
volume of the hemisphere was calculated to be 32.7 m3 while the chinese had a volume of 55.9 m3. The
volume for each diameter was the same for each of the following scenarios.
Table 6.4: Volume of the digester.
Diameter [m] 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
Hemisphere
Plant Volume, Vp 2.1 2.8 3.6 4.6 5.8 7.1 8.6 10.3 12.2 14.4 16.8 19.4 22.3 25.5 29.0 32.7
Gas Storage Volume, Vg 0.7 1.0 1.3 1.6 2.0 2.5 3.0 3.6 4.3 5.0 5.9 6.8 7.8 8.9 10.1 11.5
Digester Volume, Vd 1.4 1.8 2.4 3.0 3.7 4.6 5.6 6.7 7.9 9.3 10.9 12.6 14.5 16.6 18.8 21.3
Chinese
Plant Volume, Vp 3.6 4.8 6.2 7.9 9.8 12.1 14.6 17. 20.9 24.5 28.6 33.1 38.1 43.5 49.4 55.9
Gas Storage Volume, Vg 1.3 1.7 2.2 2.8 3.4 4.2 5.1 6.2 7.3 8.6 10.0 11.6 13.3 15.2 17.3 19.6
Digester Volume, Vd 2.3 3.1 4.1 5.1 6.4 7.8 9.5 11.4 13.6 15.9 18.6 21.5 24.8 28.2 32.1 36.3
Calculations for the two designs (hemisphere and chinese) were performed for all diameters, between 2 to
5 m. As can be seen in Table 6.5 the only diameter for the hemisphere design in the MIT sub-scenario that
reached a retention time over 30 days was the largest one of 5 m. For the chinese design, diameters larger
than 4 m had a retention time of over 30 days.
Table 6.5: Retention time and yield factor, MIT.
Diameter [m] 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
Hemisphere
Retention time 2.1 2.8 3.6 4.6 5.8 7.1 8.6 10.4 12.3 14.5 16.9 19.5 22.4 25.6 29.1 32.9
Yield factor - - - - - 7.98 7.98 6.79 6.79 6.79 5.90 5.90 5.22 4.69 4.69 4.25
Chinese
Retention time 3.6 4.8 6.2 7.9 9.9 12.1 14.7 17.7 21.0 24.7 28.8 33.3 38.3 43.8 49.7 56.2
Yield factor - - 7.98 7.98 7.98 6.79 6.79 5.90 5.22 5.22 4.69 4.25 3.88 3.58 3.32 2.89
Figure 6.9 presents the produced biogas for the two designs and the current cooking demand of 1,260 m3
per month. Neither of the designs had the potential to cover the full demand, but the largest diameter of
the hemisphere design covered 31% of the demand, while the chinese design covered 37%. In a diameter
interval from 4 to 5 m the differences between the produced amount of biogas was only around 80 m3 per
month for the chinese design, while the difference between the same diameters for the hemisphere design
47
was 110 m3 per month. The chinese design produced slightly more biogas than the hemisphere design for
almost all diameters, and for the smallest diameters the produced biogas was zero due to a retention time
less than 6 days.
Figure 6.9: Produced biogas for hemisphere
and chinese design, MIT.
No biogas was converted to electricity since the produced biogas was not enough to cover the energy
demand for cooking. This applies for all further scenarios as well.
To see how much the biogas system would cost to build and what savings it generated, an economical
analysis was performed. In Figure 6.10 the initial capital cost for the biodigester is presented, which is
the investment cost for the implemented technology. As can be seen in the figure the cost for the chinese
design was higher than for the hemisphere, and for larger diameters the difference between the design was
increased. The chinese design had a higher cost due to a larger volume of the biogas plant. The maximum
cost was just above 3,500 USD for the largest diameter of the chinese design. The Initial capital cost for
the biodigester were the same for every scenario in this report.
Figure 6.10: Initial capital cost for the
biodigester.
Figure 6.11: Savings for the construction year for
hemisphere and chinese design, MIT.
When the biogas system was implemented and the biogas was used as fuel for cooking, the use of LPG
was reduced. This entails that fewer gas bottles were needed, and money could be saved. The investment
and O&M costs were assumed to be paid with the money that was saved due to the reduction of purchased
48
LPG bottles. The other costs linked to the generator, such as upgrading cost, O&M cost and converter
cost between biogas and electricity was not included since all produced biogas was used for cooking. In
Figure 6.11 the savings for construction and replacement years can be seen and already the first year the
expenditures were less than the saved money for the cases where biogas was produced. It can be seen
that the savings of the chinese design were larger for most of the diameters and this was due to the larger
amount of produced biogas. However for the two largest diameters, the yearly savings for the hemisphere
were larger than for the chinese design. This was mainly due to the larger investment cost connected to the
plant volume for the chinese design. For some of the smallest diameters for both designs the savings were
negative. This meant that no money was saved during the year, but rather added as an extra expense, and in
this case it was due to no biogas production.
A new cost regarding the years when the investment cost had been paid off was calculated, and it turned out
that the only cost included was the O&M cost of the digester since it was the only remaining expenditure.
As can be seen in Figure 6.12, the chinese design saved more USD/year compared to the hemisphere design.
Figure 6.12: Savings after the first year for hemisphere and
chinese design, MIT.
Figure 6.13: NPC for the project lifetime for hemisphere and
chinese design, MIT.
The NPC for the biogas system included the investment cost, O&M cost as well as the cost for the LPG.
The NPC was calculated for a period of time of 25 year, which was this projects lifetime, meaning that the
digester was rebuilt once since the fixed dome digester had to be rebuild after 20 years. This resulted in
a double investment cost throughout the project lifetime and the savings calculated for the first year were
thereof counted twice, whereas the savings for the other years were counted for the remaining years of the
lifetime. In Figure 6.13 a decrease of NPC when the diameter gets larger can be seen for both designs.
The NPC for the largest chinese design was lower, 266 kUSD, compared to 285 kUSD for the hemisphere
design.
As for the biogas system the decrease of the CO2 emissions due to the lower LPG consumption can be
seen in Figure 6.14. The CO2 emissions decreased due to the increase of produced biogas and the chinese
design had a larger CO2 reduction than the hemisphere design. The CO2 reduction of the hemisphere design
was decreased with 30% while the chinese design was decreased with 36% for the largest diameter.
49
Figure 6.14: Decrease of CO2 emissions depending on
the diameter for hemisphere and chinese design, MIT.
6.1.2.3 Combined Energy System
Once the electrical and biogas systems had been evaluated separately for both the economical and environ-
mental priorities, the two systems were combined. In Table 6.6 below, the most important parameters
for both of the combined systems are presented. Both of the systems include polycrystalline panels and
the already existing equipment of the AETCR. The chosen biogas system was the chinese design with a
diameter of 4.8 m. That specific plant had a retention time close to 50 days but still in the optimal range.
The production of biogas was high and the emitted CO2 was low compared to the other sizes within the
acceptable range of retention time. Due to the biogas production the number of purchased gas bottles per
month was 21, a decrease of 12 bottles compared to the current purchased gas bottles, and the cost of
the LPG was calculated to be 43% of the total NPC. This configuration was the most suitable for both
the economical and environmental system. In the table, the abbreviations Inv. means inverter, RT means
retention time, Bio. means biogas, Diff. means difference and Em. stands for lifetime emissions. The initial
cost displayed in the table is the cost for implementing both the electricity system and the biodigester, and
covers the costs of buying the equipment and installing it the first year. It does not include any replacement
or O&M costs.
Table 6.6: Parameters for the recommended combined energy systems, MIT.
Economical Recommendation
PV Cap. [kW] Inv. size [kW] Batt. Cap. [kWh] Sys. RF [%] Tot. RF [%] Grid purch. [kWh] Ini. Capital [kUSD]
4.8 4.3 - 5.0 77.4 130,500 21
RT [days] Prod. Bio. [m3] LPG purch. [kUSD] NPC [kUSD] NPC Diff. [kUSD] Em. [tonnes CO2-eq] Em. Diff. [tonnes CO2-eq]
49.7 140,300 258 597 -120 745.1 -214.6
Environmental Recommendation
PV Cap. [kW] Inv. size [kW] Batt. Cap. [kWh] Sys. RF [%] Tot. RF [%] Grid purch. [kWh] Ini. Capital [kUSD]
5.3 3.7 2 5.4 77.5 130,100 24
RT [days] Prod. Bio. [m3] LPG purch. [kUSD] NPC [kUSD] NPC Diff. [kUSD] Em. [tonnes CO2-eq] Em. Diff. [tonnes CO2-eq]
49.7 140,300 258 600 -117 744.6 -215.1
6.1.3 Off-Grid
In this section the results regarding the off-grid simulations performed in HOMER Pro for the MIT scenario
were further looked at, to evaluate the potential of an energy system where the AETCR was self-sufficient.
No changes were added in the biogas system in this sub-scenario and it was assumed the same as for MIT.
50
6.1.3.1 Electricity system
When evaluating the Off-Grid sub-scenario, the same simulated results as shown in Section 6.1.2.1 were
used as a base. Although, there was only a few systems that were off-grid, and they are all shown in
Figure 6.15 and Figure 6.16. In the figures, the two chosen systems are marked as Off-Grid, economical
and Off-Grid, environmental. In Figure 6.15, the RF is plotted against the NPC, and it is clear to see that
all systems have high renewable fractions, but are also quite expensive. The systems on the left side all
includes the generator, hence the RF not reaching 100%, whereas the ones on the right side does not. The
upper left dots represents the LA systems, where the upper one is the monocrystalline one. The bottom left
ones are the Li-Ion systems, where the right one is the monocrystalline system. The dots on the right side
follows the same pattern, where the lower ones are Li-Ion systems, the top ones are LA systems and the
upper one of the two close to each other is the monocrystalline system.
Figure 6.15: Renewable fraction vs NPC, Off-Grid. Figure 6.16: Renewable fraction vs emissions, Off-Grid.
In Figure 6.16 the RF is plotted against the lifetime emissions. The bottom four dots are systems including
Li-Ion batteries, with the generator on the left and without it on the right, whereas the upper ones are
monocrystalline and the bottom ones polycrystalline. The upper four dots are LA systems, with the
generator on the left and without it on the right, where the upper ones are monocrystalline and the lower
ones are polycrystalline. Looking at these two figures it is clear to see that the ones that were preferable
out of an economic perspective were also preferred from an environmental perspective. The initial capital
for the systems with LA batteries was however lower than for the Li-Ion ones, but as can be seen, the more
frequent replacement and lower DoD makes the Li-Ion batteries better in the long run when looking at the
NPC. The initial costs for each system can be seen in the attached Excel file Collected data from HOMER.
Both of the chosen systems and their most important characteristics can be seen in Table 6.7 below.
Table 6.7: Important parameters for the recommended systems, Off-Grid.
Economical Recommendation
PV Capacity [kW] PV prod. [kWh] PV Area [m2] Tot. prod. [kWh] Sys. RF. [%] Tot. RF. [%]
173.0 209,200 1,050 212,500 99.0 99.0
Batt. Cap. [kWh] Inverter [kW] Fuel [l] Ini. Capital [kUSD] NPC [kUSD] Emissions sys. [tonnes CO2-eq]
583 40.9 500 974 1,731 284.9
Environmental Recommendation
PV Capacity [kW] PV prod. [kWh] PV Area [m2] Tot. prod. [kWh] Sys. RF. [%] Tot. RF. [%]
181.2 219,100 1,100 221,100 100 100
Batt. Cap. [kWh] Inverter Cap. [kW] Fuel [l] Ini. Capital [kUSD] NPC [kUSD] Emissions sys. [tonnes CO2-eq]
638 41.1 - 1,036 1,761 270.2
51
6.1.3.2 Combined Energy System
The combined systems of the off-grid sub-scenario were chosen in the same way as the MIT sub-scenario,
where the economical and environmental aspects were evaluated. In Table 6.8 the important parameters
of the two prioritizing systems are presented. The off-grid system with the best economical result had a
system RF of 99% and consumed 500 l of diesel per year. The environmentally prioritizing system had a
system RF of 100% and no fuel consumption. As can be seen in the table, the major differences lay in the
amount of installed PV capacity and the number of Li-Ion batteries, as well as one is without the generator.
Both systems require a large number of batteries and PV panels, however the environmental system needed
55 kWh of extra battery capacity and around 8 kW of extra PV capacity in order to exclude the generator.
As for the biogas system, it was the same plant set up chosen as for the MIT sub-scenario. Due to the
larger amount of batteries the NPC for the environmentally prioritizing system was 30 kUSD higher than
the economical system. The emissions varied with around 15 tonnes CO2-eq.
Table 6.8: Parameters for the recommended combined energy systems, Off-Grid.
Economical Recommendation
PV Cap. [kW] Inv. size [kW] Batt. Cap. [kWh] Sys. RF [%] Tot. RF [%] Grid purch. [kWh] Ini. Capital [kUSD]
173.0 40.9 583 99.0 99.0 - 977
RT [days] Prod. Bio. [m3] LPG purch. [kUSD] NPC [kUSD] NPC Diff. [kUSD] Em. [tonnes CO2-eq] Em. Diff. [tonnes CO2-eq]
49.7 140,300 258 1,997 1,280 638.1 -326.1
Environmental Recommendation
PV Cap. [kW] Inv. size [kW] Batt. Cap. [kWh] Sys. RF [%] Tot. RF [%] Grid purch. [kWh] Ini. Capital [kUSD]
181.2 41.1 638 100 100 - 1,039
RT [days] Prod. Bio. [m3] LPG purch. [kUSD] NPC [kUSD] NPC Diff. [kUSD] Em. [tonnes CO2-eq] Em. Diff. [tonnes CO2-eq]
49.7 140,300 258 2,027 1,310 623.4 -336.3
6.2 Social Development with a Constant Population
In this section the results from the scenario of social development with a constant population are presented.
