Annual Urban Energy Flows in Santa Cruz, Bolivia

HafenCity Universität Hamburg

M. Sc. Resource Efficiency in Architecture and Planning (REAP)

Urban Energy Flows

Summer Semester 2015

Final Report

An analysis of the annual energy demand of

Santa Cruz, Bolivia

Submitted to: Professor Hannes Schafers

On: Sunday, October 11th, 2015

Contributing Authors

Bilgici, Setenay: 6012063

Callaú, Paula: 6028741

Tewari, Babita: 6028946

Troutman, Heather: 6028601

Urban Energy Flows: Santa Cruz, Bolivia 2

Figure 1: World Map (NASA, 2002).


1. Table of Contents

1. Introduction .................................................................................................................................. 6

2. Bolivia ............................................................................................................................................ 8 2.1. Santa Cruz .................................................................................................................................. 8

2.1.1. Current Energy Situation ....................................................................................................... 9 2.1.2. Santa Cruz de la Sierra ........................................................................................................ 10 2.1.3. District Number 2 ................................................................................................................ 11 2.1.4. Climate ................................................................................................................................. 12

2.1.4.1. Geographical Location ............................................................................................................. 12

2.1.4.2. Temperature, Precipitation and Humidity ................................................................................ 12

2.1.4.3. Wind ......................................................................................................................................... 13

2.1.4.4. Solar Radiation ......................................................................................................................... 14 2.2. Architecture .............................................................................................................................. 14

2.2.5. Passive Design Concepts for Warm and Humid Climates ................................................... 14 2.2.6. Traditional Architecture ...................................................................................................... 16 2.2.7. Modern Architecture ............................................................................................................ 17 2.2.8. Material Properties ............................................................................................................. 18

2.2.8.1. Traditional Residential Architecture ........................................................................................ 18

2.2.8.1. Modern Residential Architecture ............................................................................................. 18

2.2.8.2. Modern Multi story Residential Architecture ........................................................................... 18

2.2.8.3. Commercial and Industrial Buildings ....................................................................................... 18

2.2.8.4. Eduactioaln and Health Buildings ............................................................................................ 18

3. Electricity Demand ..................................................................................................................... 19 3.1. Residential Buildings ............................................................................................................... 19 3.2. Commercial Buildings Electricity Demand ............................................................................. 20 3.3. Commercial Building Cooling Demand ................................................................................... 24 3.4. Industrial Buildings .................................................................................................................. 24

4. Traffic-Related Energy Demand ............................................................................................... 24 4.1. Existing Infrastructure and Trends ........................................................................................... 24 4.1. Fuel Consumption .................................................................................................................... 25 4.2. Environmental Impact .............................................................................................................. 27

5. Total Energy Demand of Current System and Sankey Diagram of the System ................... 28

6. Proposed Renewable Energy Technology System ................................................................... 30 6.1. Energy Efficiency .................................................................................................................... 30

6.1.1. Traffic .................................................................................................................................. 30 6.1.1.1. Sustainable Urban Planning: .................................................................................................... 30

6.1.1.2. Developing Public Transit: ....................................................................................................... 30

6.1.1.3. Improving the technology of the vehicles and choosing less polluting fuel: ............................ 31 6.1.2. Non-Residential Buildings ................................................................................................... 31

6.2. PV ............................................................................................................................................ 34 6.2.3. Potential ............................................................................................................................... 34 6.2.4. Dimensions of Needed System ............................................................................................. 35 6.2.5. Distribution Grid ................................................................................................................. 35 6.2.6. Energy Amortization ............................................................................................................ 36

6.3. Wind ......................................................................................................................................... 37 6.3.7. Potential ............................................................................................................................... 37

7. Conclusions and Recommendations ......................................................................................... 40


Figures

Figure 1: World Map (NASA, 2002). ..................................................................................................... 2 Figure 2: South America (Pape, 2002). ................................................................................................... 8 Figure 3: Map of Bolivia. Source: Authors. ............................................................................................ 8 Figure 4: Night View of Santa Cruz de La Sierra (Aosinagag, 2014). ................................................... 9 Figure 5: Aerial view from Santa Cruz de la Sierra, n.d.: ..................................................................... 10 Figure 6: District N°2 (Andes Amazonia, 2015) ................................................................................... 11 Figure 7: Temperatures in Bolivia (°C) ................................................................................................ 12 Figure 8: Precipitation in Bolivia (mm) ................................................................................................ 12 Figure 9: Weather Data of Santa Cruz de la Sierra SENAMHI (2015). ............................................... 13 Figure 10: Map of the mean wind velocity of Santa Cruz de la Sierra in m/s. (Ministerio de

Hidrocarburos y Energias, 2014). ......................................................................................................... 13 Figure 11: Map of Mean Solar Radiation in Santa Cruz de la Sierra .................................................... 14 Figure 12: Traditional Architecture. Source: Authors........................................................................... 16 Figure 13: Images of traditional architecture showing the galleries and small openings. Source:

Authors .................................................................................................................................................. 16 Figure 14: Modern Architecture with Passive Concepts. Source: Authors ........................................... 17 Figure 15: Images of the Modern house showing north façade with its galleries and big openings with

controlled sunlight. Source: Authors ..................................................................................................... 17 Figure 16: Residential Energy end-use splits in the USA. Source: Authors with data provided by

(USDE, 2011) ........................................................................................................................................ 19 Figure 17: Residential Energy end-use splits corrected for District No. 2. Source: Authors with data

provided by (USDE, 2011) ................................................................................................................... 19 Figure 18: Distribution of total commercial floor area by use (m²). Source: Authors .......................... 20 Figure 19: Distribution of energy intensity by sector and utility (kBtu/sqft*a) Source: Authors with

data provided by (USDE, 2011) ............................................................................................................ 21 Figure 20: Distribution of energy intensity by utility and sector (kBtu/sqft*a) Source: Authors with

data provided by (USDE, 2011) ............................................................................................................ 21 Figure 21: Total end use of energy in the commercial sector (GWh/a) Source: Authors .................... 23 Figure 22: Final energy use (GWh/a) of the commercial sector by utility and sector Source: Authors

............................................................................................................................................................... 23 Figure 23: No. of vehicles registered in District No.2. Source: Authors with data from (INE, 2009) .. 25 Figure 24: Extrapolation of the number. of vehicles registered in District No.2 to the year 2015

Source: Authors with data from (INE, 2009) ........................................................................................ 25 Figure 25: Distribution of vehicles by type. Source: Author’s with data from (INE, 2009). ................ 26 Figure 26: Distribution of vehicles by year. Source: Author’s with data from (INE, 2009). ................ 26 Figure 27: Distribution of vehicle fuel types in SC .............................................................................. 27 Figure 28: Sankey Diagram of the current energy system of District No2 ........................................... 29 Figure 29: Shading technologies (EWC, 2013) .................................................................................... 34 Figure 30: Direct Normal Irradiance (DNI) for each month in Santa Cruz, Bolivia Source: (OpenEI,

2015) ..................................................................................................................................................... 34 Figure 31: Direct Normal Irradiance (DNI) for Santa Cruz, Bolivia, Source: (NREL, 2015) .............. 34 Figure 32: Total Electricity Generation in Bolivia, 2012Source: (CIF, 2015) ...................................... 36 Figure 33: Total Energy Consumption in Bolivia, 2011. Source: (EIA, 2015) (EoE, 2008) ................ 36 Figure 34: Map of National Grid and isolated Power Lines in Bolivia. Source: (CNDC, 2008) .......... 36 Figure 35: Global Solar Potential in kWh/m²/a , Source: (Fraunhofer, 2015) ...................................... 37 Figure 36: Cp vs λ curve for wind turbine (with EA3) Source (The Royal Academy of Engineering,

2015) ..................................................................................................................................................... 39 Figure 37: Comparison of energy consumption rates of District No2 with the World ......................... 40


Tables

Table 1 Primary and Secondary Energy Consumption in the Department of Santa Cruz (Ministerio de

Hidrocarburos y Energía, 2010). *Barrel of Oil Equivalent ................................................................... 9 Table 2: Population Growth (INE, 2012) .............................................................................................. 10 Table 3: District N°2 of Santa Cruz de la Sierra. .................................................................................. 11 Table 4: Weather Data of Santa Cruz de la Sierra. SENAMHI (2015). ................................................ 13 Table 5: Solar radiation for Santa Cruz de la Sierra (Birhuett Garcia, 2009). ...................................... 14 Table 6: Material properties for a traditional residential building. ....................................................... 18 Table 7: Material properties for a modern residential building with passive cooling concepts. ........... 18 Table 8: Material properties for a modern multi story building without passive cooling concepts. ..... 18 Table 9: Material properties for modern commercial and industrial buildings without passive cooling

concepts. ................................................................................................................................................ 18 Table 10: Material properties for modern educational and health buildings without passive cooling

concepts. ................................................................................................................................................ 18 Table 11: Total Energy consumption in Residential Building Sector. Source: Authors with data

provided by (USDE, 2011) ................................................................................................................... 20 Table 12: Calculated total energy use in the commercial sector in 2015 .............................................. 21 Table 13: Commercial building energy intensity by sector and utility (kBtu/sqft*a). Source: (USDE,

