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Renewable Energy 35 (2010) 2921e2932

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Renewable Energy

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Technical Note

A GIS-based decision support tool for renewable energymanagement and planning in semi-arid rural environmentsof northeast of Brazil

C. Tiba a,*, A.L.B. Candeias b, N. Fraidenraich a, E.M. de S. Barbosa a, P.B. de Carvalho Neto c,J.B. de Melo Filho c

aDepartamento de Energia Nuclear da Universidade Federal de Pernambuco, Av. Prof. Luiz Freire, 1000 e CDU, CEP 50.740-540, Recife, Pernambuco, BrazilbDepartamento de Engenharia Cartográfica da Universidade Federal de Pernambuco, Av. Acadêmico Helio Ramos, s/n - CDU, Recife, Pernambuco, BrazilcCompanhia Hidro Elétrica do São Francisco eDTG- CHESF, Recife, Pernambuco, Brazil

a r t i c l e i n f o

Article history:Received 18 February 2010Accepted 7 May 2010Available online 19 June 2010

Keywords:GISPlanning and managementPhotovoltaic energyRural electrification biomassWind energy

* Corresponding author. Tel.: þ55 81 21268252; faxE-mail address: tiba@ufpe.br (C. Tiba).

0960-1481/$ e see front matter Published by Elseviedoi:10.1016/j.renene.2010.05.009

a b s t r a c t

This work describes the development of a management and planning system on a GIS (GeographicInformation System) platform destined to decision makers that is, administrators, planners or consul-tants in renewable energies. It was conceived to deal with the management and planning of solarsystems, biomass and aeolics in rural regions of Brazil. The prototype of the GIS tool covers an area of 183,500 km2 and is made up of three blocks: management of installed renewable systems, inclusion(planning) of new systems and updating of the data banks. The GISA SOL 1.0 (Geographic InformationSystem Applied to Solar Energy) has a total of 80 layers of information that permit the realization ofspatial analyses on management and planning of renewable sources of energy at macro-spatial (state)and local (municipality) levels. A description and the methodology used for its development anda description of the functionalities will be made here. The system was developed mainly for PV systemsas a support tool for management and planning of the Energy Development Program for States andMunicipalities (PRODEEM), a program for inclusion in large scale of solar photovoltaic energy in the ruralenvironment, conducted by the Ministry of Mines and Energy of Brazil.

Published by Elsevier Ltd.

1. Introduction

1.1. Program of energy development for states andmunicipalitiesePRODEEM

The Northeast of Brazil, made up of 8 states, represents 18% ofthe total area of the country, is responsible for 16% of theproduction and has a population of 42,000,000 (28%). Approxi-mately half of this area, 760,000 km2, is semi-arid where17,000,000 people live. The climate of this region is hot and dryhaving a mean annual temperature of 27 �C and 2500 h/year ofinsolation. The annual precipitation varies from 400 to 800 mm,contrasting with an evapotranspiration of 2500 mm/year, whichdetermines a dry period of more than 7 months. The vegetationthat covers the semi-arid region is deciduous tropical forest, locallyknown as the caatinga, which develops over a complex mosaic of

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soils, Fig.1. High level of insolation, scarce hydric resources and rarerainfall, poorly distributed over time, cause long periods of drought.Thus, the relative shortage of superficial hydric resources, makesevident the importance of subterranean waters. The exploration ofthese waters is found to be limited because of the nature of its soils(predominantly crystalline), low discharge rate (mean of 3000 l/h)and mainly its quality. The great majority of the wells presenthigher salinity indices than the maximum limit permitted forhuman consumption, which is of 1000 ppm of dissolved total solidsand in many cases above 6000 ppm, the extreme water salinitylevel for animal consumption. Another aggravating factor thatmakes the solution to the problem of water supply difficult is thelow index of rural electrification in the Northeast.

To face this kind of challenge, the Federal Government estab-lished the PRODEEM e Program of Energy Development for Statesand Municipalities through a presidential decree in December1994, with the following objectives:

- Make viable the installation of energy microsystems forproduction and local use in isolated needy communities that

Fig. 1. The Caatinga in dry and rainy periods and details of vegetation.