The electricity demand was increased with 10%, 20%, 30% and 50% which was directly applied on the
load curve. The biomass was also increased with the same percentages and the number of livestock as well
as the new amount of waste due to the increase are presented.
6.2.1 Increased Electricity Demand
As mentioned the electricity system was evaluated for four different cases. The resulting peak demand in
kW and the estimated yearly demand in kWh for each of the increased cases can be seen in Table 6.9 below.
Table 6.9: The resulting peak demand and yearly demand for
the increased electricity demand scenario.
Case BAU 10% 20% 30% 50%
Peak Demand [kW] 23.7 26.1 28.4 30.8 35.5
Yearly Demand [kWh] 138,700 152,570 166,440 180,310 208,050
Based on the new load curves, the resulting systems are shown in Figure 6.17 and Figure 6.18 below. The
first figure, Figure 6.17 presents the values for all cases with the RF plotted against the NPC. It can be
seen that an increased demand leads to an increased NPC in order to maintain the same RF, and the pattern
explained in the MIT case was also seen for the increased cases. The different colors represents the different
cases, where the grey dots are the results from the MIT sub-scenario. In Figure 6.18 to the right, the total
renewable fraction of the system is plotted against the emissions. Yet again it can be seen that the patterns
follow the same layout as for the MIT sub-scenario.
52
Figure 6.17: Renewable fraction vs
NPC for all cases, IED.
Figure 6.18: Renewable fraction vs
emissions for all cases, IED.
In order to asses how an electricity demand increase would affect the final system, a comparison was made
between the previously chosen systems for MIT and Off-Grid, where systems with similar characteristics
regarding RF and type of equipment were chosen for each case in the IED sub-scenario. This table was
presented in order to see the general effects, and hence only the economical system is presented. The most
important parameters are presented in Table 6.10 below. As can be seen, the needed equipment in order to
fulfill the electricity demand with the same system RF increases along with the demand. It can also be seen
that the fractional increase of the MIT cases and the Off-Grid cases depending on the demand are quite
similar.
Table 6.10: The increased electricity demand’s effect on the chosen economical systems.
MIT
Case PV Cap. [kW] PV Area [m2] Batt. Cap. [kWh] Sys. RF [%] NPC [kUSD] Emissions [tonnes CO2-eq]
MIT 4.8 29.3 - 5.0 331 392.0
10% 5.4 32.5 - 5.0 359 428.5
20% 6.5 39.2 - 5.3 386 465.5
30% 6.6 39.7 - 5.1 413 501.7
50% 7.7 46.6 - 5.0 466 575.6
Off-Grid
Case PV Cap. [kW] PV Area [m2] Batt. Cap. [kWh] Sys. RF [%] NPC [MUSD] Emissions [tonnes CO2-eq]
Off-Grid 173.0 1,050 583 99.0 1,731 284.9
10% 190.7 1,160 640 99.1 1,896 309.9
20% 211.8 1,285 688 99.2 2,063 333.0
30% 228.7 1,390 724 99.1 2,230 360.8
50% 265.9 1,615 830 99.2 2,561 409.0
6.2.2 Increased Access to Biomass
In the IAB sub-scenario the total biomass was also increased with 10%, 20%, 30% and 50%. The percentage
was added into the total amount of biomass and in Table 6.11 the corresponding amount of livestock and
waste for each case is presented. Note that only one of the alternatives in each of the columns corresponds
to the increase. For example, a 10% increase corresponds to either 2 more bovines or 9 more pigs etc.
53
Table 6.11: The increase of livestock due to the increased biomass.
10% increase 20% increase 30% increase 50% increase
Bovines [no.] 2 4 5 8
Laying Hens [no.] 660 1,390 2,120 3,580
Broiler Chickens [no.] 520 1,100 1,680 2,831
Pigs [no.] 9 19 29 49
Waste [kg/day] 141 208 274 406
Same as for the MIT sub-scenario the LPG demand corresponded to 1,260 m3 biogas per month and it was
held constant for all of the different cases of IAB. For a 10%, 20%, 30% and 50% increase of biomass the
total biomass was calculated to 580 kg/month, 640 kg/month, 690 kg/month and 790 kg/month respectively.
The result of the hemisphere and chinese design is presented separately since it is easier to see how the
increases affected the two designs. However, since the hemisphere design only had one diameter within the
optimal retention time for the MIT sub-scenario, and an increased amount of biomass results in a decreased
retention time, no diameter of the hemisphere design was suitable for implementation. Hence no result for
the hemisphere design is presented here in the result section, but they can be seen in Appendix A.5.1.
The trend of an increased biomass and a decreased retention time can be seen for the chinese design in
Table 6.12, where the retention time and the corresponding yield factor are presented for each diameter.
Compared to the hemisphere design the chinese design reached retention times over 30 days for some of
the larger diameters when the biomass increased. As for the MIT sub-scenario a 10% increase of biomass
had 5 diameters that reached the optimal retention time, but larger increases of biomass results in fewer
suitable digester sizes and the only diameter within the range of 30 and 50 days for all cases was the
diameter of 4.8 m.
Table 6.12: Retention time and yield factor for the chinese design, IAB.
Diameter [m] 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
10% increase
Retention time 3.3 4.4 5.7 7.2 9.0 11.0 13.4 16.1 19.1 22.4 26.2 30.3 34.8 39.8 45.2 51.1
Yield factor - - - 7.98 7.98 6.79 6.79 5.90 5.90 5.22 4.69 4.25 4.25 3.88 3.32 3.09
20% increase
Retention time 3.0 4.0 5.2 6.6 8.2 10.1 12.3 14.7 17.5 20.6 24.0 27.8 31.9 36.5 41.5 46.9
Yield factor - - - 7.98 7.98 6.79 6.79 6.79 5.90 5.22 5.22 4.69 4.25 3.88 3.58 3.32
30% increase
Retention time 2.8 3.7 4.8 6.1 7.6 9.3 11.3 13.6 16.1 19.0 22.1 25.6 29.5 33.7 38.3 43.2
Yield factor - - - 7.98 7.98 7.98 6.79 6.79 5.90 5.90 5.22 4.69 4.69 4.25 3.88 3.58
50% increase
Retention time 2.4 3.2 4.1 5.3 6.6 8.1 9.8 11.8 14.0 16.5 19.2 22.2 25.5 29.2 33.2 37.5
Yield factor - - - - 7.98 7.98 7.98 6.79 6.79 5.9 5.9 5.22 4.69 4.69 4.25 3.88
In Figure 6.19 the produced biogas for the four different cases as well as the current demand plotted for the
chinese design can be observed. As can be seen no larger differences compared to MIT occurred when the
biomass was increased, for example a 10% increase of biomass resulted in the same amount of produced
biogas for the diameter of 4.8 m. This occurred due to the cases having the same yield factor, but also the
fact that the volume of the biogas plant as well as the ratio of VS in slurry were constant. The number of
needed purchased gas bottles per month for the diameter of 4.8 m was 21, 20, 19 and 18 for the 10%, 20%,
30% and 50% increase of biomass respectively.
54
Figure 6.19: Produced biogas, IAB, chinese design.
As for the MIT sub-scenario an economical analysis was performed. The savings increased when the
biomass increased since less LPG needed to be bought. The savings for the construction year and for the
years when the investment cost was paid off, can be seen in Appendix A.5.2.
The NPC for the chinese design was decreased for the larger diameters compared to the MIT sub-scenario,
which can be seen in Figure 6.20. Compared to the MIT sub-scenario (grey line), the NPC decreases when
the biomass amount increases.
Figure 6.20: NPC over the project lifetime,
IAB, chinese design.
Figure 6.21: Reduction of CO2 emissions,
IAB, chinese design.
The same pattern as for the NPC can be seen for the reduction of CO2 emission. In Figure 6.21 it can be
seen that the increase of biomass also also entails in a larger reduction. A 10%, 20% and 30% increase
generated a decrease of 36%, 39% and 42% CO2 emissions per month, while a 50% increase reached a
decrease of 48% tonnes CO2 emissions per month compared to the current emissions.
6.3 Increased Energy Demand with a Growing Population
In this section, the results of the scenario called Increased Energy Demand with a Growing Population are
presented. The population was increased with 5%, 10% and 15%. For the electricity increase the demand
was increased based on the new amount of inhabitants in the village, whereas the electricity demand of one
55
person was assumed constant. For the biogas system the amount of waste and LPG was increased based on
the population growth, while the biomass from livestock remained the same in this sub-scenario.
6.3.1 Population Growth - Electricity
As mentioned in Section 5.1.1, the demand for the population growth cases were not the same as for the IED
cases, since it was increased based on the population and not the individual demand. Although, the resulting
curves are looking quite similar to the IED ones, only the effects are not as great for this sub-scenario. In
Table 6.13 below, the new peak demand and the estimated yearly demand for each of the cases regarding
population growth are presented.
Table 6.13: The resulting peak demand and yearly demand
for the population growth scenario.
Case BAU 5% 10% 15%
Peak Demand [kW] 23.7 25.0 26.2 27.3
Yearly Demand [kWh] 138,700 146,730 153,300 160,235
In Figure 6.22 the total renewable fraction plotted against the NPC is presented. As can be seen, the NPC
increased slightly when maintaining the same renewable fraction for a system that has a larger demand.
The same trend can be seen in Figure 6.23 where the RF is plotted against the emissions. Furthermore, the
same patterns can be seen as for the base scenario when it comes to the specifics of the different systems,
where the different types of systems were also placed in the same way. The different colors represent the
different cases and increases, where the grey dots yet again shows the MIT case.
Figure 6.22: The total renewable fraction plotted against the
NPC for all cases, PGE.
Figure 6.23: The total renewable fraction plotted against the
emissions for all cases, PGE.
For comparison, a more specific description of the placement of the various systems in the figures can be
seen in Section 6.1.2.1. The corresponding systems for the MIT and Off-Grid sub-scenarios and how they
would change along with the increased population is shown in Table 6.14.
56
Table 6.14: The demand increase of a growing populations effect on the systems, PGE.
MIT
Case PV Cap. [kW] PV Area [m2] Batt. Cap. [kWh] Sys. RF [%] NPC [kUSD] Emissions [tonnes CO2-eq]
MIT 4.8 29.3 - 5.0 331 392.0
5% 5.2 31.2 - 5.1 348 146.7
10% 5.7 34.6 - 5.1 360 430.2
15% 5.6 34.0 - 5.0 374 448.9
Off-Grid
Case PV Cap. [kW] PV Area [m2] Batt. Cap. [kWh] Sys. RF [%] NPC [kUSD] Emissions [tonnes CO2-eq]
Off-Grid 173.0 1,050 583 99.0 1,731 284.9
5% 189.7 1,150 593 99.0 1,824 294.1
10% 199.0 1,210 618 99.2 1,906 306.0
15% 203.1 1,235 664 99.2 1,989 320.9
6.3.2 Population Growth - Biomass
When the population grows so does the amount of waste, and in the PGB sub-scenario the amount of
increased waste was based on how much waste a person in the AETCR generated each month. The total
amount of waste and the entailed VS in the waste caused by the increased population of 5%, 10% and 15%
can be seen in Table 6.15 below.
Table 6.15: Amount of waste and VS from waste, PGB.
5% increase 10% increase 15% increase
Waste Amount of Amount VS Amount of Amount VS Amount of Amount VS
waste [kg/day] [kg/day] waste [kg/day] [kg/day] waste [kg/day] [kg/day]
Fruit 13.0 1.3 13.6 1.4 14.2 1.5
Vegetable 20.5 1.0 21.4 1.0 22.4 1.1
Other waste 45.9 40.9 48.0 42.7 50.1 44.6
Sum 79.4 43.2 83.0 45.1 86.7 47.2
In PGB the biomass from livestock was kept constant and the amount of inserted biomass (biomass mixed
with water) was estimated to be 535 kg/month, 539 kg/month and 544 kg/month for the three cases of
increased population. There were no larger increases of biomass compared to the MIT sub-scenario where
the amount of biomass was 529 kg/month, and since the amount of biomass was quite similar to the MIT
sub-scenario no larger differences for the hemisphere design were seen. The largest diameter was within
the optimal retention time but no other diameters were suitable for implementation, hence all results for the
hemisphere design can be seen in Appendix A.5.3. No larger differences for the chinese design could be
seen either. The same 4 diameters, namely 4.2 m to 4.8 m, were within the optimal range of retention time,
which can be seen in Table 6.16.
Table 6.16: Retention time and yield factor, PGB, chinese design.