2011) ..................................................................................................................................................... 22 Table 14: Calculated cooling demand for commercial sector Source: Authors, with data by (USDE,

2011) ..................................................................................................................................................... 24 Table 15: Variable calculated cooling demand for residential sector Source: Authors with data

modified from (USDE, 2011) ............................................................................................................... 24 Table 16: Annual energy demand for traffic sector in District No.2 in 2015 Source: Authors ........... 27 Table 17: CO2 eq emissions from the transportation sector in District No. 2 in 2015 ......................... 28 Table 18: Windows Types Used in Energy Calculations (EWC, 2013) ............................................... 33 Table 19: Formulas used for calculating the solar potential and calculation for the proposed system for

Santa Cruz, Sources: (Wholesale Solar, 2015) (Weatherbase, 2015). .................................................. 35 Table 20: Formulas used for calculating the solar potential and calculation for the proposed system for

Santa Cruz, Sources: (Wholesale Solar, 2015) (Weatherbase, 2015). .................................................. 35 Table 21: Electricity supply of the country and the city of Santa Cruz. Source (CIF, 2015). ............... 36 Table 22: Formulas for energy amortization. Sources: (Wholesale Solar, 2015) (Weatherbase, 2015).

............................................................................................................................................................... 37 Table 23: Calculation for energy amortization. Sources: (Wholesale Solar, 2015) (Weatherbase, 2015).

............................................................................................................................................................... 37 Table 24: Formulas ............................................................................................................................... 38 Table 25: Calculation of proposed system in regard to wind energy for the city of Santa Cruz........... 39


1. Introduction

The population in cities has been dramatically increasing since the industrial revolution. The

urban population rate has showed an important increase between the years 1960 and 2014 from 34% to

54% of the total global population. Yet, it will continue to increase as long as the related strategies will

remain constant (WHO, 2015).

Urbanization has always meant development, and energy has been a major factor for

development. Therefore cities consume the bigger share in energy consumption in the world with the

average 75 % of global primary energy and 80 % of world`s total greenhouse gasses. Cities need energy

to run their activities by supplying raw materials, continuing construction processes and maintaining

daily needs. The main activities requiring energy in cities are transport, communication, industrial and

commercial activities, buildings and infrastructure, water distribution and food production. Buildings

by themselves also require significant amount of energy for supplying of the raw materials, construction

processes and maintenance, and also the daily needs such as cooling/heating, lighting and cleaning (UN-

Habitat, n.d.).

By the increasing concern in world`s limited resources, environmental and climate change

awareness have risen in the world in the last decades. That has led to the development of more

sustainable approaches for urban energy systems. Strategies for sustainable urban energy systems have

being developing on two sides: low carbon technologies on the supply side and energy efficiently

distributed infrastructure as well as decreased consumption on the end-user side (UN-Habitat, n.d.). In

order to implement sustainable urban energy systems in a city, the energy consumption pattern of the

city should be understood properly since every single city has different patterns of energy consumption

based on their economy, location, climate, and culture. That will help to see the possible and most

effective areas for energy efficiency in the city as indicated by ESMAP (Energy Sector Management

Assistance Program):

“For cities that want to take concrete actions on improving energy efficiency, it is essential to

understand what, where, and how big the potential energy-saving opportunities are, what measures are

needed to capture the savings and at what costs, what the implementation constraints are, and how

priorities should be set given local capacity and resources. An energy efficiency assessment can provide

the necessary clarity on these issues.” (ESMAP, 2014)

Energy planning urban areas should be adopted at all scales of the urban areas: in single buildings,

neighbourhoods, municipalities, cities and territories (EIFER, 2011). This paper will conduct a study in

a district (District Number 2) with a population of 100.000 inhabitants in Santa Cruz, Bolivia. First of

all, a detailed background information will be supplied regarding the climate, architecture and current

energy situation of Santa Cruz and more specifically of District Number 2. Based on that information,

the annual energy demand of the district will be calculated considering the cooling demand, electricity


demand and transportation-related fuel demand. Total energy demand will be interpreted into

atmospheric greenhouse has (GHG) emissions related with Santa Cruz`s current energy and fuel

demand. At the second phase of the paper, alternative strategies which are suitable for Santa Cruz

regarding its background information will be presented for implementing sustainable urban energy

systems in District Number 2.


2. Bolivia

Bolivia is said to be the heart of South America. It is the

landlocked country that occupies the center of the continent and

shares borders with Brazil on the north and east, Paraguay and

Argentina on the south, and Chile and Perú on the west.

It has an area of 1,098,581 km² which go from the cold,

high mountainous region of the Andes Mountains in the east, to

the tropical lowlands with less than 500m over sea level of the

Amazon Basin in the west (Salamanca Mazuelo, 2008).

Bolivia is divided into 9 departments. Statistics provided

by the INE (2012) reveal that it has a population of 10,027,254

inhabitants. More than two thirds of the population is

concentrated between its three major urban centers which

include the cities of La Paz with 2,706,351, Santa Cruz with 2,655,084 and Cochabamba with 1,758,143

inhabitants. Bolivia’s economic, social and urban development is concentrated in these three cities. This

causes migration flows from the rural areas as well as from less prosperous departments into these cities.

The most affected city by this constant migration today is Santa Cruz de la Sierra, which in the last few

decades has also experienced the migration from people of the western region and also from neighboring

countries.

According to Urquiola (1999) the distribution of the

population of Bolivia has changed drastically since the

1950’s. Historically, the greater portion of the population

was concentrated on the eastern Andean region. However,

since the 1950’s there has been a demographic change with

this population being reduced, and the population from the

lowland areas being dramatically increased. He argues that

population shifts of such magnitude are likely to be

associated with changes of the location of economic

activity, which in Bolivia was shifted from a historical

mining based economy to an agricultural based economy

beginning in the 1950s, In addition to this, the country has

experienced a growth in the petroleum industry, and even though most of the resources are not located

in the city of Santa Cruz, they have contributed to its growth by locating the industry’s headquarters

there.

2.1. Santa Cruz

Figure 2: South America (Pape, 2002).

Figure 3: Map of Bolivia. Source: Authors.


Santa Cruz is the biggest department of Bolivia. It is located in the east side of the country in the

warm sub tropical lowlands and has excellent climatic conditions and topography to develop farming

and agriculture during the whole year which has led to its rapid growth and development in the last 65

years. This part of the country has developed modern agriculture by using techniques which allow the

production to cover not only national needs but also international market, in contrast to the western part

of the country, which is still using traditional agriculture (Montes de Oca, 1995).

2.1.1. Current Energy Situation

Four different sources provide the primary energy in Bolivia; natural gas in a 79.6%, condensed

petroleum or natural gasoline in a 13.5%, biomass in a 5.6% and hydro energy in a1.2% (Ministerio de

Hidrocarburos y Energía, 2010). In Table 1 a detail of the consumption of energy in the Department of

Santa Cruz is shown.

Primary Energy

Consumption in kboe*

Secondary Energy Consumption

in kboe*

Total Energy

Consumption in kboe*

Transport 1,152.05 4,183.02 5,335.07

Industry 2,350.40 708.11 3,058.51

Residential 373.24 1,351.86 1,725.10

Commercial and Administrative 53.52 360.35 413.87

Agriculture 0.00 1,355.13 1,355.13

Total Energy Consumption 3,929.21 7,9568.41 11,887.68

Table 1 Primary and Secondary Energy Consumption in the Department of Santa Cruz (Ministerio de Hidrocarburos y

Energía, 2010). *Barrel of Oil Equivalent

The provision of primary energy in the Department of Santa Cruz is done in 23% by Petroleum

and Gasoline, 50% by natural gas, and the remaining 27% by biomass. Santa Cruz is the department

with largest biomass energy production of the country. The provision of secondary energy is done in

13% by electricity, 12% by natural gas, 22% by diesel oil, 23% by gasoline and 30% by others

(Ministerio de Hidrocarburos y Energía, 2010).

In the end of the year 2014 there have been improvements in terms of energy generated by

renewable resources such as wind

power and photovoltaic plants, but there

are still no studies that reveal how the

energy consumption and provision has

been affected by them.

Figure 4: Night View of Santa Cruz de La Sierra

(Aosinagag, 2014).


2.1.2. Santa Cruz de la Sierra

Santa Cruz the la Sierra is the capital of the department of Santa Cruz. It was a small city with a

small population since its beginnings in the 1560’s. It experienced slow demographic changes due to its

rather low economic activity and the lack of communication with the rest of the country. However in

the 1950s, the city started to experience quick changes. The construction in 1952 of the road that

connected it to the rest of the cities and to the mining crisis in the eastern part of the country due to

international fall of prices lead to the development of what would become a rising agricultural economy

for the country. This lead to quick demographic changes shown In Table 2, that lead to an unorganized

and uncontrolled urban development. Figure 5 shows the development of the city on the west lowlands,

since the Piray River in the east was a barrier for its growth in this direction.