C. Tiba et al. / Renewable Energy 35 (2010) 2921e29322922

are not served by electric network, that are destined to aid inattending basic social demands;

- Promote the utilization of decentralized energy sources in thesupply of energy to the small producers, settlers and isolatedpopulations;

- Compliment the conventional energy system offer with the useof decentralized renewable energy sources;

Fig. 2. Settlement of landless people called Gualter, in the municipality of Canindé

- Promote the utilization of human resources and developmentof technology and national industry, essential for implantationand operational continuity of the implanted systems.

Since the year 1996 PRODEEM has bought and installedthousands of photovoltaic systems that are spread around thenational territory. In the phases denominated I to V and a special

of São Francisco in Alagoas, after the construction of the water supply system.

Fig. 3. Productive applications in community with photovoltaic solar energy: electric fence and school.

C. Tiba et al. / Renewable Energy 35 (2010) 2921e2932 2923

one denominated Pumping, three kinds of autonomous photo-voltaic systems were installed: photovoltaic systems for genera-tion of electric energy (energetic), photovoltaic systems forpumping water and for public illumination. The systems wereonly destined for application in communities, which means thatthey should benefit the communities as a whole, and not onlysome individuals in particular. The total of photovoltaic systemsinstalled in this program was 8956, corresponding to a totalpower of 5.2 MWe, and it can be considered as one of the largestrural electrification programs that use photovoltaic solar energyin developing countries. Most of the photovoltaic systems wereinstalled in the North and Northeast regions, 1471 and 4577systems respectively. In the target regions of this project AL, PEand PB 905 systems were installed, in accordance with the MMEElectric Energy Atlas [1].

Fig. 2 shows the settlement of the landless people called Gualter,in the municipality of Canindé of São Francisco in Alagoas, after theconstruction of the water supply system all supplied by photovol-taic solar energy: the water supply system, the collective laundryand the drinking trough for animals. Fig. 3 shows some otherproductive applications in the community with photovoltaic solarenergy: electrified fence and school.

Fig. 4. Fluxogram of project deve

The experience accumulated by PRODEEM in the last ten yearsshows the enormous challenge of management, planning, trainingand sociology of the implantation, on a large scale and in largeterritorial extensions, of innovating technology and decentralizedtechnology as of photovoltaic generation. The traditional toolsdemonstrate their limitations andmake the execution of such tasksvery difficult.

1.2. What is GIS and why?

The GIS (Geographic Information System) is a tool for compu-tational treatment of geographical data and their associated databanks. It can be seen as a support system for decisions that unitespatially referenced data in a problem response environment. GISgroups, bring together and unite information. Through this, avail-able information becomes more accessible, and old information isput into a new context. In this project, the GIS were used as a toolthat permits the integration and processing of information fromdiverse sources. From this it is possible to use it in the elaboration ofstrategies for implantation and management of rural electrificationwith renewable energy.

lopment, planning module.

Fig. 5. Principal menu of the GISA SOL 1.0.

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The GIS is a valuable tool for evaluation and development of theuse of renewable energy resources in large regions, because it isa tool that is specially adequate for analyzing the spatial variabil-ities of the resource as well as also for resolving problems ofmanagement and planning of installation programs of decentral-ized systems, that are characterized by a great spatial dispersion.The solar resource is strongly influenced by altitude, latitude andphytogeographical conditions; the aeolic resource for rugosity andtopography of land and finally the biomass for its soil characteristicand pluviometric conditions.

In its turn, management and planning of renewable energysystems, is a task that besides knowledge on energy resource needsknowledge on the nearest technical assistance center, a diagnosis ofthe most frequent defects, information from installed systems, theproximity to electric transmission lines, the energy demand, thelaws that regulate land use, the indices of human development andnon-electrification and tools for dimensioning the systems for thegiven local demand, among others. All these interrelationships canbe collected, quickly quantified and visualized spatially by theintrinsic management capacity of a GIS system.

1.3. GIS and renewable energies

The use of GIS in renewable energy that began in the 1990s wentthrough considerable progress and as a result various decisionsupport tools were developed [2]. The GIS applications that weredeveloped canbe classified in threegroups:GIS as adecision supporttool for integration of renewable energies on a large scale and ata regional level, GIS for assessment of distributed energy generationand that connected to the electric network andGIS for decentralizedproduction systems and autonomous production of electricity.