Diameter [m] 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
5% Growth
Retention time 3.5 4.7 6.1 7.8 9.7 11.9 14.5 17.3 20.6 24.2 28.2 32.7 37.6 42.9 48.8 55.2
Yield factor - - 7.98 7.98 7.98 6.79 6.79 5.90 5.22 5.22 4.69 4.25 3.88 3.58 3.32 2.89
10% Growth
Retention time 3.5 4.6 6.0 7.6 9.5 11.7 14.2 17.1 20.3 23.8 27.8 32.2 37.0 42.3 48.0 54.3
Yield factor - - 7.98 7.98 7.98 6.79 6.79 5.90 5.22 5.22 4.69 4.25 3.88 3.58 3.32 3.09
15% Growth
Retention time 3.4 4.5 5.9 7.5 9.4 11.5 14.0 16.8 19.9 23.4 27.3 31.7 36.4 41.6 47.3 53.4
Yield factor - - - 7.98 7.98 6.79 6.79 5.90 5.90 5.22 4.69 4.25 3.88 3.58 3.32 3.09
The cooking demand also increases due to the population growth, and for a 5% population growth the
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demand reached 1,330 m3/month, while 10% and 15% had an energy cooking demand of 1,410 m3/month
and 1,450 m3/month respectively. Same as for the other scenarios, the cooking demand is presented
in values of how much biogas that was needed to cover the same amount of LPG. For the three cases
of population growth, the biogas production increased due to the larger amount of accessible biomass.
Although, the growing population also entailed a larger demand of LPG, which increased more than the
added production, and therefore the percentage of demand that could be covered by the biogas decreased.
For all three population growth cases the produced amount of biogas was almost the same. The largest
difference could be seen in the 15% increase of population, and in Figure 6.24 the results for the chinese
design are presented and compared to the MIT sub-scenario. The darker green line represent the new
cooking demand and the lighter green is the cooking demand for MIT and the base scenario. The differences
between the PGB (darker red line) and MIT (light red line) is also displayed and it can be noticed that the
increase of biomass from waste did not have a larger impact of the produced biogas. The number of needed
gas bottles each month for the diameter of 4.8 m for a 15% population growth was corresponding to 26 gas
bottles. The results for 5% and 10% increase for both designs can be seen in Appendix A.5.3.
Figure 6.24: Produced biogas, PGB 15%,
chinese design.
An economical analysis was also preformed for the PGB sub-scenario, where the savings for both the
construction years as well as from the other years when the investment cost had been paid off were
evaluated. In Figure 6.25 the savings during the construction years for all PGB cases as well as for the MIT
sub-scenario can be seen. The savings has decreased compared to the MIT, and for the 15% population
growth no larger savings could be made for the construction years, the savings for the largest diameter was
around zero. The future savings, when the investment cost was paid, also decreased compared to MIT,
which Figure 6.26 shows. The decrease was from around 6,000 USD to around 3,500 USD for the largest
diameter.
58
Figure 6.25: Savings for the construction year, PGB,
chinese design.Figure 6.26: Savings after the first year, PGB,
chinese design.
When the savings had been analysed the NPC of the biogas system, including the cost of LPG, was
calculated and can be seen in Figure 6.27. Compared to MIT the NPC was higher for all diameters, and this
was due to the increased amount of LPG that has to be bought.
Figure 6.27: NPC for the project lifetime, PGB,
chinese design.
Figure 6.28: Decrease of CO2 emissions for
the biogas system, PGB, chinese design.
The CO2 reductions in the PGB sub-scenario were compared with the MIT sub-scenarios, and the results
for the 15% population growth case can be seen in Figure 6.28. The current CO2 emissions based on LPG
use is displayed with a light green line, while the darker green line represent the CO2 emissions for the
increased amount of used LPG when no biodigester has been implemented. The light red line is the CO2
reduction of the MIT sub-scenario and the darker red line represents the PGB of 15%. When the cooking
demand increases due to the population growth more CO2 emissions are emitted. However it can be seen
that the trend of the decrease of emissions remains almost the same for the chinese design even if the
population is growing. It can be seen by comparing the dark red line with the light red line. Which also can
be seen in the figure, the percentage between the CO2 reduction in the MIT sub-scenario and the reduction
in the PGB sub-scenario was similar for the majority of the diameters.
59
6.4 Recommended Combined Energy System
A final recommendation regarding a combined energy system that would be feasible for the population of
AETCR Llanogrande was also presented, and can be seen in this section.
Even though all the electricity systems chosen for the different scenarios were systems that could be
recommended, it was clear once the combined systems were presented, that they may not represent a system
that AETCR Llanogrande would benefit the most from. The savings accomplished by implementing the
biodigester and reducing the costs related to buying LPG were large enough to lower the overall NPC of the
system, when compared to the NPC of the existing energy solution. The recommended systems for the MIT
scenario were a lot cheaper, but did also not provide a very large increase in RF. And the recommended
systems for the Off-Grid scenario were very expensive but provided a large RF. It was however deemed more
feasible for the AETCR to implement a system somewhere in between those previously recommended,
and hence a new electricity system was recommended. As explained in Section 5.7 it was chosen by
taking the total NPC for the current system, including both the installed equipment, the grid and the LPG,
and subtracting the cost of LPG and construction and operation of the biodigester in the case where the
recommended biodigester was implemented. That was then the approximate number of the new NPC for
the electricity system. For this case, that number was 451 kUSD. As the previous results showed, the
polycrystalline panel seemed to be the better choice both for the economy and environment, and hence that
was also chosen for the recommended system. The size of the system that would leave the NPC difference
around zero was according to the results from the simulations in HOMER Pro better off with no batteries,
assuming instead that any overproduction could be sold to the grid. The new system included the generator,
polycrystalline PV panels and the grid but no batteries. The generator had the same usage frequency as
in the BAU, only covering the demand during power outages. The estimated yearly fuel consumption was
the same as for the BAU system, 435 l of diesel, consumed during the 34 hours per year the generator was
used. The already installed PV panels were of course also included in the recommended system, but is not
included in the table below. The area of the new panels was estimated to be around 225 m2. There was
some overproduction from the panels, and around 3,900 kWh was sold to the grid yearly.
The recommended biodigester for the biogas system was selected based on the results calculated for each
scenario. In the evaluation, the retention time, amount of produced biogas, savings, NPC for the biogas
system, as well as the emitted CO2 emissions from the remaining usage of LPG were considered. For the
MIT sub-scenario the chinese design with a diameter of 4.8 m was most beneficial in terms of economical
and environmental aspects and when the other two scenarios, IAB and PGB, were investigated it turned out
that the same configuration was still the better option. For IAB and PGB the retention time was decreased
compared to the MIT value, which was close to 50 days. For the produced biogas no larger differences
could be seen for the PGB sub-scenario, but for IAB it was slightly increased due to the increased amount
of biomass. During the first year, the diameter of 4.8 m had a lower sum of savings compared to the diameter
of 4.2 m. However, after the first year when the investment cost was paid off, and the yearly O&M cost was
deducted, the savings for the larger biodigester were instead higher. The NPC for the biogas system as well
as the CO2 emissions were also lower for the chosen diameter compared to the other diameters.
In Table 6.17 the most important parameters of the combined energy system are presented. As can be
seen, the total NPC was 724 kUSD and the emitted CO2 was 585.4 tonnes CO2-eq. Compared to the BAU
scenario, the NPC was increased by 7,000 USD and the CO2 emissions were reduced by 374.3 tonnes
CO2-eq for the project lifetime. The RF would increase from 76.5% to 83.2% and the total production
would increase with 44,500 kWh per year.
60
Table 6.17: Recommended combined energy system.
PV Cap. [kW] Inv. size [kW] PV Area [m3] Sys RF [%] Tot. RF [%]
36.8 20.5 225 30.1 83.2
Grid purch. [kWh] Ini. Capital [kUSD] Tot. prod. [kWh] RT [days] Prod. Bio. [m3]
98,500 138 47,700 49.7 140,300
LPG purch. [kUSD] NPC [kUSD] NPC Diff. [kUSD] Em. [tonnes CO2-eq] Em. Diff. [tonnes CO2-eq]
258 724 7 585.4 -374.3
For comparison, Table 6.18 and Table 6.19 below displays the corresponding results for the chosen MIT and
Off-Grid economical systems in the other sub-scenarios. Displayed in Table 6.18 are the two sub-scenarios
of Social Development with a Constant Population presented with both the recommended electricity and
biogas systems. The electricity systems presented for both the increased scenarios were as in previous
sections based on similar systems, with a corresponding RF and the same types of installed equipment, and
how they would differ depending on an increased demand. The results displayed for the biogas systems in
both Table 6.18 and Table 6.19 are the corresponding values for the chosen biodigester with a diameter of
4.8 m. The case with a 10% increase of biomass generated the same result as for the MIT sub-scenario and
this was due to the same yield factor.
Table 6.18: The effects of a social development on the recommended electricity and biogas system.
Social Development with a Constant Population
Increased Electricity Demand, IED
Case PV Cap. [kW] PV Area [m2] Sys. RF [%] NPC el. [kUSD] Emissions el. [tonnes CO2-eq]
Recommended 36.8 225 30.1 458 323.2
10% 40.5 250 30.0 498 352.9
20% 44.1 270 30.0 537 382.7
30% 48.0 295 30.0 577 412.3
50% 55.3 340 30.0 656 471.9
Increased Access to Biomass, IAB
Case RT [Day] Prod. Bio. [m3] LPG purch. [kUSD] NPC bio. [kUSD] Emissions bio. [tonnes CO2-eq]
Recommended 49.7 140,300 258 266 353.2
10% 45.2 140,300 258 266 353.2
20% 41.5 151,300 245 253 336.4
30% 38.3 164,000 233 241 319.6
50% 33.2 179,700 221 229 302.8
In Table 6.19 the two sub-scenarios of the Increased Energy Demand with a Growing Population scenario
are displayed, with the differing output for both the recommended electrical and biogas systems.
Table 6.19: The effects of an increased demand with a growing population on
the recommended electricity and biogas system.
Increased Energy Demand with a Growing Population
Population Growth - Electricity, PGE
Case PV Cap. [kW] PV Area [m2] Sys. RF [%] NPC el. [kUSD] Emissions el. [tonnes CO2-eq]
Recommended 36.8 225 30.1 458 323.2
5% 38.9 240 30.1 481 340.4
10% 40.0 245 30.0 500 355.1
15% 42.5 260 30.1 520 369.3
Population Growth - Biomass, PGB
Case RT [Day] Prod. Bio. [m3] LPG purch. [kUSD] NPC bio. [kUSD] Emissions bio. [tonnes CO2-eq]
Recommended 49.7 140,300 258 266 353.2
5% 48.8 141,100 282 290 386.9
10% 48.0 141,900 307 315 420.5
15% 47.3 142,500 319 327 437.3
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In order to better understand how the new system would be designed, a schematic presentation of the system
can be seen in Figure 6.29. The blue arrows and lines represents the electricity connections and which way
the energy flows, whereas the green arrows and lines connects the components and energy flows of the
biogas system. In this new system more renewable energy sources were used, but the system still relied on
the diesel generator during outages and was dependent of the LPG to cover the demand of cooking.
Figure 6.29: Schematics of the recommended combined system.
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7 Sensitivity analysis
In this chapter the performed sensitivity analysis is presented. The analysis was divided into two parts;
the electricity system and the biogas system. How the sensitivity analysis was performed as well as which
parameters involved in the analysis is explained further within the two parts. For both parts a base system
was chosen in order to properly compare the values of the varied parameters. The uncertainties of the
input values for both the economical and environmental factors were evaluated and the parameters with the
largest uncertainty were discussed for both systems.
7.1 Electricity System
When performing the sensitivity analysis of the electrical system throughout the lifetime of the project, one
system was chosen and fixed in HOMER, while one parameter at a time was varied. Since many different
systems were presented as potential solutions, with varying technologies and resulting factors, there was
no perfect system that would correspond to all technologies. It was desired not to choose a system with
a too modest or too substantial RF or self sufficiency since this could also affect the extent of the impact
caused by the various input data. Therefore, the assumed conditions of the chosen system was that it should
be somewhere around the middle of the RF scale, it should contain a rather large amount of batteries,
a generator and have a fairly large capacity of PV. Furthermore, since the proposed new installments
were never mixed considering mono- and polycrystalline panels, as well as LA and Li-Ion batteries in
the simulations, it was important to find a system that still maintained quite similar characteristics in terms
of installed capacities, RF, NPC and emissions when looking at two systems with different types of panels
and batteries. One system was however chosen as a base, in this case a monocrystalline system with Li-Ion
batteries at a system RF of 70%, which was then transformed into two more systems. The transformation
included changing the monocrystalline panels to the same amount of installed capacity of polycrystalline
ones, and changing the installed capacity of Li-Ion batteries in the monocrystalline system, into the same
installed capacity of LA batteries. The chosen system and its translated versions with the other type of
PV and battery are displayed in Table 7.1 below. In addition to the fixed characteristics, only the affected
variables used for further calculations are shown in this table, the full systems can be seen in the Excel file
Collected data from HOMER. Worth noting is that the already installed PV panels are referred to as PV Old
in the following figures. The numbers displayed in the table below are not rounded since they lay the base
for the sensitivity analysis cases.
Table 7.1: Important characteristics of the three systems used in the sensitivity analysis.
Tech. PV [kW] Gen. [kW] Batt. [kWh] Inv. [kW] NPC [USD] RF [%] Gen. [hours]
Mono, Li-Ion 93 140 214 27.6 845,340 92.9 11
Mono, LA 93 140 214 27.6 867,020 88.4 8
Poly, Li-Ion 93 140 214 27.6 841,250 92.9 11
Tech. Gen. prod. [kWh] Gen. fuel [l] PV prod. [kWh] Grid purch. [kWh] Grid sold [kWh] Emissions [kgCO2-eq]
Mono, Li-Ion 385 140 112,770 43,110 6,940 252,880
Mono, LA 280 100 112,770 81,100 24,710 355,920
Poly, Li-Ion 385 140 112,440 43,160 6,850 238,770
Since the first system was used as a reference, most of the variations were simulated depending on that
system. The other two were used when simulating for the technologies that the first system did not contain.