Table 2: Population Growth (INE, 2012)

The first urban plan from 1959 was organized around four concentric rings with radial avenues

The basic unit of design was the Neighbourhood Unity which aimed to be residential and should fulfill

70% of the residents’ basic needs within the area. The plan encouraged the use of private automobiles

and practically had no consideration for pedestrians, since according to it; all their needs would be

satisfied within their neighborhood. The first ring hosts the old part of town, while the second and third

were designed for new residential areas. Between the third and fourth ring, there was an area meant to

provide infrastructure for the community including education, health, culture, sports, religion and

leisure. Beyond the forth ring the non heavy industry had its place while the heavy industry was meant

to be after the fifth ring. Unfortunately the plan expected a population growth for the next 20 years that

was quickly surpassed, reaching by the

end of the century a population of over

2,000,000 inhabitants. This resulted in

an uncontrolled growth, surpassing the

urban plane, with a disorganized

occupation with low density in the

surrounding area (MMAyA, 2012).

Figure 5: Aerial view from Santa Cruz de la Sierra, n.d.:


2.1.3. District Number 2

The city of Santa Cruz de la Sierra is

divided into 12 districts. District N°2,

marked in dark Green in Figure 6, has

been chosen as the area of analysis for this

report. It has a population of 101,598

inhabitants and an area of 936h. There are

25,481 homes combined with educational

and health facilities as well as commercial,

cultural and recreational infrastructure.

Water provision and sewage systems cover

the entire area as well as energy supply

(Fundación PAP, 2002).

According to Bazzaco (2009), District

N°2 is one the wealthiest of the city. It shows

life expectancy, educational levels and social indicators highly superior compared to the other districts.

Unfortunately Bolivia is a country with enormous inequities, therefore the results of this calculations

will not entirely represent the reality of the whole city.

For the effects of having simple numbers for the calculations required in this analysis, the number

of population has been slightly altered and simplified as shown in the Table 3 as has the number of

residences in the district. The m² corresponding to commerce, education, health and industry

infrastructure has been estimated according to measurements and knowledge of the area.

Distric 2 Levels Popultaion Inhab/unit Units Homes m²/unit m²

Residential Modern 2 90,000 4 22,500 22,500 228 5,130,000

Residential Traditional 1 5,000 10 500 500 871 435,500

Residential Multistorey 10 5,000 200 25 1,000 468 11,700

Commercial 2 370,000

Education 2 125,000

Health 2 165,000

Industry 2 115,000

Total Population 100,000

Total Homes 24,000

Total m² Built 6,352,200

Total m² 9,360,000

Table 3: District N°2 of Santa Cruz de la Sierra.

Figure 6: District N°2 (Andes Amazonia, 2015)


2.1.4. Climate

2.1.4.1. Geographical Location

Santa Cruz de la Sierra is located between the tropical humid north lowlands of the northwest and

the tropical dry lowlands of the southwest and has a warm humid climate with intense winds all year

round. The city is located at 416m over sea level and its coordinates are 17°47’00 S 63°10’00 O. The

annual precipitation is around 1200 mm³ and the mean humidity is 71% (SENAMHI ,2015).

Even though Bolivia should have a tropical climate due to its latitude, the pronounced variation

of altitude from east to west cause climatic variations which change from cold and dry polar climate in

the Altiplano Region of the Andes Mountains to the tropical climate of the lowlands in the east.

According to Montes de Oca (2005), the various climatic conditions that are found in Bolivia are caused

by the combination of many factors that affect the temperature, precipitation, humidity, wind,

evaporation and atmospheric pressure such as its close position to the tropic of Capricorn, its latitude

and longitude, its variable altitude, the existence of the Andes Mountains in the east and the lowlands

in the west, and the winds coming from south and northeast. Urquiola (1999) argues however, that the

main factor which defines these different climates is its altitude variation, with a maximum of 6.500m

over sea level in the east to a minimum of 90m in the west.

2.1.4.2. Temperature, Precipitation and Humidity

The following Figure 7 and Figure 8 show the mean temperature in Bolivia (°C) and the annual

precipitation in the entire region (mm). In both figures the city of Santa Cruz de la Sierra is represented

with a white dot.

Figure 7: Temperatures in Bolivia (°C)

Mapa Temperaturas Bolivia, n.d.

Figure 8: Precipitation in Bolivia (mm)

Mapa Lluvias Bolivia, n.d.


Data provided by SENAMHI (2015) which is displayed in Table 4 and Figure 9 shows the

weather data for the city including monthly precipitation (mm), humidity (%) and temperature values

(°C). Even though the medium temperature of the city is of 24°C, it has a warm and humid climate with

a mean maximum temperature of 29°C in summer and minimum of 18°C in the short winters.

Table 4: Weather Data of Santa Cruz de la Sierra. SENAMHI (2015).

Figure 9: Weather Data of Santa Cruz de la Sierra SENAMHI (2015).

2.1.4.3. Wind

The information provided by the Ministerio de

Hidrocarburos y Energías (2014) states that Santa Cruz de

la Sierra has an annual mean wind velocity of 4.0 to 4.5

m/s with 225 W/m². It argues that with these values, the

city and the entire department has a great potential for

wind energy generation. Figure 10 shows the map with

the wind velocity classification for the entire country,

represented with a white dot is the city of Santa Cruz de

la Sierra.

During autumn and winter, polar winds rise from

the Pacific canalized by the Andes Mountains until they

reach Bolivia. This cold and heavy polar air, known as

“surazo”, crushes with the tropical warm air found in the

lowlands generating a sudden change in temperature which may reach a temperature variation of 10°

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11 12

Tem

per

atu

re

Pre

cip

itat

ion

Months

Precipitation (mm³)

Temperature (Max.) °C

Temperature (Mean) °C

Temperature (Min.) °C

Figure 10: Map of the mean wind velocity of Santa

Cruz de la Sierra in m/s. (Ministerio de

Hidrocarburos y Energias, 2014).


from one day to the other causing precipitation and 10 to 20 days of winter weather. In summer the

predominant and constant warm winds with humid air coming from the Amazon region generate a lot

of rainfall (Montes de Oca, 1995).

2.1.4.4. Solar Radiation

The information provided by ENERGETICA

(2010) provided information regarding the solar radiation

in the entire country. In Figure 11 the mean solar

radiation values per day are shown in the entire country.

Represented with a white dot, Santa Cruz de la Sierra has

between 4.5 and 5.1 kwh/m² per day.

According to the Ministerio de Hidrocarburos y

Energías (2014), Santa Cruz has potential for solar

energy generation, but not as much as the east part of the

country which enjoys of much higher values.

The Table 5 shows the solar radiation values for

the city of Santa Cruz de la Sierra as well as the hours of

sun and sunlight.

Table 5: Solar radiation for Santa Cruz de la Sierra (Birhuett Garcia, 2009).

2.2. Architecture

2.2.5. Passive Design Concepts for Warm and Humid Climates

There are several factors that must be taken into consideration when designing a passive cooling

construction for warm and humid climates such as the one found in Santa Cruz de la Sierra. In these

climates, the difference in temperature between day and night is almost insignificant compared to warm

dry climates, where thermal mass is a good solution to address this issue. Szokolay (2008) argues that

in this context, the main goal is to avoid getting the inside air hotter than the outside air specially by

addressing internal and external heat gains.

The combination of heat and humidity causes the evaporation from the skin to be restricted. To

solve this and gain thermal comfort, an effective crossed ventilation must be achieved to guarantee air

renovation inside the building. Allowing the air to circulate constantly guarantees fresh air and avoids

Figure 11: Map of Mean Solar Radiation in Santa

Cruz de la Sierra

(ENERGETICA, 2010)


having heat and humidity accumulated in the building. According to Szokolay (2008) the main purpose

of this ventilation is to immediately remove any heat gain that could be produced inside the room that

may increase the inside temperature even more than the outside temperature. This ventilation

nevertheless should never be too accelerated as to be a bother in the everyday activities. To do this, a

longitudinal building can be designed, with a short width in order to be able to have windows in both

sides of the rooms, or inner gardens can be solution for more compact designs.

It is a very important factor for the design of these architecture, to consider the orientation of each

element of the building. Walls facing north are the ones that are subject to more hours of direct sun, but

luckily the sun’s angle in this orientation is pretty high. All the openings in this façade must have

horizontal protection which guarantees that no heat from the sun enters the rooms through the windows.

The walls in this façade should also have protection, to avoid having the sun hitting the surface of the

wall, which eventually will get warm and let the heat go through it. The walls and opening in the south

do not require any protection, since they receive no direct sunlight.