The GIS decision support tool for integration of renewableenergies on a large scale and at a regional level (EuropeanCommunity) proposes to analyze: evaluation of renewable energypotential (solar, aeolic, biomass and minihydraulic), its participa-tion in relation to primary regional energy and the potentialreduction of CO2 emissions [3]; evaluation of economic andpotential renewable energies to identify regions of the EuropeanCommunity where the renewable sources were competitive ata determined risk [4]; evaluation of renewable energy potential,calculation of the final use in the region and according to thescenario the insertion of a given renewable energy, makes itsdimensioning and evaluates the economic impacts [5].

TheGIS for evaluationof distributed generation, connected to theelectric network considers the following renewable energy sources:aeolic, biomass and solar. The majority of GIS applications for aeolicenergy deal with the optimum localization of the aeolic plants,consider the potential of the resource, the infrastructure for accessand transmission lines and environmental restrictions and land use[6e8], also Matthies [9] considers petroleum platforms, shippingroutes and submarine lines for study of optimum localization ofoffshore aeolic farms. Marnay [10] developed a study of the use ofphotovoltaic solar energy installed on roofs of residences in the USAusing GIS. The project included a municipality level resolution andconsidered the followingvariables: solar irradiation, averagepriceofelectricity and spatial distribution of the population.

A peculiar characteristic of biomass utilization is the necessity oftransport from the local of cutting to a central transformer whichmakes the geographic proximity of the offer a determining factor forthe final cost of the generated electric energy. Noon [11] developeda GIS for the Tennessee Valley, USAwhich considered the followingvariables: the characteristics of places of biomass offer, places of

Fig. 6. GISA SOL general functionalities: Management at state (macro) and municipal (local) levels.

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demand and transport costs, technical characteristics of the plants,forestry residues or cultivated forests, road networks and adminis-trative limits. Voivontas [12] developed awork on the Island of Creteabout thebiomass potential for generation of electric energy. It dealswith the combination of evaluation of the resources (theoreticaland/or available), the transport cost, the identification of optimumlocals for biomass cultivation and the definition of the size of theplant for determining its economic competitiveness in the presenceof conventional sources. Similarly in Spain one was developed byIBERINCO [13].

SOLARGIS [14] is a GIS for rural electrification with renewablesources of energy. It is a paradigm of a GIS tool for this purpose asmuch for its completeness, relatively ample diffusion of its use asalso for the periodic updating and improvements. The principalobjectives of its development were: the demonstration of value ofthe GIS methodology for the development of the implantation ofrenewable sources for rural electrification, demonstration of itsapplicability in some target regions and proper construction ofa GIS tool for analysis of the potential renewable sources. TheSOLARGIS methodology intends to obtain the best option for ruralelectrification, in isolated localities using renewable systems or not,being individual user or users connected to a local mini-network.The isolated residence could be electrified by PV systems, aeolic,gas generator, diesel group or interconnected to an electric mini-grid. Amini-grid could be supplied by group diesel or hybrid aeolic-

diesel system. The high potential regions are determined throughcomparison of equivalent costs of electrification of the energysystems considered. For this calculation, with a resolution of 1 km2,the following information is used: habitation density, mean annualglobal irradiation on the collector plane, mean annual wind velocityand distance of residence to electric energy network. SOLARGIS wasapplied in Tunis (Tunisia), Kairouan (Tunísia), Marrocos, Sicilia(Italia), Andaluzia (Spain), Murcia (Spain), Crete (Greece), Island ofSantiago (Cape Green), Pará (Brazil) and Karnataka (India).

NREL [15] is a GIS tool that is accessible via web that permitsvisualization of monthly mean solar irradiation with a spatialresolution of 40 km � 40 km (low) and in high resolution10 km� 10 km for a collector plane facing the south, with the tilt inrelation to the horizontal equal to latitude or the direct normalsolar irradiation. In the same way it produces estimates of aeolicenergy on an annual base, for low resolution (1/3 or 1/4�) and highresolution cell size of 20e1000 m. Also the tool includes an esti-mation of the biomass potential derived from the different sources(agricultural and forestry residues, waste, among others).