As can be seen in Table 7.1 the systems were however a little bit different in terms of the important
characteristics, and all sensitivities were thereof weighted against its own original numbers, such as NPC
and emissions, in order to create a less complex way of evaluating the results. All the graphs presented
below thereof has no unit on the y-axis, since it is a ratio of the change in each system. The systems
were tested for many different input factors, namely; capital, replacement and O&M costs for each of the
technologies, derating factors for the PV panels, efficiency of the inverter, minimum SoC and throughput of
the batteries, fuel price of diesel, power price of buying electricity from the grid as well as the sellback rate,
63
the individual emissions of each technology, and last but not least, the GHI and DNI. The capital cost was
however not applicable for the already installed equipment. When possible, all variables were evaluated
for a ±20% in steps of 5% change of the input values. However when looking at factors considering
the performance, this was not always applicable. Hence, those sensitivities are presented with a different
percentage change on the x-axis.
The first part evaluated in the sensitivity analysis for the electrical system was the economical effects,
where the NPC was the factor of focus. The superior influence on the NPC came from the capital cost of
the equipment. Furthermore, as can be seen in Figure 7.1 below, the PV panels would create the largest
impact. Since the capital cost of the panels was found to be quite similar, it is not too surprising to see
that they both affect the NPC by the same order of magnitude. Although, both the LA and Li-Ion battery
also has potential to impact the final cost of the system by quite a lot. The Li-Ion however weighs heavier
since the capital cost per kWh of installed capacity was larger than for the LA ones. The inverter capital
cost shows little to no impact on the NPC of the system. Furthermore, these systems are chosen to have
the same amount of installed capacity for the batteries whereas two otherwise "equal" systems in terms
of RF and self-sufficiency each with one type of the batteries, would not have the same amount. As was
mentioned in Section 6.1.2.1 the general systems would require less installed capacity of Li-Ion than LA,
meaning that the impact of the two might differ than from the results of the analysis.
Figure 7.1: How a change of ±20% on the capital costs
affects the NPC.
Figure 7.2: How a change of ±20% on the replacement costs
affects the NPC.
The replacement costs of the various equipment was not really applicable for the PV panels, since the
lifetime was the same as the project lifetime, meaning that they most probably wont need to be replaced
unless something unpredictable happens. The batteries however have much shorter expected lifespans,
meaning that the costs of replacing them every 3 (LA) or 10 (Li-Ion) years inquires large replacement
costs. It is clear to see in Figure 7.2 that it is instead the LA battery that has the largest impact. This was
most probably due to the short lifetime and large amount of replacements. The inverter replacement cost
can also be seen to cause a smaller change on the NPC, however it was not a major influence. The inverter
price was initially part of the capital cost for the PV panels but divided when added into HOMER Pro,
based on findings of a USD/kW price for the equipment. This could cause some margin of error for the
replacement cost, since it was assumed to be the same as the capital cost and that the labor for installing
it might still be included in the capital cost for the PV panels, and not part of the equipment price for the
inverter. This entails that the replacement costs for the inverter might be larger than estimated, however
most probably it does not significantly change the outcome of the analysis since the effect on the NPC of
the tested price change is small in regards to the overall system.
The next costs that were evaluated were the ones for operation and maintenance. As can be seen in
Figure 7.3 the PV panels are yet again the factor that would cause the largest impact if the price would
change. Although, both the batteries and the inverter has the potential of influencing the NPC by quite a
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lot, considering that the NPC is in the order of 100,000’s, a change of 1 percent is equal to a change in
the order of 1,000’s USD. The O&M cost of the already installed PV panels does not affect the system by
much. This is due to the quantity being so small that the price is more or less insignificant compared to the
new installments.
Figure 7.3: How a change of ±20% on the O&M costs affects the NPC.
The influence of the performance of the technologies on the NPC was as mentioned also analyzed. The
performance of the PV panels and the inverter was already quite high, and it was not possible to increase it
by 20% since that would result in a performance larger than 100%. It was thereof increased by percentage
units instead. For the PV panels the derating factor was set to 88% from the beginning, and then being
changed in steps of 2% until ±8%-units was reached in the analysis. The same applied for the inverter
efficiency that was set to 97%, which was changed in steps of 0.5 percentage units until ±2% was reached.
As can be seen in Figure 7.4 below, the largest impact would be caused by the inverter or the PV panels.
The inverter shows a major influence over the NPC. There was however a limitation as to how much the
NPC could be lowered, since the inverter can not get a that much higher efficiency than what was tested
in the analysis. An inverter not functioning well or having a low efficiency means that the transformation
from DC to AC could generate large losses, lowering the power output. This could cause major impacts on
the NPC since all the usable electricity has to go through the inverter and if large losses would occur, either
more electricity would have to be bought from the grid, or a larger system and inverter is needed. The PV
panels also creates a major difference in the NPC when the derating factor is changed. This is due to the
fact that the power production of the system is dependent on the PV panels, meaning that if the generation
increases or decreases the simplest option is to buy more electricity from the grid, which in turn changes the
value of the NPC. In this case there is a large installed capacity of PV panels, resulting in a major difference
in output if the performance of the panels would change. The already installed PV panels however do not
affect the system that much since the capacity is so small.
65
Figure 7.4: How a change of ±8% and ±2% on the
performance of the PV panels and the inverter affects the NPC.
Figure 7.5: How a change of ±20% on the allowed
minimum state of charge affects the NPC.
In Figure 7.5 the effects of changes in the allowed minimum state of charge is displayed. The SoC was
as the other parameters changed with ±20%. It can be seen that both batteries had a similar impact on
the NPC, but that an increase in SoC would cause larger effects than a decrease. This was due to that the
usable capacity of the batteries decreases, and more of the produced electricity that was not needed in the
moment it was created would have to be sold to the grid, or wasted. Furthermore, more electricity would
have to be bought since the overproduction can not be stored to the same extent to be utilized when needed.
And due to that the sellback rate of the grid was set to be half of the buying price, the NPC was bound to
increase as the SoC increases, since more were both bought and sold to the grid. A decrease in the SoC
however would instead decrease the need to purchase electricity from the grid as well as the amount of sold
electricity.An increase in the SoC entails that a smaller part of the capacity in the battery could be utilized
for each cycle of charging and discharging, whereas a decrease allows for a larger part of the capacity to
be utilized. Hence, the throughput of the battery was changed along with the SoC, but in the opposite way.
When looking at the fractional change of the throughput for the changes, it could be seen that the increase
causes a larger loss than the decrease provides extra capacity. The crooked shape of the curve was due to
HOMER Pro changing the amount of used diesel in order to compensate for the extra or lost throughput.
The variable tested next was the grid. Both the power price and sellback rate were tested for variations
that extends from a reduction of 50 percent to a doubling of the price. The results can be seen in Figure 7.6
where it is clear that the power price causes a larger impact on the NPC. This was mainly since the amount
of bought power was so large compared to the amount of sold power. The bent part of the power price curve
was caused by a change in generator usage in the simulations. Since the power price was reduced, HOMER
Pro deemed it feasible to decrease the usage of the generator and increase the amount of bought electricity
from the grid.
66
Figure 7.6: How changes on the price of electricity
bought and sold to the grid affects the NPC.Figure 7.7: How a change of ±20% on the price of
diesel and the GHI affects the NPC.
As can be seen in Figure 7.7 the fuel price of diesel merely has any influence on the NPC. This was due to
the very small amount of used fuel for the generator each year, that the cost could more or less be deemed
insignificant in terms of effects on the NPC. The GHI however plays a big role on the lifetime costs of the
system, since it controls the amount of potential production of all the PV panels. The phenomenon that can
be seen in the figure, where a decrease creates almost a three times larger impact than an increase, could
be explained by how the PV panels function. An increased GHI would result in a higher PV production,
but the increase would also most probably entail an increased cell temperature. The increased temperature
would in turn lower the efficiency of the cells, whereas the improved effects on production due to the GHI
declines as the irradiance was increased. The crooked top left part of the curve was as in the analysis of the
power price due to compensations with the generator production, because of the production losses for PV.
The second part of the sensitivity analysis for the electrical system was concerning the lifetime emissions
of the system. The first part of analysing the lifetime emissions included the individual emissions of each
technology. They were changed by ±20% of the assumed values, and the resulting sensitivity can be seen
in Figure 7.8 below. In the figure it can be seen that the emissions from the grid has the largest impact on
the amount of emissions throughout the lifetime. This was most probably due to the fact that approximately
one third of the electricity demand of this system was bought from the grid. A system with a smaller
grid consumption would hence not be affected to the same extent by the changes in grid emissions. Next
in line was the mono- and polycrystalline panels. It was established early on that the monocrystalline
panels created more emissions than the polycrystalline ones due to the more energy consuming process of
production. That is reflected in the graph, where it can clearly be seen that monocrystalline has a steeper
inclination in effects on the total emissions than polycrystalline panels. It can also be seen that LA and
Li-Ion batteries were not too far off from each other, whereas the Li-Ion was just slightly lower. This was
as mentioned about the NPC due to the short lifetime of the LA batteries. Both batteries’ emissions were
estimated based on the total installed capacity, where the LA actually had lower emissions in terms of
created CO2 per kWh. Although, as can be observed in the figure the longer lifetime of the Li-Ion batteries
outweighs the larger amount of emissions from production. Furthermore, the generator shows quite large
effects on the emissions considering the very small amounts of used fuel each year. This emphasises the
well known fact that burning diesel is not a good option when trying to mitigate emissions, proving the
effects of even small amounts of diesel.
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Figure 7.8: How a change of ±20% on the emissions for
each technology affects the lifetime emissions.
The results based on changes in the performance of the equipment was also evaluated in terms of the
emissions, and can be seen in Figure 7.9. In this case the inverter was yet again the main influence, as could
also be seen when evaluating the NPC for varying performances. And as stated before, it had to do with
the fact that an inverter not functioning very well will limit the power output and force the system to buy
more electricity from the grid. The PV panels also had quite large impacts on the emissions. However, it
could be seen that a change in the polycrystalline panels production would affect the emissions more. This
was as mentioned before due to the already lower efficiency of the panel, causing larger fluctuations in the
amount of produced electricity and hence larger differences in the bought amount of power from the grid.
The emissions from the installed PV panels are not affected much, since the capacity as mentioned was so
small.
Figure 7.9: How a change in performance of the PV panels
and inverter affects the lifetime emissions.Figure 7.10: How a change of ±20% on the SoC affects
the lifetime emissions.
In Figure 7.10 the emissions based on the LA and Li-Ion batteries can be seen. As mentioned when looking
at the NPC, the formation of the curve was due to HOMER Pro compensating for the increased or decreased
self consumption. Due to the compensation it was hard to tell which battery caused the most effects on the
emissions, but the LA seemed to provide the largest overall difference and could therefore be assumed to
be contributing the most.
The last part of the sensitivity analysis for the electrical system was on the GHI, and the results are shown
in Figure 7.11 below. As mentioned for the figure displaying the effects on NPC considering changes in the
GHI, the same applies for the emissions. When the GHI increases, so does the production, but in a slower
pace due to the cell temperature described before. The emissions were in this case mostly tied to the usage
of the grid, which was increased and decreased in the same matter as the curve shown here. The crooked
68
part at the top left of the curve was due to HOMER Pro adding in more production from the generator to
compensate for the production losses from the PV panels.
Figure 7.11: How a change of ±20% on the GHI affects
the lifetime emissions.
In addition to the displayed graphs, changes in the DNI and annual throughput of the batteries were also
tested. However, no noticeable effects could be seen on any of the relevant output within the chosen range of
variance, and the results were thereof not included. All results can be seen in the Excel file called Collected
data from HOMER.
Looking at all the factors affecting the NPC, it could clearly be seen that the largest differences were
caused by the capital costs of the PV panels and the price of buying power from the grid. Although, the
replacement costs of the batteries, the O&M cost of the PV panels and the GHI were not far behind. As
for the amount of emissions throughout the lifetime of the system, the individual emissions from the grid
was by far the most influential. Furthermore, both the individual emissions and performance of the new
installed PV panels and batteries, as well as the performance of said PV panels and the inverter had potential
of effecting the system a lot.
7.2 Biogas System
The sensitivity analysis of the biogas system was performed similar to the approach of the electrical system,
i.e. a set biogas plant was chosen while one input parameter at the time was varied. The chosen plant
configuration was desired to be feasible to implement in the AETCR and therefore the chinese design with
a diameter of 4.6 m was chosen to be evaluated. The parameters that were varied were the amount of
manure from livestock, amount of food waste, VS ratios for manure, VS ratios for waste, produced biogas,
investment cost and O&M cost. For all input parameters except the VS ratios the parameters were changed
by ±20% with steps of 5%. For the VS ratios a change of only ±8% with a step of 2% was performed,
since a larger increase or decrease would generate values that were not possible to obtain, like a negative
amount of VS in the biomass. For the case where the amount of manure was increased, all different types
of animal manure has been increased or decreased separately but equally and at the same time, and then
added together. This was also the case for the VS manure ratios and VS waste ratios. The analysis was
performed for the current available biomass in the AETCR Llanogrande and the output values looked at
were the retention time, biogas production, savings, NPC and emissions. In Table 7.2 the mentioned output
values are displayed for the lifetime of the project, i.e. 25 years.
Table 7.2: Output values for the original case that were used as a comparison when varying parameters.