These types of climates are often found close to the equator, which means that the area of the roof

is receiving very strong radiation due to the position of the sun. To avoid heat penetration through the

roof, it should be materialized with thermal insulation materials and an even better solution would be to

have a ventilated double roof or attic. In the case of having a closed attics, the air inside of it, might

eventually get hot, and it is only a matter of time until it makes its way through the ceiling, which by

the way should have adequate thermal insulation, and goes into the building, increasing the inside

temperature.

East and west walls should have the least amount of openings possible to avoid receiving heat

from a low angle sun of the morning and afternoon, and if they do, they should have vertical protection.

These walls should be materialized with thermal insulation and if it is possible, be protected to avid

receiving direct solar radiation. Even though the angle of radiation for the east and west is the same,

special consideration should be taken when designing the west wall. When the afternoon sun radiation

is reaching the building’s wall, the temperature of all the materials is higher since it is the end of the

day, and the whole building is already warm. Whereas in the east wall, with the morning sun, the

temperature ha slightly dropped during the night, and the building is not as warm as it will be in the

afternoon.

Finally, as a precipitation protective element are the galleries. Usually in these climates, it rains

a lot, and it rains nearly every day. For this reason, galleries should cover the greatest amount of area

possible, since it will protect the users as well as the materials of the house, such as windows and doors.

If they are unprotected, rainfall will quickly deteriorate them, and they will need more maintenance.


2.2.6. Traditional Architecture

The first case study presented in this analysis is a

traditional multifamily house shown in Figure 12. These kind of

houses where usually occupied by families of 10 to 15 members.

In the old times, grandparents would usually live in these houses,

with their children and their grandchildren.

The main concept of these buildings was an inner central

garden with a surrounding gallery and surrounding rooms. All

the rooms of the house, which were more or less the same size

and shape would have exterior doors to the gallery which

surrounded the garden. Even though the house could be

circulated through the inside by entering each room, the most

common way of circulating this building typology was by the

surrounding gallery. The common and social activities were held in the gallery due to its cool shadow

and constant natural ventilation.

The rooms usually had small windows, covered by wooden sheds in order to avoid direct sunlight

and heat to go into the rooms. This caused the rooms to be dark and cool, which is another reason why

most of the common activities were done in the exterior galleries.

The garden in the middle, usually had the water supply installation, and was in complete shadow

to avoid the ground, usually made of bricks, getting warm and heating the air warm around the gallery.

Surrounding the house there was also an outside gallery to avoid the sunlight to heat the exterior walls

of the house and penetrating the walls. A lot of social activities happened in this gallery, as the

inhabitants would use this cool and shadowed space to socialize. Both the inside and the outside gallery

also provided protection from the constant rainfall that fell on the city, mainly in the summer.

In Figure 12 a plan of a traditional house is shown. The inner garden has been marked with green

while the galleries are represented in pink. Typically the orientation was not an factor taken into account

in the design , and it this typology would be placed in any direction with respect to the north.

Figure 13: Images of traditional architecture showing the galleries and small openings. Source: Authors

Figure 12: Traditional Architecture.

Source: Authors


2.2.7. Modern Architecture

The second case study presented in this analysis is a family

house built with passive design concepts and modern technology

by the architect Juana Poduje shown in Figure 14. It was build to

shelter her family of six people; her husband and their four

children.

The house was built in two stories, in a rectangular lot, with

the entrance facing the south. Following local regulations, there

house was separated from the municipal line by a 5m deep garden

in the south façade, where the entrance was placed. In the back

part of the house, the north side of the lot a bigger garden was

designed. The public areas of the house were located in the floor

plan, while the private areas were in the upper floor.

The orientation of the rooms was a key factor in the design of the house. The openings made in

the walls were studied according to the angle of the sun at different times of the day to gain the least

possible heat infiltration through them. The walls and windows facing the north were protected by

galleries and eaves. Since the east façade was completely attached to a neighbor’s wall it had no

openings. The west façade was completely exposed to the afternoon sun and therefore was designed

with no windows and constructed twice as thick as the rest of them. The south walls was protected by

galleries and eaves covering most of the windows, but in this case they were protecting them from the

heavy rainfall produced by the “surazo” with strong winds from the south.

All the rooms of the house were designed with crossed ventilation. Since it is a compact design,

rather than a longitudinal one, this was achieved by the two small inner gardens. They provide openings

in each room. This guaranteed each room of the house to have two sets of windows, one in their north

wall, and the other in the south wall.

In Figure 14 a plan of the modern house is shown. The gardens have been marked in green while

the northern and southern galleries are shown.

Figure 15: Images of the Modern house showing north façade with its galleries and big openings with controlled sunlight.

Source: Authors

Figure 14: Modern Architecture with

Passive Concepts. Source: Authors


2.2.8. Material Properties

2.2.8.1. Traditional Residential Architecture

Material Thickness

(mm)

U-Value

(W/m²K) Details

Walls (N,S,E,W) 400 0.00175 380 mm of mud and 20 mm of mud plaster

Ground 50 2.22 50 mm of solid ceramic brick on top of the soil

Roof 100 1.99 50 mm of solid ceramic brick and 50 mm of ceramic tiles

Wooden Doors 25 3.4 25 mm of solid wood

Glass Windows 3 3.54 3 mm of glass*

Table 6: Material properties for a traditional residential building.

*for the effects of the calculations, the windows have been considered as plain glass since their air tightness is almost null.

2.2.8.1. Modern Residential Architecture

Material Thickness

(mm)

U-Value

(W/m²K) Details

Walls (N,S,E) 142 2.81 20mm of ext. plaster, 110mm of solid ceramic brcik, 12mm of int.

plaster

Walls (W) 272 1.83 20mm of ext. plaster, 240mm of solid ceramic brcik, 12mm of int.

plaster

Ground 100 2.42 80 Non Structural Concrete, 20 ceramic floor

Roof and Ceiling 87 1.7 50mm of ceramic tiles, 25mm of wood, 12mm of thermal insulation


Glass Windows 8 3.46 8 mm of templated glass*


Table 7: Material properties for a modern residential building with passive cooling concepts.


2.2.8.2. Modern Multi story Residential Architecture

Material Thickness

(mm)

U-Value

(W/m²K) Details

Walls (N,S,E,W) 142 2.81 20mm of ext. plaster, 110mm of solid ceramic brcik, 12mm of int.

plaster


Roof 250 0.74 200mm of concrete, 50mm of thermal insulation



Table 8: Material properties for a modern multi story building without passive cooling concepts.


2.2.8.3. Commercial and Industrial Buildings

Material Thickness

(mm)

U-Value

(W/m²K) Details


plaster


Roof 150 2.52 5mm of zink roof, 10mm of thermal insulation



Table 9: Material properties for modern commercial and industrial buildings without passive cooling concepts.


2.2.8.4. Eduactioaln and Health Buildings

Material Thickness

(mm)

U-Value

(W/m²K) Details


plaster


Roof 250 0.74 200mm of concrete, 50mm of thermal insulation




Table 10: Material properties for modern educational and health buildings without passive cooling concepts.



3. Electricity Demand

Detailed information on energy intensities of various building types in Santa Cruz or Bolivia was

not identified for use in this report. Instead, detailed information as provided by the United States

Department of Energy (USDE) (2011) has been modified to reflect expected differences from energy

use in buildings in the US and in Bolivia. The reader should note that District No.2 is one of the

wealthiest areas in all of Bolivia (Bazzaco, 2009). Considering this, the authors have confidence that

utilization of US building data is appropriate with respect to the modifications made in this report.

3.1. Residential Buildings

According to the USDE (2011) single-family and multi-family residential buildings consume 55

kBtu/sqft*a and 70 kBtu/sqft*a, respectively. 54% of delivered energy consumed in residential

buildings in the US is used for space heating and cooling, as shown in Figure 16Figure 16: Residential

Energy end-use splits in the USA. Source: Authors with data provided by (USDE, 2011). All residential

buildings in District No.2 are constructed using passive design strategies and therefore have no energy

consumption related to space heating or cooling. This study has modified the USEIA published values,

as shown in Figure 17.

Figure 16: Residential Energy end-use splits in

the USA. Source: Authors with data provided by

(USDE, 2011)

Figure 17: Residential Energy end-use splits

corrected for District No. 2. Source: Authors

with data provided by (USDE, 2011)

55 𝑘𝐵𝑡𝑢

𝑠𝑞𝑓𝑡∗

1 𝑠𝑞𝑓𝑡

0.092903 𝑠𝑞𝑚∗

0.29307107 𝑘𝑊ℎ

1 𝑘𝐵𝑡𝑢∗ 0.4 𝑐𝑜𝑟𝑟𝑒𝑐𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟 =

70 𝑘𝑊ℎ

𝑠𝑞𝑚

The available energy intensity values have been discounted by 60% — 54% reflecting the absence

of heating and cooling demand and an additional 6% reflecting more conservative living patterns in

Santa Cruz than in the US with the quantity and size of electronics, especially large, energy intensive

equipment such as washing machines and refrigerators. This study assumes an average energy intensity

of 70 kWh/sqm and 88 kWh/sqm in single-family and multi-family residential buildings, respectively.