Renewable Energy Atlas of the West [16] is a GIS tool that isaccessible via web which synthesizes the data and maps onrenewable energies for eleven American states that are situated intheWest of America: Arizona, California, Colorado, Idaho, Montana,Nevada, New Mexico, Oregon, Utah, Washington and Wyoming. Ata regional level (West American) the atlas shows, solar, aeolic,

Fig. 7. Photovoltaic pumping systems installed in the states of Paraiba (a) and Pernambuco (c). (b), the water pumping systems with discharge rate higher than 6 m3/h installed inParaiba and (d), the photovoltaic pumping systems in Pernambuco with manometric heights greater than 30 m.

C. Tiba et al. / Renewable Energy 35 (2010) 2921e29322926

biomass and geothermic resources, the present mix of electricitysupply, the renewable energy systems installed and information onpublic policies for stimulating the use of renewable energies. Alsothe present capacity of transmission lines, an estimation of chargegrowth in the region, aspects of soil use and environmental impactsare presented. In other sections the Atlasmakes an in detail accountof this information at state level.

PV-GIS [17] is aGIS application that is available in real time inwebfor calculating the photovoltaic solar energypotential in Europe. Theuser can navigate over solar irradiation maps and obtain the solarirradiance incident on a photovoltaicmodule positioned at differentinclinations. A second application permits the obtention of themonthlymeandailyprofile for a givenmonthanddifferent positionsand inclinations of the module. Finally a third application calculatesthe photovoltaic electric energy for a given configuration of PVsystems that are localized in a given place.

2. Methodology for development of GISA SOL 1.0

The development of GISA SOL - Geographic Information SystemApplied to Solar Energy [18] methodology includes diverse stagesthat can be schematically seen in Fig. 4 where the fluxogram of

development of the GIS planningmodule is shown. The great stagesof development of the module for planning the inclusion ofrenewable energies can be seen from left to right and represent:

- Collection of raw data on renewable energy resources, infra-structures, economic and social information, demographies,indices of non-electrification, aptitude for determinedcultures, installed renewable energy systems, existing wells,among others;

- Elaboration of a standardized geographic data bank, that is,referenced and uniform data;

- Elaboration of data bank with dimensioning of PV energysystems and for pumping water; estimation of electricitygenerated by sugar cane bagasse; estimation of electricitygenerated by wind and climatic aptitude for biomass cultures;

- Creation of a system that permits cross information accordingto rules dictated by geographics, techniques, social or admin-istrative restrictions. The crossing is a geographic filtering thatpermits an answer to a given investigation of the user and

- Finally the study of the best localities is done for inclusion ofa determined renewable energy technology in accordancewithsome criteria pre-established by the user.

Fig. 8. Batteries (a) and inverters (b) installed in Pernambuco. Additionally in yellow (a) PVX 12105 model batteries and (b) the Starpower model inverters.

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The management module has the same structure as the plan-ning module, however, it has different geographic data bases andresults. The geographic data bank in this case contains detailedinformation on the PV systems installed by PRODEEM for phases Ito V and emergent phase (pumping) whose fields are defined in theTechnical Report on Revitalization of Energy Systems and Infor-mation on the Availability of Energy Sources. The results permit theidentification of types of equipment, kinds of benefits, installationphase, ill functioning (fault) and distance to the nearest mainte-nance center, among others.

3. General description of GISA SOL 1.0

The GIS prototype tool covers an area of 183,500 km2 andcorresponds to the total area of three states, Alagoas, Pernambucoand Paraiba. In a second phase it will be extended to 1,561,178 km2

which corresponds to the total area of the Northeast region.The energy sources considered in this project were solar, aeolic

and biomass. These renewable energy sources are abundant in the

Fig. 9. Installation phase according to PRODEEM, in (a) the ph

region, adequate for the distributed generation and impact as muchfor the quality of life as well as for generation of income and jobs inthe region, particularly in the case of castor bean plant with theinclusion of family agriculture in the production chain of biodiesel.

The totality of the developed GIS tools previously described arefocused on the planning of the insertion of renewable sources anddoes not deal with the management problems of a program forinsertion of renewable energies on a wide spatial scale such asPRODEEM e The Energy Development Program for States andMunicipalities. The GISA SOL (Geographic Information SystemApplied to Solar Energy) is a methodology based in GIS formanagement and planning of programs for insertion of renewableenergy sources.

3.1. Principal menu

The GISA SOL 1.0 (Geographic Information System Applied toSolar Energy) is made up of three principal blocks: management,planning, and updating of data bank, according towhat can be seen

ase V in Paraiba and in (b) illumination in Pernambuco.