Retention Time [Days] Biogas Prod. [m3] Savings [USD] NPC [USD] Emissions [kgCO2]
43.8 133,196 127,889 277,111 370,056
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As for the electrical system, all sensitivities were weighted against the original number of the output value
and the results in all graphs below are thereof presented as a ratio of the change. As can be seen in Figure
7.12 the changed amount of manure from the livestock was the most critical parameter and affected the
retention time most. If the manure from each livestock was decreased with 20%, a retention time of more
than 50 days was reached, which is outside the optimal time range. Changing the VS ratio for the manure
and waste does not affect the retention time at all, since the retention time depends on the total amount of
biomass.
Figure 7.12: Changes in retention time. Figure 7.13: Changes in biogas production.
The produced biogas depends on the amount of biomass inserted in the digester, and by varying the
parameters connected to the biomass the produced biogas increases or decreases. In Figure 7.13 the
variation between the input parameters is shown, and even if the VS ratios of manure varied with only
±8% it had the largest impact on the produced amount of biogas. The manure, food waste and VS ratio
of waste did not affect the biogas production as much as the VS ratio of manure. The increased amount of
manure generated a smaller amount of biogas and this was due to the decreased retention time. The amount
of food waste was constant during the increases but when it decreased with more than 10% a reduction
could be seen.
The resulting graph of the savings was quite similar to the biogas production graph. When the VS ratio of
the manure varied, the savings decreased or increased in the same manner. However, as shown in Figure
7.14 there are some changes compared to the biogas production graph. The savings were depending on the
number of gas bottles bought for the AETCR and thereof the graph is more angular. This could easily be
seen when the VS of waste was varied. When the VS of waste was increased, the need to buy LPG was
decreased, resulting in having to buy fewer LPG bottles. For this case an 8% decrease entailed that one
gas bottle less was required per month, which created money savings. Anyhow, the parameter affecting the
savings the most was the VS ratio of manure.
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Figure 7.14: Changes in savings. Figure 7.15: Changes in NPC.
For the NPC evaluation the changes of produced biogas, investment cost and O&M cost were added into
the graph. As can be seen in Figure 7.15 the investment and O&M cost did not have a significant impact
on the NPC compared to the other input parameters. This was mainly because of the high cost of LPG.
Changes in the VS ratio in manure affected the NPC the most, but variations in the amount of produced
biogas also resulted in large differences. The produced biogas was added in order to evaluate the effects
any potential leakages or damage to the equipment could cause.
In Figure 7.16 the analysis of the effects on the emissions are presented. The graph looks similar to the
NPC graph since the emissions only came from the used LPG, which is also the main cost of the biogas
system. Similar as for the savings, the emissions were connected to the number of gas bottles bought for
the AETCR. When the number of bottles decreases so does the emissions, and vice versa.
Figure 7.16: Changes in emissions.
By looking at the results of the sensitivity analysis for the biogas system it can be seen that the factor
with the most impact was the VS of manure. When the VS ratio in manure was varied it resulted in large
changes regarding the output ratio in general. This was due to the new value of the initial concentration of
VS in slurry. If the VS in manure increases the total amount of VS in biomass increases as well, meaning
that the initial concentration of VS in slurry increases and more biogas is produced. With more produced
biogas fewer gas bottles of LPG were needed, and the resulting effects were a reduction of NPC and lower
emissions. Since savings, NPC and emissions were directly connected to the LPG consumption all the
figures look very similar. If the cost of LPG was lower it is possible that the investment cost would cause a
greater affect on the savings and the NPC.
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8 Discussion
In this chapter, results for both the electrical and biogas system are discussed as well as for the combined
energy system that was recommended based on the findings during this project. Social aspects and how
the inhabitants of AETCR Llanogrande could be affected due to the implementation was also discussed.
A sustainability analysis on how the potentially installed energy system was connected to the SDGs was
performed and in the section Further Improvements and Future Work, some of the suggested improvements
of this study outlined along with proposals of future work are presented.
The two research questions that were formed in the beginning of the study reads as follows:
1. What is the best design for an energy system that focuses on each of the three objectives separately?
2. What is the best design for an energy system that combines all of the objectives?
However, only the economical and environmental objectives were measurable in a sense that they could
be analysed. The third objective, the social aspect, was not possible to measure and was hence chosen
to be discussed. Although, the social benefits are affected by the two other objectives in a sense that
any implementation of new energy systems would cause social benefits, such as job opportunities and the
potential of an improved health and lifestyle. This is further discussed in Section 8.4.
8.1 Electricity System
As could be seen in the results, implementing a new electricity system which relies less on the grid and
provides more self-produced electricity would in cases where the right equipment were chosen lower the
emissions over the project lifetime in the AETCR. The implementation of a new system was thereof highly
recommended. The system that was recommended in the previous section, is a good option for both
economical and environmental reasons, since the NPC of the whole project is more or less the same as
it would have been if the current system would be kept, and the emissions were lowered. Although, there
are no clear systems that are right or wrong to implement in terms of size, but the evidence from the results
points towards a system consisting of polycrystalline panels, the generator and Li-Ion batteries would be
the best way to go. There were however a few things to keep in mind when considering an implementation
of the electricity system.
The recommended system that was mentioned in Section 6.4 was based on the current energy situation
of the AETCR and did not consider the potential, and very likely scenario, of social development in the
future. Whether it originates from a population growth or just an individual demand increase along with an
increased standard of living, the system should be implemented with that in mind. Hence, it is important
to consider a system that is easy to develop and expand. Considering the chosen type of inverter, the string
inverter, it would be rather easy to install more inverters if the installed capacity of PV would increase. It
is however usually a cheaper option to buy one large inverter than several smaller ones or upgrading to a
larger one, whereas it is recommended that the size of the inverter is chosen based on the total size of the
system that is desired in the future, rather than to size it after the present implementation. This simplifies
the installation of new panels since the base of the system already exist. It should however be noted that
the PV panels have to be similar in specifics in order for them to be connected in the same string, whereas
future add-ons to the PV system has to be chosen carefully.
When the demand was estimated for the AETCR, it was assumed that all inhabitants had the same consump-
tion and followed the same usage patterns. This might entail errors in the dimensioning of the system, since
there might actually be large differences in the load patterns. For example, there were several children in
the village that most probably did not consume electricity or cooking gas to the same extent as the adults
would. This could lead to the possibility of a system where the average demand for an adult is smaller
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than the real life value, since an extra part of the demand might be "taken" from the amount a child needs.
It should also be considered that the parents and caretakers of the children most probably consumes more
in order to provide for example food, daycare and education for them. Hence, there is a possibility that
the system is either over- or underdimensioned, especially when looking at the scenarios of the increasing
population. The new demand is also depending on the type of people the increased population includes,
like families having children or adults moving into the AETCR, meaning that the new demand may develop
in different ways.
Concerning the placement of the PV panels, no potential land area was evaluated in this report. However,
it was given that there were available land areas that could be utilized. Furthermore, the suggestion of
using the land owned by people living outside the AETCR in exchange for them being able to benefit from
the electricity system was also presented. Although, this evaluation is most probably easier to do on site.
Another thing to consider regarding the placement and the PV area, is that the estimated areas shown in
the results are merely estimates for the area of the actual panels. Depending on how the panels are placed,
the total area will be larger. Space between the panels is required in order to perform maintenance and
reparations, at least on one side, and the possibility of shadowing depending on the tilt angle of the panels
might entail the requirement of having space between them in several directions. Since the AETCR is
located where it rains a lot, this could potentially cause damage to the panels in the form of landslides,
corrosion and undermining of the ground. The chosen location of the panels should therefore be carefully
evaluated. If necessary there are also aids that could be implemented to lessen the impact of the heavy rain,
like retaining walls.
Considering the NPC of the electricity system, it was shown in the sensitivity analysis in Section 7.1 that
the capital cost of the PV panels played a major part. Since all the costs implemented in the system were
estimates and averages of found market prices, they are not necessarily correct. There might be capital cost
reductions if a large capacity is purchased, and if a large system is purchased from a provider that deals
with both panels, inverters and installation, the total cost might be decreased as well. Furthermore, the price
could also increase depending on what panels that are bought.
Throughout the results and the sensitivity analysis, it became quite clear that the polycrystalline panels
along with Li-Ion batteries would be the best combination, if batteries were included in the system. The
polycrystalline panels may have a lower efficiency, but the lower price and the less demanding production
weighs up for it, both in terms of economical and environmental aspects. The estimated amount of
emissions per kWh of produced electricity throughout the lifetime of the PV panels could however vary a
great deal depending on how they were measured, as mentioned in Section 4.1.1, which provides uncertain-
ties in the calculations that can be seen in the performed sensitivity analysis. Furthermore, the lifetime of
the equipment was indicated to play a big part in the sustainability of the system, where fewer replacements
could lead to that a technology with higher production emissions actually has lower lifetime emissions (like
in the LA vs Li-Ion comparison). The costs and emissions related to the transport and maintenance of
equipment with longer lifespans also decreases.
Another parameter that will affect the lifetime costs and emissions was the performance of the different
technologies. As could be seen in the sensitivity analysis, all of the technologies except the old PV panels
could affect the NPC by a lot. It is thereof of great importance to properly manage the maintenance of the
installed equipment, ensuring that the PV panels are clean and placed somewhere with limited interference
of shadowing, and continuous checks to ensure there is no damage to any of the equipment. It could also
be to ensure that equipment that could be sensitive to for example heat or erosion, like the inverter and the
batteries, are placed somewhere that would minimize the risk for damage. This could for example be in the
shadow and with protection from the rain.
When performing the sensitivity analysis, there were some factors that were not included. For example
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concerning when the DoD was changed for the batteries. The changes indicated lowered lifetime emissions
for an increased DoD. This could however be slightly misleading since other aspects of the batteries’
performances changes with the DoD, like the lifetime. Batteries take more damage the larger the span
of minimum and maximum discharge and charge is, which shortens the lifetime and the capacity of
the batteries. This phenomenon was however not included in the sensitivity analysis where the lifetime
remained the same. An increased DoD and a shortened lifetime could thereof instead lead to increased
emissions due to the more frequent replacements. Furthermore, the different systems that were evaluated
were not perfectly equal, which could also cause margins of error when evaluating them, and in the same
way as for the batteries any causal factors that might be changed due to an increase or decrease of the input
parameters were not included in the analysis.
The grid was another input that could cause rather big differences in the outcome of the system. It was
shown early on that the RF of the electricity mix in the grid was already high, at almost 77%, due to large
amounts of hydro power in the country. The hydro power production was however largely depending on
the rain, whereas the amount produced might vary throughout the year. This would in turn entail that the
RF would change depending on the season and the total amount of rain of a specific year. Furthermore,
in the simulations it was assumed that any overproduction of electricity could be sold to the grid. This
might however not be the case, since the electricity company might not be interested in buying it. This
would either lead to a larger amount of wasted electricity, or the waste could be limited. This could be
done by either decreasing the amount of installed PV power, which would also increase the amount of grid
purchases. Or, more batteries could be implemented whereas the overproduction could be utilized when
needed. It could also be sold to the neighbouring people of the AETCR if there is a demand. Throughout
the results it was also very clear to see that there was a distinct connection between the emissions of the
system and the amount of purchased electricity from the grid. It was also the factor that had the largest
impact on the lifetime emissions in the sensitivity analysis.
Some negative aspects of an implementation could be that PV panels does not even remotely blend in
to the landscape. They are quite unappealing to the eye and might cause reflections of the sun that could
be disruptive for both the people and animals in and around the AETCR. Additionally, the construction
of a PV field might also be disruptive to the environment and animal life due to transports, construction,
cabling and so on. Furthermore, there are always extra costs and emissions connected to the transport and
construction of the equipment when it should be built in a remote place. One of the downsides with solar
power is also the fluctuating amount of available energy. On bad days there might be almost no production
at all whereas other days has great production. This would cause some days to rely more on the grid, having
to buy more electricity. Although, since the grid is available, this is not a problem other than that it would
be more expensive and increase the lifetime emissions. The AETCR already has a system that seemingly
works well with covering the demand, apart from the occasional outages and high emissions due to the
LPG. It could thereof be deemed expensive to upgrade the system only to increase the RF and decrease the
emissions.
As mentioned in the results section, the figures were cut in order to be more presentable and easier to
understand. However, there were not that many cases that were not included, but all of them were deemed
unreasonable in proportion to the project. For example systems with huge amounts of PV either with the
generator and no batteries or without the generator with a large amount of LA batteries. In these cases,
the production was not enough to cover the yearly demand and half the demand was bought from the grid,
whereas 7 times the yearly demand was instead sold to the grid. For these cases, both the NPC and the
emissions were very high and so were the initial costs. Hence, they were not considered feasible enough to
include in the figures. But as mentioned they are included in the Excel file Collected Data from HOMER.
Looking at research question one, there were several potential cases that could be good when evaluating
the individual objectives. For all different scenarios and cases, both an economically and environmentally
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prioritizing system was chosen. All the systems were different for the various cases, and the chosen systems
are based on the limitations of the created sub-scenarios of MIT and Off-Grid. There are however systems
that are better both from the environmental and economical perspective, if the limitations are not accounted
for. The absolute cheapest electricity system would be to not change the current system that is already in
place, i.e. the BAU case. Furthermore, there are systems that has lower emissions than the off-grid systems
as well, with the minimized lifetime emissions of 204.9 tonnes CO2-eq. This system can be seen in the
Excel file Collected Data from HOMER.