Total electricity demand for residential buildings in District No.2 is expected to be 390 GWh per year,

as shown in Table 11.

District N°2 m² kWh/m²*a GWh/a

Single-Family Residential 5,565,500 70 389.59

Multi-Family Residential 11,700 88 1.03

Total 5,577,200 - 390.64

Table 11: Total Energy consumption in Residential Building Sector. Source: Authors with data provided by (USDE, 2011)

In comparison, data published by the Ministerio de Hidrocarburos y Energía (2010), estimates

that 319 GWh were consumed in District No.2 in the year 2010, after being adjusted for population.

The results of this study are 22.5% higher than the published values. There was a 5.5% annual increase

in energy consumption in the residential sector in Santa Cruz from 2005-2010 (MHE, 2010). Assuming

this trend persists consistently through 2015, then expected energy consumption in the residential sector,

adjusted for population, is expected to be 407 GWh in District No.2; or, 4% greater than this study’s

calculated value. Considering the uncertainty of these estimations, this report is confident that

approximately 390 GWh of energy will be consumed in the residential building sector in District No.2

in 2015.

The authors acknowledge that this calculation can be improved with more accurate information

on energy intensity in the residential sector in Bolivia.

3.2. Commercial Buildings Electricity

Demand

This study has divided non-residential

buildings into two broad categories: commercial

and industrial.

Commercial buildings have been further

sub-divided into 11 categories, office, retail,

shopping malls, lodging, service, civic,

religious, grocers, restaurants, educational and

health reflecting great variance in building use

and associated energy intensity, as shown in

Figure 18 and Figure 19. Again, energy intensity data was taken from the USDE (2011) and modified

to reflect conditions in District No.2. This data is presented in Table 12.

Figure 18: Distribution of total commercial floor area by use

(m²). Source: Authors


Figure 19: Distribution of energy intensity by sector and utility (kBtu/sqft*a) Source: Authors with data provided by (USDE,

2011)

Figure 20: Distribution of energy intensity by utility and sector (kBtu/sqft*a) Source: Authors with data provided by (USDE,

2011)

The total calculated energy consumption for commercial buildings is 135.9 GWh/a, as shown in

Table 12. This is 535% higher than the value published by the Ministerio de Hidrocarburos y Energía,

25.4 GWh/a in 2010, as adjusted for the population of District No.2. Assuming that the average annual

energy use increase of 5.5% previously

discussed is consistent across all sectors,

this study has extrapolated the 2010 data

published by the Ministerio de

Hidrocarburos y Energía to 2015 to be

33.2 GWh/a, or 24.4% of this study’s

calculated value.

Table 12: Calculated total energy use in the commercial sector in 2015


The energy intensity values presented in Table 12 reflect published data for commercial buildings

in the US as provided by USDE (2011). The values were discounted by the published energy intensity

values for heating and cooling respective for each sector, as published in Table 13. The sectors

highlighted in blue have been used to calculate the commercial cooling demand in Section 3.3, below.

Table 13: Commercial building energy intensity by sector and utility (kBtu/sqft*a). Source: (USDE, 2011)

Again, considering that District No.2 is one of the wealthiest areas of all Santa Cruz and Bolivia

(Bazzaco, 2009) this study expects a higher concentration of commercial activity and associated energy

use in District No.2 than is proportionally expected from normalizing statistical data from Santa Cruz’s

2,655,804 population to District No.2’s population of 100,000. However, the calculated value is

suspiciously high.


In attempt to understand this discrepancy,

energy intensities by sectors were applied to the

total built area of the associated sectors to visualize

where the end use energy is being consumed. The

health sector occupies 25% of the total built area

in District No.2, or 165,000 sqm of a total

660,000sqm of built space; yet, is projected to

consume 40% of the total end use energy in the

commercial sector due to the expected energy

intensive activities required in a hospital.

When the calculated energy demand of health facilities is disregarded, the total annual energy

consumption in the commercial sector of District No.2 drops to 82.1 GWh/a, or 247% of the 2015

extrapolated value (33.2 GWh/a) of the Ministerio de Hidrocarburos y Energía published value for 2010

(25.4 GWh/a). While this is still greatly incongruous with the expected value, this study has confidence

that the actual annual energy demand of the commercial sector in District No.2 in 2015 is closer to the

estimated value of 135.9 GWh/a than the extrapolated value.

Figure 22: Final energy use (GWh/a) of the commercial sector by utility and sector Source: Authors

Figure 21: Total end use of energy in the commercial sector

(GWh/a) Source: Authors


3.3. Commercial Building Cooling Demand

Artificial cooling units are uncommon in Bolivia. Temperatures are consistently comfortable

throughout the year — especially for the residents, whom are acclimated to temperatures considered

“hot” in cooler, northern climates. Maximum daily temperatures rarely exceed 30°C, as shown in Figure

9. Because of the passive design strategies discussed in Section 2.2, ambient temperatures stay below

25°C.

This study assumes that only four of the 11 sub-divisions of the commercial sector use air

conditioning units: retail, shopping malls, lodging and health care. Using the discounted values

discussed in Section 3.2, this study calculates that 11.07 GWh/a are consumed for cooling buildings in

these four sectors, as shown in Table 14. If all buildings in the commercial sector used air conditioning

this calculated value would more than double to 20.7 GWh7a, as shown in Table 15.

3.4. Industrial Buildings

Calculation of the energy demand for the industrial sector in District No.2 followed the same

methodology applied in the residential and commercial sector. An energy intensity of 500 kWh/a

(USDE, 2011) was applied to a total built area of 115,00 sqm resulting in an annual energy consumption

of 181.4 GWh/a. This is 96.71% of the extrapolated value of the published Ministerio de Hidrocarburos

y Energía data, 187.6 GWh/a. This study finds this result applicable.

4. Traffic-Related Energy Demand

4.1. Existing Infrastructure and Trends

According to the most recent traffic study made available by the National Institution of Statistics,

Instituto Nacional De Estadística (2009), there were 273,785 registered vehicles in Santa Cruz in 2009.

For the purposes of this analysis, the value has been normalized by population to reflect 10,311

registered vehicles in District No. 2 in 2009. Between 2001 and 2009 the data shows an average annual

Table 14: Calculated cooling demand for commercial sector

Source: Authors, with data by (USDE, 2011)

Table 15: Variable calculated cooling demand for

residential sector Source: Authors with data modified

from (USDE, 2011)


growth rate of 10% per year, as represented in Figure 5.1. Data from 1999 and 2000 have been omitted

from the calculation of average annual growth rate because these years experienced substantially higher

growth rates than the other years under study – 187% and 40%, respectively.

Figure 23: No. of vehicles registered in District No.2. Source: Authors with data from (INE, 2009)

The data provided by Instituto Nacional De Estadística (2009) has been extrapolated to the year

2015 using a static annual growth rate of 10% in Figure 24. The values in a lighter shade of orange

represent the growth from the previous year. This calculation suggests that the number of registered

vehicles in District No.2 has grown by 77% from 10,311 in 2009 to 18,266 vehicles in 2015.

Figure 24: Extrapolation of the number. of vehicles registered in District No.2 to the year 2015 Source: Authors with data

from (INE, 2009)

4.1. Fuel Consumption

At the time of the traffic study, 59% of the registered vehicles in Santa Cruz were lightweight

passenger cars (22%) and combi vehicles, such as station wagons (37%). Only 12% of the registered

vehicles were highly inefficient freight trucks (11%) and large, city buses (1%). The remaining 22%

were medium efficiency light trucks (10%), sports utility vehicles (5%) and small delivery vehicles

(7%), as shown in Figure 25


Figure 25: Distribution of vehicles by type. Source: Author’s

with data from (INE, 2009).

Figure 26: Distribution of vehicles by year. Source:

Author’s with data from (INE, 2009).

The vast majority, 50%, of the vehicles registered in Santa Cruz in 2009 were 10-20 years old,

having been manufactured between the years 1991-2000. 26% of the vehicles were manufactured

between 1981 and 1990, and only 14% of the vehicles had been manufactured in the nine years prior to

the study, as represented in Figure 26. The age distribution of the vehicles suggests that District No.2’s

fleet is not operating at maximum fuel efficiency, but can be expected to be performing relatively high

as less than 11% of the total fleet was older than 30 years.

One can logically expect that new additions to District No.2’s fleet between 2009 and 2015 will

follow a similar vehicle type distribution as represented in the 2009 traffic study. This assumption,

however, may not hold true for the age distribution. Understanding the likelihood of error by making

such an assumption, this study has attributed general fuel efficiency values, represented in miles per

gallon (MPG), to vehicle types in attempt to average variance in fuel efficiency between vehicle ages

evenly across a particular vehicle category. This assumption suggests that age distribution is uniform

across vehicle types.