Fig. 10. Photovoltaic systems installed in the municipality of Ibimirim in the state of Pernambuco (a) and in (b) models of PV modules that were used in the systems.

C. Tiba et al. / Renewable Energy 35 (2010) 2921e29322928

in Fig. 5. Management and planning occur at two levels: macro-spatial (state) and local (municipal). The updating of data bank canbe done by rectification, exclusion or inclusion of information todata banks that are associated to already installed energy systems.

3.2. Functionalities

The use of a GIS tool requires the formulation of questions,whose answers are products of crossing one or more data banksand/or maps. The result is not normally completely conclusive(closed) and the product is a group of spatial information and/orreports that almost always still require the interpretation of whomade the question. The GISA SOL 1.0 was constructed to give theuser answers to questions, of general and simple character, that inthe majority of times corresponds to one layer of information orcomplex questions whose answers are products of crossing ofdiverse layers of information. The answer to questions of simplegeneral character are denominated default functionality and are

Fig. 11. Operational state of PV system components installed in P

recorded as sub-menus in the menus of management and planningat macro-spatial and local level. The non default functionalitiesgenerated by complex questions by the users can be printed orrecorded and can be transformed into default functionalities. Otherdefault functionalities associated to the tasks of updating the databank and dimensioning renewable energy systems are in the sub-menus of the updating and planning menu.

3.3. Management module

The default functionalities of the GISA SOL 1.0, managementmodule (PV management) are made up of three levels menus:a macro-spatial where the basic unit is the state, another local atmunicipal level and finally the possibility of updating of table data,according to what can be seen in Fig. 6, where are open.

The macro-spatial management is constituted of 5 distinctblocks:

ernambuco (a) and in (b) the nearest maintenance centers.

Fig. 12. Municipalities of Pernambuco that have income per capita less than US$100 (a) and (b) areas of exclusion defined as indigenous, ecological reserves and special areas ofpreservation.

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- Installed photovoltaic systems and types of application;- Description of type, operational situation, fault andmodel of all

the components of the installed photovoltaic systems;- Maintenance and training centers;- Phase of installation according to PRODEEM and- Infrastructure of transmission lines, roads and airports.

Fig. 7 shows the photovoltaic pumping systems installed in thestates of Paraiba (a) and Pernambuco (c). It also shows for each typeof application the possibility of a more detailed filtering througha menu where the benefits and some specific aspects can bechosen: in (b), for example, the water pumping systems withdischarge rate higher than 6m3/h installed in Paraiba and in (d), thephotovoltaic pumping systems in Pernambuco with manometricheights greater than 30 m.

Fig. 8 shows the batteries (a) and inverters (b) installed in Per-nambuco. Additionally it shows the possibility of a more detailedfiltering by a menu where a specific model can be chosen: in (a)

Fig. 13. Subterranean wells cadastred by

showPVX 12105 model batteries and in (b) the Starpower modelinverters.

Fig. 9 discriminates the photovoltaic systems installed in Ala-goas and Pernambuco showing the installation phase according toPRODEEM, in (a) the phase V in Paraiba and in (b) illumination inPernambuco.

3.4. Local management functionalities

The local management is regarded in 4 distinct blocks:

- Photovoltaic systems installed in the municipality;- Identification of a determined model and manufacturer for

each component;- Identification of a determined model and manufacturer of

photovoltaic modules;

CPRM in the state of Pernambuco.

Fig. 14. Aptitude of sugar cane culture in two distinct scenarios: dry and rainy period.

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- Operational situation of all the components of the installedphotovoltaic systems;

- Identification of the nearest training and maintenance center.

Fig. 10(a) shows the photovoltaic systems installed in themunicipality of Ibimirim in the state of Pernambuco and in (b)which are the models of PV modules that were used in the systems.Fig. 11(a) shows the operational state of PV system componentsinstalled in Pernambuco and in (b) the nearest maintenancecenters.