8.2 Biogas System
For the biogas system two designs of the fixed dome digester was evaluated in order to see which of the
designs that would be recommended to implement. The two different types were the hemisphere design and
chinese design, and in the very first sub-scenario, MIT, the hemisphere design indicated that the amount of
biomass available in AETCR Llanogande was a lot more than optimal for the configuration. It was seen
by looking at the retention time, which did not reach 30 days for any diameters but the largest one. The
same result was obtained in the PGB sub-scenario, however in the IAB sub-scenario, the hemisphere design
could not even be considered as an option due to the low retention time. If the amount of available biomass
was smaller, the hemisphere design would be of greater interest. For the chinese design the amount of
biomass was more suitable, and diameters above 4 m were of interest for all scenarios since the retention
time was in the range between 30 and 50 days. For the MIT scenario the largest diameter, 5 m, was outside
the range. However, for an increase of biomass with at least 20%, i.e. 4 bovines, a digester with a diameter
of 5 m would be feasible to implement. The population growth did not obtain any new results compared
to the MIT sub-scenario since the increase of biomass was too small. With only the results of the retention
time it was clear that a digester with a chinese design would be recommended.
In order to decide which diameter, i.e. volume, the most suitable digester would have, evaluations of the
environmental and the economical aspects were performed. Firstly, the amount of biogas was calculated,
and with a larger diameter more biogas could be extracted from the biomass, since the volume of the plant
was a factor in the produced biogas equation. Hence the digester with the largest volume would constantly
be the one producing most biogas, and therefore decrease the amount of needed LPG. However, that did not
affect the final result in terms of reduced LPG consumption, since the LPG gas bottles consisted of 18 kg
gas, which corresponded to 38 m3 of biogas, and the increase of produced biogas did not change as much
between the different diameters. In the diameter interval of 4 to 5 m the biogas production was increased
with around 80 m3 per month for the MIT sub-scenario, which was equal to 2 gas bottles of LPG. This
meant that some of the diameters had the same reduction of LPG consumption, since a full gas bottle was
purchased even if a smaller amount was needed. Therefore, the graphs regarding the emissions, savings and
NPC was quite angular. These three parameters were directly connected to the purchased LPG gas bottles
and it entailed that the results were more or less similar for every scenario. The obvious choice was thereof
the largest diameter due to the savings each year and the smaller amount of CO2 emissions. The important
factor then was the retention time, and since the diameter of 5 m had a retention time of over 50 days, the
diameter of 4.8 was strongly recommended.
The same system configuration was recommended for all scenarios, as well as for both the economically
and environmentally prioritizing systems. This was due to the fact that the LPG stood for such a large part
of both the emissions and costs, whereas the extra costs added from an increase in biodigester size would
not play that big of a part in the overall price of the system. Hence, a larger biodigester was to prefer in
all cases. Furthermore, the biodigester is most probably not that simple to expand in case of an increased
biomass availability, whereas it is also a better choice to build a larger biodigester that could also fit into
the future development of the society from the beginning.
The NPC calculated for the biogas system included the cost of the LPG, which entailed a high NPC
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for the biogas system in all scenarios. In BAU, 56% of the total NPC was linked to LPG, and with
an implementation of a biodigester and a smaller amount of PV panels the NPC for the economically
prioritizing combined energy system in MIT was reduced with 120 kUSD. The share of LPG in was around
43% of the total NPC and since the LPG cost was included as a part of the biogas system, it seemed like
the implementation of the biodigester was more expensive than it actually was. The largest initial capital
cost of the biodigester was just above 3,500 USD, and this was the cost for the largest proposed digester,
the chinese design of 5 m. However, the investment cost of the digester was estimated to increase linearly
with the volume of the digester, since the data regarding the digester was in a range between two volumes.
Thereof, the investment cost may become higher than the cost calculated in this project, but according to
the sensitivity analysis the changes in costs regarding the digester did not have a major impact on the NPC
in the end. It was however clarified that the implementation of a biodigester reduced the total NPC. But
since the LPG had such a major impact on the NPC, another solution would be to replace the LPG using
gas stoves, with for example electrical stoves. It would lead to an increase of the electricity demand, and
a larger PV system would then be necessary to implement in order to meet the requirements. How the
system set up, emitted CO2 and the NPC would be affected due to the replacement would definitely be an
interesting comparison to the analysis performed in this project. With a replacement of the gas stoves a
huge reduction of CO2 would also occur.
Since it was not possible to replace all used LPG with produced biogas, calculations for the savings were
performed to see how much money that could be saved due to the implementation. It was found that all
volumes of the digesters feasible to implement saved money in all scenarios except in the PGB case with a
15% population growth. In that case only the diameters above 4.4 was saving a smaller amount of money.
Anyhow, the money that had been saved could potentially be used to pay the people who works to collect the
biomass as well as the ones being responsible for equipment, and that the right maintenance is performed
at the configuration. Another thing that has to be noticed is the amount of gas bottles that are bought. Since
the purchased gas bottles depended on the amount of produced biogas and a full bottle was bought if just a
smaller amount of gas was missing, there was gas not being used left each month. It entailed that more LPG
than needed was bought each year which was not considered in the calculations performed in this project.
Therefore, more money could possibly be saved and the NPC and emissions could be reduced as well.
A negative aspect that had been thought about regarding the implementation of the biogas system was
the large land area required to built the biodigester. For this project there were limitations regarding the
available land area, however it was never specified. A digester with a large diameter of 4.8 m was selected
as the recommended choice. The volume of the plant was 49.4 m3 where the larger part of the digester is
placed underground, and was therefore considered to comply with the limitations of available land area.
Although, due to the location in the mountain the bedrock might be difficult to manage. However, the
digester type was assumed to be the most suitable in terms of the sustainability, which was a requirement
since the livestock moves freely and no damage for neither the equipment nor the livestock is desired. If not
enough land is available for such a large implementation, a smaller amount of biomass could be collected
and used. As could be seen in the results for the IAB sub-scenario, an increase of biomass resulted in a
decrease of retention time, so if the case was reverse a decrease of biomass would generate an increased
retention time for the smaller volumes. But if it would be necessary to decrease the amount of biomass, less
money could be obtained and the reduction of CO2 emissions would not be as large as the ones presented
in this report. Another negative aspect was the design of the biogas plant, since it might not be aesthetically
pleasing.
8.3 Recommended Combined Energy System
The second research question was evaluated by finding the recommended combined system. Here, the
economical objective is considered since the systems are chosen so that the NPC of the system is close to
the original NPC that would be obtained if no implementations were added. Through these chosen systems,
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the environmental objective is also considered, since the lifetime emissions are mitigated by 374.3 tonnes
CO2-eq, i.e. almost a third of the original emissions. Furthermore, the chosen systems would also consider
the social objective, which is discussed further in the next section.
The current energy system was seemingly reliable and the outages were estimated to be around 40 hours a
year. During the outages the generator was operated to provide electricity. With the new system a larger
RF would be obtained and the reliability of the system would still remain the same, partly because the
grid would still be connected to the AETCR and the generator would be available to operate if anything
unpredictable would happen.
As mentioned before, the electricity system was chosen based on when the total NPC for both the electrical
and biogas system was close to equal to the original system. It concluded in a system with 36.8 kW of
installed capacity of PV panels, with no added batteries and with the generator, as well as the already
existing PV panels and the grid connection. Since there are no batteries included, the electricity produced
during the day wont be stored, and it would be utilized right away or sold to the grid, whereas the electricity
was bought from the grid in the evenings and when it was dark outside. In the HOMER Pro model
however, the electricity price was set to be the same for all hours of the year, meaning it was not more
expensive during peak hours which is usually a pretty common phenomenon since the demand is larger.
If the electricity prices were in fact more expensive during the peak hours in the evening, it might be
more economical to invest in batteries and save the electricity production from the day to utilize during
the evening, and buy electricity from the grid during the days when it is cheaper. Although, if the desired
system of the AETCR would instead be larger, batteries would be included either way.
In the recommended system, the generator was still utilized. Burning fossil fuels to create power might
seem to completely go against the vision of creating a sustainable energy system. Nevertheless, considering
the few amount of hours per year that the generator was running, the reliability of it during outages and the
electricity security it provided, it was still concluded to be the more sustainable alternative. Considering
that the generator would instead have to be traded for batteries if removed, there would be both extra costs
and emissions for the production of the batteries. Furthermore, the batteries are limited in their capacity,
meaning that if a longer power outage would happen and there was no sun, the power would not last that
long. This also presumes that the batteries were in fact charged at the time of the power outage. The
generator on the other hand can be refilled with stored fuel and run for the period of time that it is needed
and with the necessary power output. Hence, the more sustainable choice for the AETCR would in this
case be to keep the generator and the energy security it provides.
For the biogas system the chinese design with a diameter of 4.8 m was chosen due to the larger amount
of produced biogas and the possible reduction of NPC and CO2 emissions. However, if a smaller digester
would be requested, the chinese design with a diameter of 4.4 m would be a better option. The advantage
of the smaller biodigester was the savings for the construction years. The savings those years were higher
for the diameter of 4.4 m compared to the 4.8 m. However the other years, when the investment cost was
paid off, the savings for the diameter of 4.8 was more profitable.
Based on the results a recommended implementation plan would be to start to build the biodigester in order
to reduce the cost of LPG as soon as possible and reduce the pollutants that the inhabitants were exposed
to. Thereafter, it would be recommended to start implementing the solar system in the extent the available
investment capital would allow. The inverter should however as mentioned not be sized considering the
first implementation of solar power, but the desired final amount in order to save money.
All in all, an implementation of both a biodigester and the electricity system does not have to cost more
than maintaining the already existing system. The momentarily initial capital would be large, but the overall
benefits were deemed worth it.
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8.4 Social aspects
If a new and more renewable energy system was implement in a smaller village like the AETCR Llanogrande
more or less all inhabitants would be affected. A new system could lead to a more sustainable everyday life
for the people living in the AETCR in terms of how to use the available energy resources in the nearby area.
Along with the implementation of new and more sustainable technologies, it might also inspire both the
inhabitants of the AETCR and the people living around the village to progress towards a more sustainable
lifestyle.
For cooking a large amount of LPG was used and the gas was provided by ARN. When using LPG,
pollutants are emitted which could have negative impacts on the inhabitants health, mainly the ones who
usually do the cooking. If the implementation of a biodigester would be reality, biogas could be used as
the cooking fuel instead, meaning that the people would not be exposed to the same amount of pollutants.
Unfortunately, the calculated amount of produced biogas was not enough to cover the full demand for
cooking, and therefore another solution in terms of the health of the people in the AETCR could be to
replace the remaining gas stoves with electrical stoves, which was also mentioned earlier in the discussion.
So, if the LPG stoves were replaced it would benefit both ARN, who was currently paying for the gas, as
well as the people in AETCR Llanogrande.
An implementation of a new renewable energy system was economically evaluated and the cost for the
recommended system reached an NPC of 724 kUSD, which corresponds to around 2,730,000,000 COP.
This value was for the project lifetime of 25 years. Potential investors, sponsors and helping foundations
could be contacted in order to get financial support and depending on whom the owner of the system is,
subsides from the government could be applied for. As mentioned in Section 1.1 there are several large
organizations that has been part of the peace agreement and the reincorporation. For example the European
Union, UNESCO and UNDP. All of these organizations are able to grant funding for projects supporting
their cause, which this project does. Even though the whole sum may not be possible to find funding for,
all additions are good additions. Furthermore, the UN could help with temporary support missions to aid
in maintaining the peace if needed. If the inhabitants of the AETCR had the possibility to own the energy
system it might lead to a lower cost compared to the cost of the electricity from grid, and in the future the
electricity could be more or less for free. If the government pays for the system, it is most likely that the
inhabitants has to pay for the electricity in the same way as they did before the potential implementation.
However, if all maintenance of the system could be performed by the inhabitants, additional cost for workers
could be saved by the government. Therefore, it could be up for discussion to reduce the cost for electricity
due to the performed maintenance.
If the inhabitants had the opportunity to work with the new energy system and perform all necessary
maintenance the NPC might be able to be lowered further. If some of the ground work would be done
by the inhabitants, both as work and in educational purposes, it would benefit all the involved partners. By
educating the inhabitants regarding said groundwork, cost regarding for example transportation and workers
could be reduced. Jobs created due to the new installed biodigester was earlier stated in the biogas system
section above, and for the electricity system jobs concerning the maintenance of the PV-panels, inverters
and batteries can be created. It is important that the PV-panels are kept clean in order to achieve the best
performance possible. Other initiatives, such as the waste collecting system for the families could also be
used to educate the people in the AETCR as well as people in the surroundings of the importance to make
use of all resources.
Most likely, the noise level will increase over a period of time when the system is built. This could have
a negative impact on the inhabitants and animals residing in the close proximity. Another negative impact
could be the less pleasant view around the village, where the biodigester or a PV field would take place.
The livestock could also be negatively affected since they move freely, and with a new energy system the
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available area could be reduced.
8.5 Sustainability analysis
In order to properly analyse the sustainability of the project, a comparison of the different SDG’s presented
in Section 2.3 was done. The first SDG, SDG 7, handles the right to access to affordable and clean energy.