In the absence of detailed information on average annual distance traveled by vehicle type in

Bolivia or South America, this study has used standard vehicle parameters as made available by the

United States Department of Energy (USDE) (2015). To calculate the annual energy demand for the

transportation sector in 2015, this study has assigned average fuel efficiencies to vehicle types and

average vehicle miles traveled, as provided by the USDE, to the number of vehicles per vehicle category,

as provided by the Instituto Nacional De Estadística’s 2009 traffic study, shown in Table 16.

This calculation was repeated with the data provided for 2009 and compared with fuel

consumption in 2009 in the traffic sector as published by Ministerio de Hidrocarburos y Energía. (2010).

202,711 boe/2009 were calculated compared to 200,938 boe/2009 as published by Ministerio de

Hidrocarburos y Energía and normalized for a population of 100,000 in District No.2. The calculated

value is 1% higher than the published value. Provided that all previous assumptions considering the

growth of the vehicle fleet are true, the expected energy demand for the traffic sector in District No.2 in

2015 should be 358,798 boe, or 584.2 GWh. This suggests an increase of 77% in annual energy demand


for the traffic sector between 2009 and 2015. The authors acknowledge that the exact increase in the

number of vehicles in District No.2 and the age and type distribution is not likely to have been as simple

and uniform in reality as suggested by this analysis. Considering this, we expect that the calculated

value is representative of the actual situation.

Vehicle Type No. of Vehicles MPGeq1 M/a Geq/a boe/a2 kWh/a3

Car 3,982 24 11,000 1,825,120 43,455 70,195,015

Truck 1,969 7 20,000 5,626,177 133,955 218,105,812

4 by 4 1,847 17 12,000 1,303,672 31,040 50,105,812

Van 33 11 11,000 32,850 782 1,273,471

Jeep 965 22 15,00 658,233 15,672 25,517,492

Microbus 374 17 13,000 286,091 6,812 11,090,789

Minibus 1,042 12 14,000 1,215,733 28,946 47,129,924

Motorcycle 1,161 44 3,000 79,137 1,884 3,067,888

Transit Bus 139 7 34,000 673,674 16,040 26,116,100

Combi 6,738 22 11,000 3,368,892 80,212 130,600,703

Total 18,250 -- -- 15,069,519 358,798 584,195,015

Table 16: Annual energy demand for traffic sector in District No.2 in 2015 Source: Authors

1 MPGeq – miles per gallon equivalent – normalized for natural gas and diesel engines

2 boe/a – barrels of oil per year – assumes a standard 42 gallons per barrel of crude oil

3 kWh/a – kilo-Watt hour per year – assumes a standard 1,628.2 kWh per barrel of crude oil

4.2. Environmental Impact

According to the United States Environmental

Protection Agency (USEPA) (2014) “on average, CO2

emissions are 95-99% of the total greenhouse gas

(GHG) emissions from a passenger vehicle, after

accounting for the global warming potential of all

GHGs. The remaining 1-5% is CH4, N2O, and HFC

emissions.” Applying a standard 8,887 grams

CO2/gallon of gasoline burned, 10,180 grams

CO2/gallon of diesel and 6,665 grams CO2/ gallon of

gasoline equivalent of natural gas burned, and assuming that the distribution of total miles driven is

directly proportional to the distribution of vehicles operating on the three fuel types, as provided by the

Instituto Nacional De Estadística (2009) and shown in Figure 27, the total amount of CO2eq emissions

from the transportation sector in District No.2 in 2015 will be approximately 1,309 metric tons CO2eq,

as shown in Table 17. This is approximately 3.6e-6% of the global total CO2 emissions in 2013 (36

GtC/2013) (CDIAC, 2013). This value seems plausible as the road transport sector is expected to

Figure 27: Distribution of vehicle fuel types in SC

Source: Authors with data provided by (INE, 2009)


contribute 17-18% (UNEP, 2015) of annual global CO2 emissions, and District No.2’s population is

1.4e-3% of the global 7.3 billion.

Table 17: CO2 eq emissions from the transportation sector in District No. 2 in 2015

Source: Authors data provided by (INE, 2009) (USEPA, 2014).

The authors admit that this calculation over simplifies the distribution of miles driven by various

engine types. There are several incongruous assumptions that can be made concerning the distribution

of engine types such that:

1. All natural gas vehicles are fleet vehicles, such as city transit buses, as it is still uncommon to

find natural gas powered passenger vehicles anywhere in the world due to insufficient fueling

infrastructure.

2. All freight and delivery vehicles have diesel engines.

3. Or, the majority of diesel engines may be passenger vehicles as District No.2 is one of the

wealthiest communities in Santa Cruz and Bolivia, and may have a large percentage of imported

European vehicles.

In the absence of detailed information on the distribution of vehicle types by engine make the

authors are not comfortable with making such assumptions, as any could prove asinine to the actual

situation. This study assumes that errors can be generalized over the total miles driven in a year with

hopes of correcting errors in orders of magnitude.

5. Total Energy Demand of Current System and Sankey Diagram of the System

The total Energy Demand of the current System of District No. 2 is of 1,049 GWh/a and is

distributed as shown in Figure 28.

Fuel % of Vehicles No. of Vehicles Miles/a Grams CO2eg/mile MT CO2eg/a

Natural Gas 2 365 2,880 6,665 19.2

Diesel 19 3,468 27,360 10,180 278.5

Gasoline 79 14,418 113,760 8,887 1,011

2015 Total 100 18,250 144,000 -- 1,308.7


Figure 28: Sankey Diagram of the current energy system of District No2

The Sankey Diagram of the current energy demand of District No 2 was conducted based on the

available information and the results of the energy calculations of the urban systems. Three basic

adaptations were done due to the lack of necessary information:

1- Since there is not available information related with primary energy sources of the district,

the primary energy data of Santa Cruz was adapted for the area. That means the percentages

of three primary energy sources (23% by petroleum and gasoline, 50% by natural gas and 27

% by biomass) of the city was used for the district as well.

2- There was a lack in the information of the amount of transformed primary energy to the

secondary energy sources for the district. For that reason primary energy sources were

accumulated as total energy demand (1049 GWh/a) and then distributed to the sectors.


3- There was also a lack in the information regarding losses in the system, therefore the losses

are missed out for the diagram.

6. Proposed Renewable Energy Technology System

6.1. Energy Efficiency

6.1.1. Traffic

In order to achieve energy efficiency in urban scale, traffic is one of the main areas to focuse on.

There are basically two reasons for that. First of all, traffic is the component of an urban area which

requires significant amount of energy. Secondly, there are substantially increasing technologies and

alternative solutions for the problems arisen due mass energy consumption in transportation which

mainly offer less usage of motorized vehicle. There are three degrees of increasing energy efficiency in

traffic by reducing motorized mobility which can be summarized as follows (Böhler-Baedeker &

Höging, 2012):

Travel efficiency: Decreasing the need and demand for transport,

System efficiency: Meeting the travel demand with more efficient ways of transport,

Vehicle efficiency: Developing the vehicle technology in an energy efficient way.

In order to achieve the suggested to energy efficiency at these three main area, there are some

measures defined specifically for each of them. The measures are specified and suggested by this paper

for the case of 100.000 populated chosen district of Santa Cruz as follows:

6.1.1.1. Sustainable Urban Planning:

For the future land use planning of the district, a more sustainable way of urban planning should

be made. That would lead to decentralize the activities in the districts of the city. For that reason, this

paper suggests to increase the activities arising from basic human needs (supermarkets, cinema, various

stores, post office, medical care, pharmacy, grocery, banks etc.) in the chosen district which would help

to decrease the travel demand and motorized movements in the city.

6.1.1.2. Developing Public Transit:

Comparing to the personal vehicles, public transit has less energy needs and smaller ecological

impact on nature (Jacobson & Forsyth, 2008). For that reason more investments on public transit are

suggested for the chosen district to improve the means of transportation like subways, trams, busses,

etc. In addition to increasing investments on public transit, the planning of the district should be based

on a more transit-oriented approach which will integrate the urban design of the district and the public

transport means.

Encouraging Car-pooling: Gathering of people having the same travel destinations together is

both an energy efficient way for the environment and also a cost efficient way for the individuals.

Through carpooling the used energy for travel will be reduced as well as the emissions. In addition the


individuals will also benefit from it by sharing the everyday cost of travels. For the chosen district it is

suggested to encourage the networks like carpooling websites which will bring together the people who

have the similar destinations like work or study aimed and extracurricular activities (Litman, 2015).

Installing Bicycle Renting Stations and Encouraging a Bike Friendly Urban Design: Travelling

by bike not only improves the energy efficient ways of transportation but also encourages a healthier

way of life (Litman, 2015). Taking into consideration the first suggestion (Sustainable Urban Design)

having shorter distances to the daily activities within the district will also increase the use of bikes with

the help of a bicycle friendly urban design and traffic management.

Installing of Electric Car Sharing Systems: This measure will help people to rent cars from the

defined stations whenever they need to travel bigger distances in the cases of not being able to use the

public transit or bikes. A developed car sharing system will also decrease the car ownership in longer

term (Litman, 2015) .