3.5. Planning module

The planning process for the insertion of renewable energies inrural areas is normally a complex task because it demands anapproach with multiple criteria: energy resources, socio-economicindicators, indices of non-electrification, among others. If weadditionally consider the intention of stimulating regional devel-opment through the inclusion of energy systems for productiveaims, we have to consider the aptitude of the soil for diversecultures and the existence of hydric resources. The GISA SOLplanning module was constructed considering these conditionals

Fig. 15. Mean annual wind speed and prevailing direction o

and the possibility of analyzing the possible combinations ofcriteria defined by the user for localities for the implantation of newrenewable energy systems.

The GISA SOL functionalities for macro-spatial planning basi-cally consist of the following blocks:

- HDI and index of non-electrification;- Areas of exclusion;- CPRM wells;- Aptitude for sugar cane, quantity of produced cane and

capacity of electric energy generationwith sugar cane bagasse;- Aptitude for castor bean plant, period of planting and biodiesel

plants;- Energetic forests;- Wind direction and intensivity, promising area and capacity of

electric generation by the wind;- Monthly solar irradiation on the horizontal plane and solar

irradiation on the collector plane in the month of minimumirradiation.

Fig. 12(a) shows the municipalities of Pernambuco that haveincome per capita less than US$100. The HDI sub-menu permits the

f winds in two distinct scenarios dry and rainy period.

Fig. 16. Solar irradiation on the horizontal plane for the months of minimum occurrence (July) and maximum (November) for the state of Pernambuco.

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obtention of maps with other additional social indicators. The areasof exclusion are defined as indigenous, ecological reserves andspecial areas of preservation. They are considered areas of exclusionwhen one wants to localize conventional energy systems or largescale renewable energy systems. In the case of localization of smallscale and distributed renewable systems, such areas must beconsidered as maximum priority. Fig. 12(b) shows these areas forPernambuco.

Fig. 13 shows all the subterranean wells cadastred by CPRM inthe state of Pernambuco. A more detailed filtering through a menupermits the choice of some specific aspects as depth or finality. Inyellow, for example, wells of depths greater than 30 m.

Fig. 14 shows from left to right the aptitude of sugar cane culturein two distinct scenarios: dry and rainy period. Fig. 15 shows fromleft to right themean annual wind speed and prevailing direction ofwinds in two distinct scenarios dry and rainy period. Finally, Fig. 16shows solar irradiation on the horizontal plane for the months ofminimum occurrence (July) and maximum (November) for thestate of Pernambuco.

3.6. GISA SOL e calculus

In the planning process for inclusion of renewable energysystems, after the definition coming from a multiple criteriaapproach (energy resources, socio-economic indicators, indices ofnon-electrification, among others) of the localities to be benefited,a dimensioning of the energy systems is necessary. The GISA SOLpermits the realization of dimensioning or simplified calculus forthe following systems:

- Autonomous photovoltaic system [19];- Photovoltaic system interconnected to the network;- Photovoltaic pumping systemwith given demand and depth of

well [19];- Photovoltaic pumping systemwith given capacity and depth of

well;- Annual electric energy generated by sugar cane bagasse and- Annual electric energy generated by wind energy [20,21].

4. Conclusions

The most important aspects for management and planning ofdecentralized renewable energy systems were identified and

implemented in a Geographical Information System denominatedGISA SOL 1.0 (Geographical Information System Applied to SolarEnergy).

The methodology developed in GISA SOL 1.0 permits planningof massive insertion of renewable energy systems and themanagement of renewable energy systems already implanted anddistributed in large spatial areas. The planning module makespossible the identification of the most favorable localities for theinstallation of new energy systems, bearing in mind diversecriteria such as: solar resource, HDI, rural electrification index,income per capita, proximity to transmission line, existence ofpotable water, aptitude for diverse agricultural cultivation, windresources and restriction of soil use. Apart from this, the modulepermits the carrying out of simplified dimensioning for photo-voltaic and wind systems as well as calculating potential localelectrical energy generated by biomass. The management modulefor renewable energy systems (PV systems management) makespossible the crossing of thematic maps such as: installed photo-voltaic systems and types of application; operational situation,fault and model of all the components of the installed photovoltaicsystems; maintenance and training centers; phase of installationaccording to PRODEEM and infrastructure of transmission lines,roads and airports.

Finally, the totality of the developed GIS tools previously pub-lished are focused on the planning of the insertion of renewablesources and do not deal with the management problems ofa program for insertion of renewable energies on a wide spatialscale, GISA SOL 1.0 consider both.