By implementing the combined system of both PV, batteries and biogas, the amount of clean energy in the
village could be increased. Furthermore, as mentioned in the previous section, using biogas instead of LPG
even further contributes to this SDG, since the pollutions emitted while cooking could be mitigated and a
more sustainable everyday situation could be created for many of the inhabitants. Regarding SDG 8, about
decent work and economic growth, not only could work opportunities occur due to the implementations,
learning about sustainability and renewable energy sources could also open doors for the inhabitants and
might be something they find interesting and wants learn more about, or even work with. When it comes to
SDG 11, sustainable cities and communities, it seemed reasonable to assume that the AETCR is well on its
way towards becoming a more sustainable community. Both since a system for food waste collection has
been introduced and since this thesis was suggested. Furthermore, if the new energy system is implemented,
the vast majority of the electricity comes from renewable energy sources that would decrease the emissions
by more than 350 tonnes CO2 over 25 years. The implementation of new technologies might also lead the
inhabitants of the AETCR and the surroundings to even further improve the sustainability aspects of their
everyday life and might inspire others to do the same thing, as mentioned in the previous section.
Of course there are also downsides to implementing a new system, even if it includes better and cleaner
energy sources. For example what was discussed regarding the fluctuation of solar power, which might
lead to power losses during long periods of limited irradiation. Although, since both the grid and the
generator are available, that loss in production may not necessarily affect the inhabitants. And even though
the village most probably will never be CO2 neutral, the sustainability steps taken by implementing even a
smaller renewable system, are steps in the right direction. In addition, all the aims and goals of this thesis
includes and revolves around creating a sustainable energy system for the AETCR and the subject has been
discussed throughout the length of the report.
8.6 Further Improvements and Future Work
A proposed improvement of this project is to analyse the electricity consumption in the AETCR more in
detail. With more knowledge of the electric appliances, such as TVs, fridges, freezers, laundry machines
and electrical stoves etc., as well as when and how often they are used, would entail a more reliable load
curve. Another improvement is regarding the cost of the technologies, implementations, fuels and the grid.
A further research of the Colombian market could generate an improved economical analysis. How much
money that can be obtained if some of the produced electricity would be sold back to the grid, is also an
area of improvement potential, since the prices were based on the electricity market in Sweden.
In terms of future works, measurements of the water flow in the two other streams would be interesting
to have in order to evaluate if it is possible to implement a micro-hydro system. Although, since the two
streams are located in the mountain area it could be difficult to implement a system, both due to the harsh
environment and that the distance to the AETCR may be too far away if anything unpredictable would
happen and the system was damaged. The measurements in this project were performed during the dry
season when the water level was reduced by half. Even though the results indicated that it would not be
possible to install a feasible micro-hydro system it would be interesting to see how the measurements would
change during the rain season. It might be possible to implement a micro-hydro system that only runs in
the raining season, to compensate for when the PV output may not be as large. On-site measurements of
the irradiance could also be of great interest in order to further evaluate the feasibility of the system, since
the current data is merely estimated.
79
During the time this report was written, discussions regarding the initiation of a waste-collecting project was
performed in AETCR Llanogrande. The potential to collect waste and directly insert it into a biodigester
could definitely be further investigated and analysed in further projects to see how it would affect the
outcome of the biogas system. The potentially increased RF due to the implementation of the biogas system
was not evaluated in this project, and could be further analysed in the future. Also an analysis regarding
the replacement of the gas stoves, discussed earlier, can be performed to see if it would be possible to
completely remove the usage of LPG.
As mentioned in the discussion regarding the electricity system, the land area at which the system should
be implemented needs to be evaluated before an implementation is possible. Furthermore, depending on
the intended land area, and whether the system should be shared with neighbouring people and farms or
not, the capacity of the system might need to be increased in order to meet the new demand. Furthermore,
the type of soil that the PV field should be placed on defines which type of mounting hardware that should
be used, which is another future evaluation point that needs to be performed. Something that should also be
considered when choosing the placement, is that there are both agriculture and livestock projects planned
for future implementation, whereas the PV panels could be used for shadow. Furthermore, if hourly price
rates is something that is used in the AETCR, it could be interesting to apply this to the HOMER Pro model.
In the sensitivity analysis it could be seen that the performance of the panels, inverter and batteries could
affect the system by quite a lot. The Li-Ion batteries could as mentioned have a DoD up to 80 - 100%
without taking too much damage or have extensive lifetime shortages. Utilizing batteries like that is most
probably more expensive, but the benefit would be that fewer would be needed. It could thereof be of
great interest to further investigate whether or not the extra expense would be worth the benefits before
implementing any batteries. It was stated in the beginning of the project that a supply of hot water was not
a necessity for the AETCR, however it could be of interest to further evaluate the potential of either PVT
or thermal collectors. This could provide hot water for showers and everyday hygiene like handwashing
after toilet visits and so on, as well as any needed heat for the biodigester. Since the available land area was
limited, PVT could be a great solution, even though the efficiencies are lower than for the separate systems.
80
9 Conclusion
Early on in the study it was concluded that neither wind nor hydro power were feasible technologies to
implement due to the prerequisites of AETCR Llanogrande. The access to biomass and the amount of
solar irradiation however showed great promise and two systems were evaluated around those resources;
the electrical system and the biogas system. Furthermore, the main fuel for cooking in the village was
LPG, which is a gas that releases plenty of pollutants and emissions when burned and could potentially
contribute to health issues. Any produced biogas could aid in decreasing the usage of LPG, and mitigate
both the pollutions and emissions.
The electrical system was evaluated for both mono- and polycrystalline PV panels, LA, Li-Ion and no
batteries, with and without the already existing generator and with and without the grid. It was concluded
that a polycrystalline system, with the generator and the grid connection, along with Li-Ion or no installed
batteries would be the preferable combination both from an economical and environmental point of view.
There were plenty of options as to how big the system could be depending on the desired outputs in terms
of RF, costs, available land area for the PV panels, the extent of the desired self-sufficiency and the amount
of lifetime emissions.
As for the biogas system it was concluded that an implementation of a biodigester could lead to a reduction
of LPG used for cooking in the AETCR. Hence, the purchased gas decreased, meaning that the expenditures
decreased and the emissions were reduced. The chosen type was a fixed dome biodigester with a chinese
design and a diameter of 4.8 m. By implementing a biodigester a few job opportunities could also be created
regarding biomass collection and maintenance of the biodigester. Therefore, with all three objectives
evaluated and based on calculations performed in this project, it was possible to install a biodigester in
AETCR Llanogrande.
The chosen combined energy system that was recommended had a total production of 47,700 kWh for
the electrical system where the total RF was estimated to be 83.2%. The inverter size was 20.5 kW and the
area of the PV panels was calculated to be 225 m2. The initial cost of both the electricity and biogas system
was 138 kUSD. The diesel generator operated for 34 h per year, which was during the outages where it
consumed 435 l of diesel. The electricity bought from the grid was 98,500 kWh and the electricity sold
was 3,900 kWh yearly. The cost of the LPG used for the cooking was 258 kUSD during the lifetime of the
project, which was 25 years. The biogas system had a retention time of 49.7 days and produced 140,300 m3
of biogas. The total NPC was then calculated to 724 kUSD and resulting in an almost equal NPC compared
to the lifetime costs for the operations of the current system. The emissions were however estimated to
be 585.4 tonnes CO2-eq, which was a reduction of 374.3 tonnes CO2-eq. The overall conclusion was
that an energy system should be implemented, with both the biodigester and electrical system in order to
maximize the benefits. However, the size of the electrical system could be varied depending on the desired
characteristics of AETCR Llanogrande.
81
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92
A Appendix
In the appendix information about AETCR Llanogrande, Hydro power measurements manuals, MATLAB
codes and results are inserted in order to take part of more information and calculated data.
A.1 Conditions for AETCR Llanogrande
Within this section graphs and diagrams of climate conditions for AETCR Llanogrande are shown. The
measured values and pictures from the flow measurement of the stream are presented as well as pictures of
the existing generator.
A.1.1 Generator
Figure A.1.1 and Figure A.1.2 shows the existing generator in AETCR Llanogrande.
Figure A.1.1: The generator. Figure A.1.2: The generator.
A.1.2 AETCR Climate
The precipitation and cloud cover are presented in the diagrams. The data in the diagrams are based on 30
years of hourly weather model simulations for Llanogrande. [40]
Figure A.1.3: Days with precipitation in
Llanogrande. [40]
Figure A.1.4: Days with cloud cover in
Llanogrande. [40]
As can be seen in Figure A.1.3, the precipitation varies each month in Llanogrande and it is only a few days
that are completely dry. The average precipitation is 281.5 mm each mouth throughout the year. In addition
93
to precipitation, the cloud cover over Llanogrande is presented in Figure A.1.4. Overcast days are the ones
with 80 % or more cloud cover, and partly cloudy represent days with a cover of 20 - 80 %. Worth to notice
is the very few days that are completely sunny.
A.1.3 Irradiance
The yearly irradiance in Llanogrande is presented in Figure A.1.5 to A.1.8. Each figure displays the
irradiance for three months, and it can be seen it is quite constant, varying from around 450 - 700 W/m2.
Figure A.1.5: Average daily global irradiance
in Llanogrande from January til March. [19]
Figure A.1.6: Average daily global irradiance
in Llanogrande from April til June. [19]
Figure A.1.7: Average daily global irradiance
in Llanogrande from July til September. [19]
Figure A.1.8: Average daily global irradiance
in Llanogrande from October til December. [19]
A.1.4 Hydro Measurement
As was described in Section 3.3.2 the measurement were performed at five different routes. In Table A.1.1
to A.1.5 the measured values of the length, width, depth and time are presented.
Table A.1.1: Route 1.
Measurement 1 2 3
Length [m] 1.7 1.7 1.7
Width [m] 0.6 0.6 0.6
Depth [m] 0.14 0.12 0.10
Time [s] 2.81 2.89 3.35
Table A.1.2: Route 2.
Measurement 1 2 3
Length [m] 1 1 1
Width [m] 0.4 0.4 0.4
Depth [m] 0.15 0.15 0.12
Time [s] 1.72 1.2 1.48
94
Table A.1.3: Route 3.
Measurement 1 2 3
Length [m] 1.2 1.2 1.2
Width [m] 0.5 0.5 0.5
Depth [m] 0.13 0.12 0.13
Time [s] 3.02 3.23 3.47
Table A.1.4: Route 4.
Measurement 1 2 3
Length [m] 1.3 1.3 1.3
Width [m] 0.5 0.5 0.5
Depth [m] 0.13 0.13 0.12
Time [s] 1.93 1.45 1.75
Table A.1.5: Route 5.
Measurement 1 2 3
Length [m] 1.1 1.1 1.1
Width [m] 0.5 0.5 0.5
Depth [m] 0.14 0.13 0.11
Time [s] 1.92 2.1 1.85
In Table A.1.6 the calculated average velocity and water flow for both dry season (January- April) and
rain season (May- December) for each route are presented as well as the average values that represent the
velocity and water flow for the stream.
Table A.1.6: Calculated measurement results.
Route 1 2 3 4 5 Stream average
Velocity [m/s] 0.57 0.70 0.37 0.77 0.56 0.60
Water flow, dry season [l/s] 41.2 39.1 23.5 48.9 35.6 38.2
Water flow, rain season [l/s] 82.4 78.2 47.1 97.8 71.2 76.4
In Figure A.1.9 to A.1.12 more pictures taken by Mr. Fernández during the time of the measurement are
attached.
Figure A.1.9: Surroundings of the stream. Figure A.1.10: Measure of the length.
95
Figure A.1.11: Measure of the width. Figure A.1.12: Measure of the depth.
96
Hydropower Measurement manual
Head & Flow In order to create electricity from hydropower, two parameters are critical:
Flow; or the minimum amount of water that is constantly available throughout at least 9
months of the year.
Head; the difference in height between upper water level and lower water level.
With knowledge of water flow and height difference the potential power can be estimated.
Measuring Head & Flow The first step to judge a sites hydropower potential is to measure/estimate head and flow.
Head (the vertical distance between the intake and the outflow of the turbine)
Flow (how much water comes down the stream)
Head is very often exaggerated as is the flow rate, which varies over the year.
Wrong data occurs frequently. Confirmation of existing data is highly recommended!
Head and flow are the two most important facts of a hydro site. This will determine everything about
the hydro system - volume of civil constructions, canal size, turbine size and power output.
Inaccurate measurements can result in lower efficiency, and higher cost.
For sophisticated methods how to inquire a sites feasibility, "Layman's book: How to develop a Small
Hydro Site" may be a good start.
A.2 Hydro Power Measurement Manual
Here the manual used for the measurements of the water flow in the river close to AETCR Llanogrande
is presented [136]. The manual was retrieved from Turbulent ([46]) and translated to Spanish, since the
contact with Néstor Fernández has partly been in Spanish.
English:
97
Simple methods for Head and Flow Measurement
If detailed maps with contour lines are available or a topographical survey has been done, the
gross head can be determined by consulting these aids. Otherwise the following methods can be
used to determine the head. You will now measure the height difference between the inlet and the
outlet of your future turbine. The following methods can be used:
Spirit level and plank (or string): This is a step-by-
step procedure to determine total head Hg
between outflow water level and upper
water level (at waterfall / inlet), by using a spirit level
and plank. When measuring over a longer distance,
you measure the height difference in multiple
sections (with a distance in between of the length
of your plank). You then add them all up using the
following formula to reach the total head.
Estimation of height
98
A correct estimation of flow is more difficult without special devices, however, there is a very easy method to
do a rough estimation. This will quickly show you if your site is suitable for our turbines.
Float method:
Procedure:
locate an evenly flowing area of water of a certain length L [m] where there is almost
no turbulence.
Determine the area’s cross section by measuring
B [m] and H [m]: A = B x H
In order to determine velocity V [m/sec] measure the time T [sec] it takes for a float to travel the above determined length L (allow floats to accelerate before the start), then divide length L by time T. V = L / T
to determine the flow Q multiply velocity V by cross-sectional area A. Q = V x A
With thanks to Energypedia and GTZ for the source materials.