6.1.1.3. Improving the technology of the vehicles and choosing less polluting fuel:

The vehicle technology has improved the energy efficiency of cars in a way that consumes less

energy and produces less emission comparing to older technologies like bio-fuel and electricity cars.

According to the information provided by the Union of Concerned Scientists, “On the best rate plans,

electric vehicles can save $750 - $1,200 a year on fuelling costs compared to a gasoline vehicle

averaging 27 miles per gallon and fuelled at $3.50 per gallon.” (Anair & Mahmassani, 2012)

This paper will suggest replacing the old cars which are already in use with the electric cars in

the chosen district within a reasonable time period. This will be done by leading of public authorities

and necessary public regulations.

6.1.2. Non-Residential Buildings

In the chosen district which has 936 ha of surface area, there 165,000m2 hospital, and 125,000

m2 school area existing. In order to achieve best practices in energy efficiency of public buildings, this

paper will provide some applicable measures in Santa Cruz.

Due to the hot climate public buildings needs to be cooled especially during the summer season

that will require air conditioning. In order to reduce the need the of cooling and thus the amount of

energy used for that basic features to be developed for the envelope of the building are: reinforcing the

general insulation for the walls, a good insulation for the roof using the reflective technology, improving

the windows with double or triple glazing (IEA, 2009).

Insulation of the Walls: Since walls are the major part of a building envelope and exposed to

outside temperature, they are subject to heat conductivity and thus thermal increase of the building.

Appropriate thermal insulation with the suitable material will help to lower down the heat transfer.


According the report of Energy Conservation Methods recommended by HPCB 1 , thermal

performance of walls can be developed by four basic steps (HPCB, 2012):

1. Increasing the thickness of walls

2. Arranging air cavity between walls and hollow masonry blocks

3. Applying insulation on the external surface.

4. Applying light colored painting on the external surface of the wall in order to reflect the sun rays.

Roofs: The roof of the building is exposed to significant level of solar radiation that is why it has

an important effect on heat gains. For an energy efficient building the roofs have to be protected in a

proper way which is suitable to the climate. For a proper insulation of the roof, the choice of the material

is important to achieve a higher R-Value2 in order to prevent heat flow (HPCB, 2012)According to

Holladay (Holladay, 2009); the ceilings or roofs should be insulated with the materials which improves

the resistance of the roof to the heat flow with at least the value of R-30.

Another important way of blocking the heat gains through roofs is to install reflective insulation

on the roofs of the buildings. In hot climates installation of radiant barriers made of aluminum foil is

advised to be very beneficial to avoid heat gains (Melody, 2005). Aluminum foil has two basic functions

to reduce the heat gains; first, it reflects the thermal radiation very well and secondly it gives off very

little heat. It might reduce the cooling demand of the building up to 8-12%, depending on the climate

and the user habits.

Air sealing: For both hot and cold climates, the buildings which need heating or cooling, tight

air sealing is an effective way to prevent heat transfer and thus will result in large energy savings.

Although the fresh air ventilation is essential for air quality, the mass amount of air leakage does not

improve air quality properly and also leads to energy losses. Designing of the buildings in way which

satisfies the ventilation need will be useful to reduce air ventilation energy consumption (IEA, 2009).

Windows: Windows are the components of a building which allows physical and visual

connection with outside environment, at the same time allows sunlight and air transfer (HPCB, 2012).

The right windows are the ones which allow sunlight pass through to lighten the inner environment, but

block the heat transfers in order to help to save energy to cool the building for hot climates. In order to

achieve the best energy efficient window the measures should be applied according to four mean factors

of a window: the size and placement, glazing, frame, shading.

1 High Performance Commercial Buildings in India 2 R-Value: the measurement of the resistance of an insulation or building material to heat transfer, expressed as R-11, R-20, etc.; the higher number indicates a greater resistance to heat transfer


Size and placement: In the case of Santa Cruz, the less number of windows should be faced to the

North to decrease heat gains. In addition, the size of the windows is suggested to be smaller in hot

climates in order to reduce thermal discomfort (HPCB, 2012).

Glazing: There are numbers of glazing systems existing in the market having variety of

combinations of glass panels, special coatings and tints. U-factor and SHGC (Solar Heat Gain

Coefficient) values are the basic numbers helping to decide on the most suitable material. The lower the

values are, the less the windows transmit through the building (HPCB, 2012).

Frame: Heat gain/ heat loss characteristics of a window also depends on the type and quality of

window frames. Table 18: Windows Types Used in Energy Calculations shows 20 windows systems

depending on different materials of frames and glazing (EWC, 2013). SHGC and U-factor values are

represented for the both centre of the glass and the whole window including the frames.

Shading: In order to minimize energy use for cooling, not only the low SHGC windows but a

good shade management is also important (EWC, 2013). Some examples for shading options are the

exterior devices like grills, awnings, shutters, roll-down shades, and canopies (Figure 29: Shading

technologies . For the chosen district, overhangs above the public buildings can be considered to be a

good option to provide shading. On the other hand, they can comply aesthetically with the galleries of

traditional housing in Santa Cruz.

Table 18: Windows Types Used in Energy Calculations (EWC, 2013)


Figure 29: Shading technologies (EWC, 2013)

6.2. PV

6.2.3. Potential

Bolivia has enormous potential in terms of generating solar energy due to its geographic location

and being close to equator. The country has potential to produce around 322 TWh solar energy within

a year as per National Renewable Energy Laboratory (NREL) in 2008, or 36% of the total annual energy

demand of 1,049 GWh/a in District No.2. The average Direct Normal Radiance (DNR) in Bolivia varies

from 3.5 to 8.9 KWh/sq m per day whereas in the city of Santa Cruz it's 3.79 KWh/sq m per day

(OpenEI, 2015).

Above Figure 30 and Figure 31 show the Direct Solar Irradiance for the city of Santa Cruz in

Bolivia. The use of renewable energy can decrease the country's dependency on fossil fuels and

hydropower projects for power generations, which adversely impact the environment. Thus, the strategy

would be to eventually cover the entire residential energy demand by using renewable resources.

Figure 30: Direct Normal

Irradiance (DNI) for each month in

Santa Cruz, Bolivia Source:

(OpenEI, 2015)

Figure 31: Direct Normal Irradiance (DNI) for Santa Cruz,

Bolivia, Source: (NREL, 2015)


6.2.4. Dimensions of Needed System

We have selected Poly-crystalline solar panels with the efficiency if 14.4% to be installed in Santa

Cruz at a capacity of 230-Watt peak demand. The city is blessed with 12 hours sunshine per day but we

took average sunshine of 8 hours considering the case of winter and rainy season (Weatherbase, 2015).

With the peak power, efficiency of the Poly-crystalline Solar Panels taken from the World's

largest solar panels manufacturers "Yingli Solar" and son hours per day taken for the city of Santa Cruz,

we calculated the peak power production for the whole city. The maximum number of modules is being

calculated based upon total roof top area of residential and nonresidential buildings. The given “total

production” results from covering the entire rooftop of the city with solar modules. As a result, we could

see that approximately 36% of the total annual energy demand of District No.2 can be achieved through

solar energy if all the rooftops of the houses in the city would be covered by poly-crystalline PV modules

with a peak demand of 230Watt.

Below tables display the formulas used for calculating the solar potential and calculation process

for Santa Cruz (Wholesale Solar, 2015).

Table 19: Formulas used for calculating the solar potential and calculation for the proposed system for Santa Cruz, Sources:

(Wholesale Solar, 2015) (Weatherbase, 2015).

Table 20: Formulas used for calculating the solar potential and calculation for the proposed system for Santa Cruz, Sources:

(Wholesale Solar, 2015) (Weatherbase, 2015).

6.2.5. Distribution Grid

In Bolivia around 96% of people in urban areas get electricity from two major sources, a natural

gas fired plant and a hydropower plant. The thermoelectric power plant runs on natural gas and a small

Peak Power Production (KWh/year)=Peak Power (Watt) × Efficiency (%) × Sun hours/day × 365 ÷1000

Maximum number of Modules= Total Roof Top Area (m2) ÷ Dimension of the Solar Panels (m2)

Production by Roof Top Area= Peak Power Production (KWh/year) × Maximum number of Modules

Dimension 1.3*0.9m2 Poly-crystalline Solar Panels

Peak power 230Watt Module type- YL230-29B 230-watt modules

Efficiency 14.4%

Sun hours per day 8

Peak Power production 113.004 KWh/a

Roof Top area 6,352,200m2

Max. number of panels 3,912,416

Production by Roof top

378.4 GWh/a

Coverage 36% Production by Roof top/total electricity

demand (residential)

Dimension 1.3*0.9m2 Poly-crystalline Solar Panels

Peak power 230Watt Module type- YL230-29B 230-watt modules

Efficiency 14.4%

Sun hours per day 8

Peak Power production 113.004 KWh/a

Roof Top area 6,352,200m2

Max. number of panels 3,912,416

Production by Roof top

378.4 GWh/a

Coverage 36% Production by Roof top/total electricity

demand (residential)


amount of oil and the total electricity generation is 5.8 billion kilowatt-hours (kWh). The economy of

the country relies on export of natural gas to other countries like Brazil and Argentina. Natural gas holds

around 32 % of the public sector revenue (EIA, 2015).