Acknowledgements

To the National Research Council (CNPQ), the São FranciscoHydroeletric Company (CHESF), and Brazilian Electric Centers S.A.(ELETROBRAS), CAPES-PROENGENHARIAS for the support in thesolar energy researches, particularly are regarding the themesreferring to measurements, evaluation and solar irradiationmapping.

References

[1] MME electric energy Atlas, www.mme.gov.br. Access in September 2009.[2] Bravo JD. Los sistemas de información geográfica en la planificación e inte-

gración de energías renovables. Madrid, España: Editorial CIEMAT, ISBN84-7834-434-9; 2002.

C. Tiba et al. / Renewable Energy 35 (2010) 2921e29322932

[3] Bourges D. A geographical information system for large scale integration ofrenewable energies into regional energy markets, Renewable Energy Devel-opment European Conference and APAS-RENA Contractors Meeting, EDIFIR,Florence; 1996.

[4] Rialhe A. Epure project: economical potential use of renewable energy,Renewable Energy Development European Conference and APAS-RENAContractors Meeting, EDIFIR, Florence; 1996.

[5] Georgopoulou E, Sarafidis Y, Diakoulaki D. Design and implementation ofa group DSS for sustaining renewable energies exploitation. European Journalof Operational Research 1998;109(2):483e500.

[6] Voivontas D, Assimacopoulos D, Mourelatos A. Evaluation of renewableenergy potential using a GIS decision support system. Renewable Energy1998;13(3):333e44.

[7] Petit C. Winds of change. GIS helps site wind farms in France. GIS Europe.Godmanchester (Huntington): GeoTec media; 1995. pags. XVII-XVIII.

[8] Baban SMJ, Parry T. Developing and applying a GIS-assisted approach tolocating wind farms in the UK. Renewable Energy 2001;24(1):59e71.

[9] Matthies HG, Nath C, Schellin TE, Garrad AD, Wastling MA, Quarton DC, et al.Study of offshore wind energy in the EC. 5th ed., vol. 1. Brekendorf, Germany:Verlag Natürliche Fnergic; 1995. Offshore Wind Energy Potential in the ECJoule I (JOUR 0072).

[10] Marnay C, Richey R.C, Mahler S.A, Bretz S.E. and Markel R.J. Estimating theenvironmental and economics effects of widespread residential PV adoptionusing GIS and NEMS, Ernest Lawrence Berkeley National Laboratory:University of California, EEUU Report, LBNL-41030, UC-1321; 1997.

[11] Noon CH, Daly MJ. GIS-based biomass resource assessment with BRAVO.Biomass and Bioenergy 1996;10(2e3):101e9.

[12] Voivontas D. Assessment of biomass potential for power production: a GISbase method. Biomass and Bioenergy 2001;20:101e12.

[13] Iberinco, Oportunidades para la producción de energía a partir de biomasa enLa Rioja (España) y La Toscana (Italia), ALTENER pilot Project, Contract No.XVII/4, 1030/Z/98e214; 1998.

[14] Solargis Team. Solargis handbook. Bruselas: Comision Europea, DirecciónGeneral XII; 1996.

[15] NREL. Dynamic maps, GIS data and analysis tools, www.nrel.gov/gis/maps[Access in April 2007].

[16] Renewable energy Atlas of the West, www.energyatlas.org [Access in April2007].

[17] Suri M, Huld TA, Dunlop ED. PV-GIS: a web-based solar radiation database forthe calculation of PV potential in Europe. International Journal of SustainableEnergy 2005;24(2):55e67.

[18] Siga Sol 1.0. Sistema de informação geográfica aplicada à energia solar. ProjetoANEEL-CHESF; 2007. CT-I-192.1760.0, in Portuguese.

[19] Tiba C, Fraidenraich N, Barbosa EMS. Instalação de sistemas fotovoltaicos pararesidências rurais e bombeamento de água. Recife, Pernambuco: Universitáriada UFPE, ISBN 85-7315-118-8; 1998. In Portuguese.

[20] Retscreen. Photovoltaic projects analysis, www.retscreen.net [Access in April2009].

[21] Amarante OC, Brower M, Zack J, Leite de Sá A. Atlas do potencial eólicobrasileiro. MME eELETROBRAS-CEPEL; 2001. In Portuguese.