Estimation of flow
Example:
A ball drifts 10 m in 20 s speed = 10m/20s = 0.5 m/s.
Cross section A= 5 m x 0.5 m = 2.5 m2
Flow volume 0.5 m/s x 2.5 m2 = 1.25 m3/s = 1250 l/s
99
Manual de medición de la energía hidráulica
Altura y caudal
Para crear electricidad a partir de la energía hidroeléctrica, hay dos parámetros
fundamentales:
Caudal; o la cantidad mínima de agua que está constantemente disponible durante al
menos 9 meses del año.
Altura; la diferencia de altura entre el nivel de agua superior y el nivel de agua inferior.
Conociendo el caudal de agua y la diferencia de altura se puede estimar la potencia
potencial.
Medir la altura y el caudal
El primer paso para juzgar el potencial hidroeléctrico de un lugar es medir/estimar la altura y
el caudal.
● Altura (la distancia vertical entre la entrada y la salida de la turbina)
● Caudal (la cantidad de agua que baja por la corriente)
La altura suele ser exagerada, al igual que el caudal, que varía a lo largo del año.
Los datos erróneos son frecuentes. Es muy recomendable confirmar los datos existentes.
La altura y el caudal son los dos datos más importantes de un emplazamiento hidroeléctrico.
Esto determinará todo lo relacionado con el sistema hidroeléctrico: el volumen de las
construcciones civiles, el tamaño del canal, el tamaño de la turbina y la potencia. Las
mediciones inexactas pueden dar lugar a una menor eficiencia y a un mayor coste.
Dependiendo de cómo sea el río (véanse los tres tipos siguientes) las medidas para
determinar la altura serán diferentes. Si el río presenta caídas bruscas (tipo 1 y 2), basta
con medir el desnivel. Si desciende gradualmente, se debe medir una distancia de 100
metros.
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100
Métodos sencillos para medir la altura y el caudal
Estimación de la altura
Para determinar la altura se pueden utilizar los siguientes métodos. A continuación, mida la
diferencia de altura entre la entrada y la salida de su futura turbina. Se pueden utilizar los
siguientes métodos:
Nivel de burbuja y tabla (o cuerda): Se trata de
un procedimiento paso a paso para determinar la
altura total Hg entre el nivel del agua de salida y el
nivel superior del agua (en la cascada/entrada),
utilizando un nivel de burbuja y una tabla. Cuando
se mide una distancia mayor, se mide la diferencia
de altura en varias secciones (con una distancia
intermedia de la longitud de la tabla). A
continuación, se suman todos los tramos utilizando
la siguiente fórmula para obtener la altura total.
Altura de la presa - para el diseño Caída bruta
Estimación del caudal
Una estimación correcta del caudal es más difícil sin dispositivos especiales, sin embargo,
hay un método muy fácil para hacer una estimación aproximada. Esto le indicará
rápidamente si su emplazamiento es adecuado para nuestras turbinas.
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Método del flotador:
Procedimiento:
● Localice una zona de agua que fluya uniformemente y tenga una longitud
determinada L [m] en la que apenas haya turbulencias.
● Determine la sección transversal de la zona midiendo B [m] y H [m]: A = B x H
● Para determinar la velocidad V [m/seg] mide el tiempo T [seg] que tarda un flotador
en recorrer la longitud L determinada anteriormente (deja que los flotadores se
aceleren antes de la salida), luego divide la longitud L por el tiempo T. V = L / T
● Para determinar el flujo Q multiplique la velocidad V por el área de la sección
transversal A. Q = V x A
Ejemplo:
Una bola se desplaza 10 m en 20 s velocidad = 10m/20s = 0,5 m/s.
Sección transversal A= 5 m x 0,5 m = 2,5 m2
Volumen de flujo 0,5 m/s x 2,5 m2 = 1,25 m3/s = 1250 l/s
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A.3 Demand Curve Table
In Table A.3.1 below, the estimated hourly values for each of the scenarios can be seen.
Table A.3.1: The hourlu values for the different demand curves.
Hour Base Case Increased Demand Increased Population
0% 10% 20% 30% 50% 5% 10% 15%
1 9.69 10.66 11.63 12.60 14.54 10.24 10.72 11.19
2 9.53 10.48 11.43 12.38 14.29 10.07 10.53 11.00
3 8.38 9.21 10.05 10.89 12.56 8.85 9.26 9.67
4 8.90 9.80 10.68 11.57 13.35 9.41 9.84 10.28
5 10.51 11.56 12.61 13.67 15.77 11.11 11.62 12.14
6 9.85 10.84 11.83 12.81 14.78 10.42 10.90 11.38
7 11.37 12.50 13.64 14.78 17.05 12.01 12.57 13.12
8 11.69 12.86 14.03 15.20 17.54 12.36 12.93 13.50
9 13.80 15.18 16.56 17.94 20.70 14.58 15.25 15.93
10 15.47 17.02 18.57 20.11 23.21 16.35 17.11 17.86
11 16.88 18.57 20.26 21.95 25.33 17.85 18.67 19.49
12 18.07 19.87 21.68 23.49 27.10 19.10 19.98 20.86
13 20.07 22.08 24.09 26.09 30.11 21.21 22.19 23.17
14 19.58 21.54 23.49 25.45 29.37 20.69 21.65 22.60
15 21.88 24.07 26.25 28.44 32.82 23.12 24.19 25.26
16 21.71 23.88 26.06 28.23 32.57 22.95 24.01 25.07
17 18.89 20.78 22.67 24.55 28.33 19.96 20.89 21.81
18 19.41 21.36 23.30 25.24 29.12 20.52 21.47 22.41
19 21.35 23.49 25.62 27.76 32.03 22.57 23.61 24.65
20 20.70 22.76 24.83 26.90 31.04 21.87 22.88 23.89
21 23.68 26.05 28.42 30.79 35.53 25.03 26.19 27.34
22 19.22 21.14 23.06 24.98 28.83 20.31 21.25 22.19
23 17.05 18.75 20.46 22.16 25.57 18.01 18.85 19.68
24 12.32 13.55 14.78 16.01 18.48 13.02 13.62 14.22
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A.4 Yield Factor for Biogas Production
The yield factor was retrieved from the report Measuring small-scale biogas capacity and production
published by IRENA [128].
Table A.4.1: Yield factors for biogas production,
by temperature and feedstock retention time.
Retention time [Days] 19-21 [°C]
6-10 7.98
11-15 6.79
16-20 5.90
21-25 5.22
26-30 4.69
31-35 4.25
36-40 3.88
41-45 3.58
46-50 3.32
51-55 3.09
56-60 2.89
61-65 2.72
66-70 2.57
71-75 2.43
76-80 2.30
81-85 2.19
86-90 2.09
91-95 2.00
96-100 1.92
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A.5 Biogas System Results
In this section all results from the biogas calculations are presented. The hemisphere design for all scenario,
except of the results from the MIT sub-scenario (which was presented in the result chapter), can be seen as
well as the results from PGB for the 5% and 10% increased population for the chinese design.
A.5.1 Increased Access of Biomass - Hemisphere Design
The retention time and the yield factor for all diameters of the hemisphere design for the IAB sub-scenario
are presented in Table A.5.1. None of the cases where the biomass was increased for the hemisphere design
resulted in a retention time above the optimal limit of 30 days.
Table A.5.1: Retention time and yield factor for hemisphere design, IAB.
Diameter [m] 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
10% increase
Retention time 1.9 2.5 3.3 4.2 5.3 6.5 7.8 9.4 11.1 13.1 15.3 17.7 20.4 23.3 26.5 29.9
Yield factor - - - - - 7.98 7.98 7.98 6.79 6.79 5.90 5.90 5.22 5.22 4.69 4.69
20% increase
Retention time 1.8 2.3 3.0 3.9 4.8 5.9 7.2 8.6 10.2 12.0 14.0 16.3 18.7 21.4 24.3 27.4
Yield factor - - - - - - 7.98 7.98 6.79 6.79 6.79 5.90 5.90 5.22 5.22 4.69
30% increase
Retention time 1.6 2.2 2.8 3.6 4.4 5.5 6.6 8.0 9.5 11.1 13.0 15.0 17.3 19.7 22.4 25.3
Yield factor - - - - - - 7.98 7.98 7.98 6.79 6.79 5.90 5.90 5.90 5.22 4.69
50% increase
Retention time 1.4 1.9 2.4 3.1 3.9 4.7 5.8 6.9 8.2 9.6 11.2 13.0 15.0 17.1 19.4 21.9
Yield factor - - - - - - - 7.98 7.98 7.98 6.79 6.79 6.79 5.90 5.90 5.22
As shown in Figure A.5.1, the produced biogas for the hemisphere design does not change much due to the
increase of biomass.
Figure A.5.1: Produced biogas, IAB, hemisphere design.
An economical analysis was performed for the IAB sub-scenario, and in Figure A.5.2 the savings for the
construction year are presented. It can be seen that more money can be saved when the biomass inserted in
the biodigester increased.
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Figure A.5.2: Savings for the construction year,
IAB, hemisphere design.
Figure A.5.3: Savings after the first year,
IAB, hemisphere design.
The results of the savings when the investment cost was paid off is displayed in Figure A.5.3 and the results
of the NPC is presented in Figure A.5.4. When the biomass increased, a reduction of NPC can be seen for
all diameters where the biodigester produce biogas.
Figure A.5.4: NPC for the project lifetime,
IAB, hemisphere design.
Figure A.5.5: Reduction of CO2 emissions,
IAB, hemisphere design.
For the environmental impact of the hemisphere design the reduction of CO2 emissions was determined.
As can be seen in Figure A.5.5 the decrease of CO2 emissions was similar to the NPC graph since both
parameters depends on the number of LPG bottles that has to be bought.
A.5.2 Increased Access to Biomass - Chinese Design Savings
The savings for both the construction year and the years when the investment cost is paid off can be seen in
Figure A.5.6 and Figure A.5.7.
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Figure A.5.6: Savings for the construction year,
IAB, chinese design.
Figure A.5.7: Savings after the first year,
IAB, chinese design.
A.5.3 Population Growth
In Table A.5.2 the retention time and the corresponding yield factor for the hemisphere design in the PGB
scenario is presented. As can be seen, only the diameter of 5 m reaches a retention time over 30 days.
Table A.5.2: Retention time and yield factor, PGB.
Diameter [m] 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
Hemisphere
5% Growth
Retention time 2.1 2.8 3.6 4.5 5.7 7.0 8.5 10.2 12.1 14.2 16.5 19.1 22.0 25.1 28.6 32.3
Yield factor - - - - - 7.98 7.98 6.79 6.79 6.79 5.90 5.90 5.22 4.69 4.69 4.25
10% Growth
Retention time 2.0 2.7 3.5 4.5 5.6 6.9 8.3 10.0 11.9 13.9 16.3 18.8 21.7 24.7 28.1 31.8
Yield factor - - - - - 7.98 7.98 7.98 6.79 6.79 5.90 5.90 5.22 5.22 4.69 4.25
15% Growth
Retention time 2.0 2.7 3.5 4.4 5.5 6.8 8.2 9.8 11.7 13.7 16.0 18.5 21.3 24.4 27.7 31.3
Yield factor - - - - - 7.98 7.98 7.98 6.79 6.79 5.90 5.90 5.22 5.22 4.69 4.25
15% Growth
Retention time 3.4 4.5 5.9 7.5 9.4 11.5 14.0 16.8 19.9 23.4 27.3 31.7 36.4 41.6 47.3 53.4
Yield factor - - - 7.98 7.98 6.79 6.79 5.90 5.90 5.22 4.69 4.25 3.88 3.58 3.32 3.09
Produced Biogas
In Figure A.5.8 and Figure A.5.9 the results for both the hemisphere and chinese design are presented. The
green line is the new amount of biogas that has to be reached to cover the cooking demand of the AETCR.
No larger differences between the new produced biogas and the produced biogas in the MIT sub-scenario
can be seen for either 5% and 10% increase of population.
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Figure A.5.8: Produced biogas, PGB 5%. Figure A.5.9: Produced biogas, PGB 10%.
In Figure A.5.10 the case of a 15% population increase for the hemisphere design is presented. As for the
two other cases no larger changes could be seen.
Figure A.5.10: Produced biogas, PGB 15%,
hemisphere design.
Economical
The economical part for the hemisphere design of the PGB sub-scenario is presented below. In Figure
A.5.11 the different increases of population are shown for the construction year, while Figure A.5.12
displays the savings for the remaining years of all cases.
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Figure A.5.11: Savings for the construction year,
PGB, hemisphere designFigure A.5.12: Savings after the firts year,
PGB, hemisphere design
In Figure A.5.13 the NPC increases due to the different cases that are presented for the hemisphere design.
Figure A.5.13: NPC for the project lifetime,
PGB, hemisphere design
Environmental
The CO2 emissions for both the hemisphere and chinese design for both a 5% and a 10% population
growth are presented in the figures below. In Figure A.5.14 the result for the 5% increase are presented,
while Figure A.5.15 shows the results for the 10% increase of population.
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Figure A.5.14: Reduction of CO2 emissions, PGB 5%. Figure A.5.15: Reduction of CO2 emissions, PGB 10%.
Calculations of the CO2 emissions for the hemisphere design with a 15% population increase was also
performed and the results can be seen in Figure A.5.16.
Figure A.5.16: Reduction of CO2 emissions, PGB 15%,
hemisphere design.
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TRITA -ITM-EX 2021:186
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