Electricity Supply in Bolivia (with the exclusion of North and East Bolivia)

Total Capacity Total number of Users

National Grid: Sistema

Interconectado Nacional (SIN)

1455MW not connected to North and East part

of country

Isolated System: Sistemas

Aislados (SA)

220MW 200000

Electricity Supply in Santa Cruz (East part of Santa Cruz)

Vertical Grid Operators Total Capacity Users

Servicios Eléctricos Tarija, S.A. (

SETAR)

44 MW 56885

Empresa Nacional de Electricidad

(ENDE)

16.65MW 16650

Cooperativa Regional de

Electricidad (CRE)

14.53MW 4940

Table 21: Electricity supply of the country and the city of Santa Cruz. Source (CIF, 2015).

The figure below shows the arrangement of electrical infrastructure of the national grid system

for the country of Bolivia.

Figure 34: Map of National Grid and isolated Power Lines in Bolivia. Source: (CNDC, 2008)

6.2.6. Energy Amortization

In order to determine the payback time of PV modules for the city of Santa Cruz, we considered

$400 US as cost of a Yingli YL230-29B 230-watt module type taken from Yingli Solar. The total cost

of PV modules is calculated from the number of modules

required for the proposed system as calculated above. As in

Bolivia, electricity supply depends on two main systems

such as national grid (SIN) and isolated system (SA)

therefore we considered the average number of it, as cost of

electricity. "The electricity tariffs are US$ 0.14 per kWh on

average in SA, and in some cases close to US$ 0.30 per kWh,

compared to $US0.08 per kWh for the SIN” (CIF, 2015). To

determine the annual electricity cost for Bolivia, we used the

Figure 32: Total Electricity Generation in Bolivia,

2012Source: (CIF, 2015)

Figure 33: Total Energy Consumption in Bolivia,

2011. Source: (EIA, 2015) (EoE, 2008)


calculated rooftop area and the electricity cost for 1 KW and thus determined the payback period of 24

years.

Table 22: Formulas for energy amortization. Sources: (Wholesale Solar, 2015) (Weatherbase, 2015).

Table 23: Calculation for energy amortization. Sources: (Wholesale Solar, 2015) (Weatherbase, 2015).

The Energy Payback Time of a PV systems is dependent on the geographical location. The energy

payback for poly-crystalline PV cells is 1.2 years for the country of Bolivia.

Figure 35: Global Solar Potential in kWh/m²/a , Source: (Fraunhofer, 2015)

6.3. Wind

6.3.7. Potential

Bolivia has huge potential in terms of generating wind energy. The first wind farm, Qollpana

Wind Farm, in the country, installed on January, 2014, has installed capacity of 3MW with total

investment of US$7.6 million and serves 24,000 people (CIF, 2015). The average wind speed in the city

of Santa Cruz is around 7.1 m/s. During the month of July and August the wind speed reaches its

maximum to 8.8m/s (NREL, 2015).

1

Module

Total number of modules needed for the

proposed system

Number of modules - 1 3,912,416

Total cost for PV modules - $400 US $1,564,966,741 US

Electricity production by roof top 378,371,398.7

KWh/a

- -

Cost of electricity per KW $0.17 US/KWh - -

Total annual Production value of PV in

District No.2

-- - $65,584,376 US/year

Payback period - - 24 years

Total cost of PV modules ($US) = No. of modules × Cost of a module

Total annual cost of electricity for Bolivia ($US) = Electricity production by roof top area (KWh/year) × Cost of

electricity for one Kilowatt ($US/KWh)

Payback period= Total cost for PV modules ($US) ÷ Total cost of electricity ($US/year)

https://en.wikipedia.org/wiki/Insolation


“A 1 MW turbine operating at a 25% capacity factor will deliver 2190 MWh during a year”

(GWEC, 2014).

In order to determine the wind potential for the city of Santa Cruz, the wind speed for each month

is considered from Solar and Wind Energy Resource Assessment. To determine the power produced by

wind turbine in different conditions, the wind speed for each month is taken into consideration. For that

purpose, the wind turbine of GoldWind GW77/1500 manufactured by China is considered with the

capacity of 1.5MW and 77 meter diameter of turbine. Different variables are considered in the tables,

presented below with description and calculation as follows: (The Wind Power, 2015), (NREL, 2015).

Formula Description Reason for choosing

Power converted

from wind into

rotational energy

Equation of the power can be defined

as P=0.5 ρAv3 by taking into account

the different rules and conditions such

as Newton's law, 3rd equation of

motion, considering initial velocity of

object. By considering the other factors

also in a complete wind turbine system

such as the gearbox, bearings,

generator etc. - only 10-30% of the

power of the wind is ever actually

converted into usable electricity.

Hence, the power coefficient needs to

be considered in above equation.

Power coefficient (Cp) Betz Limit

Cpmax = 0.59

Not a static value,

varies with speed

ratio and the wind

speed. Basically it

depends on turbine

and location.

A German physicist Albert Betz

concluded in 1919 that no wind turbine

can convert more than 16/27 (59.3%)

of the kinetic energy of the wind into

mechanical energy turning a rotor.

Speed ratio (λ)

= blade tip speed÷ wind speed

Not a static value,

varies with blade tip

speed and wind

speed

It helps to determine the value of

power coefficient by reading the Cp,

corresponding to speed ratio (λ) .

Blade tip speed

= rotational speed × π × diameter of

turbine(length of the blade) ÷ 60

It varies with the

length of turbine's

blades and its

rotational speed.

It helps to determine speed ratio

Table 24: Formulas

Power


Figure 36: Cp vs λ curve for wind turbine (with EA3) Source (The Royal Academy of Engineering, 2015)

Months Wind Speed

(m/s)

Air density

(kg/m3)

Swept area

(m2)

Speed ratio

(λ)

Power

Coefficient

(Cp )

Power (KW)

January 6.73 1.225 4657 7.873717 0.35

304316.5

February 6.38

1.225 4657 8.305661 0.34 251856.6

March 6.31

1.225 4657

8.3978

0.34

243657.2

April 6.38

1.225 4657

8.305661

0.34

251856.6

May 6.91

1.225 4657

7.668613

0.375

352921.2

June 7.94

1.225 4657

6.673818

0.4

571128.5

July 8.33

1.225 4657

6.361359

0.42

692463.1

August 8.11

1.225 4657

6.533923

0.41

623819.2

September 7.68

1.225 4657

6.899755

0.4

516839.8

October 7.52

1.225 4657

7.046558

0.425

515531

November 7.31

1.225 4657 7.24899

0.415

462394.4

December 6.39

1.225

4657 8.292663

0.34

253042.7

5039827

Table 25: Calculation of proposed system in regard to wind energy for the city of Santa Cruz.

Sources: (The Royal Academy of Engineering, 2015), (The Wind Power, 2015), (NREL, 2015)


7. Conclusions and Recommendations

As it is already pointed out at the beginning, planning of sustainable urban energy flows should

be adopted at all levels of urban areas such as buildings, neighbourhoods, municipalities, cities and

territories. From that point, District No.2 was chosen to conduct an urban energy assessment

considering the sectors of residential, commercial, industrial and transport based on available data. The

distribution of energy demand in District 2 is shown together with the distribution of World`s energy

consumption based on sectors (EIA, 2012) in Figure 37.

Figure 37: Comparison of energy consumption rates of District No2 with the World

As seen from the Figure 37, the urban energy distribution chart of the district is quite compatible

with the World`s common energy consumption pattern except of slight differences. The basic difference

is the higher percentage of residential energy use in District No 2 which might be resulted from its being

high-density residential area.

The best practices for the district are presented in the Chapter 6 suggesting low carbon

technologies for energy production (supply side) and energy efficiently planned infrastructure as well

as decreasing consumption habits (end-user side). Supply side and end-user side suggestions for District

No.2 can be summarized as follows.

Supply side:

Solar Energy is a great potential for a city like Santa Cruz due to its geographic location

and being close to equator. Therefore implementation of PV cells is suggested.

Wind Tribunes are also applicable in the area due to the high wind energy potential of

the city.

End-User Side:


District Cooling Grids can be implemented for the commercial areas in order to apply

a more efficient cooling strategy.

Transportation Planning should be conducted with the consideration of travel, system

and vehicle efficiency in traffic.

Non-Residential Buildings should be equipped with suggested strategies in order to

decrease the cooling demand of non-residential buildings (commercial).


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http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1814660

Data & Analytics

Annual Urban Energy Flows in Santa Cruz, Bolivia