GIS Tool for Rural Electrification with Renewable Energies in Latin America

Transcription

1 GIS Tool for Rural Electrification with Renewable Energies in Latin America Javier Domínguez, Irene Pinedo-Pascua Renewable Energy Department CIEMAT, Science & Innovation Ministry Madrid, Spain Abstract Renewable energy sources are increasingly being considered as feasible and competitive alternatives in the provision of electricity to isolated rural communities. Electrification planning process must consider the geographical characteristics of the renewable energy sources as well as the social and economical particularities of the target communities, contributing to the long and stable operation of the chosen technologies. GIS are able to manage all the data needed in the decision making process, providing means to compare costs of alternative technologies, based on renewable and non-renewable energy sources. This paper discusses the methodology used by the GIS group for regional integration of Renewable Energies and rural electrification (gtiger). This method, named IntiGIS, aims to provide the analysis tools we use with more flexibility and dynamism, broadening its application possibilities based on the huge chances given by Geographical Information Technologies. In this paper, an example of GIS to rural electrification carried out in Latin American countries is presented. Keywords: rural electrification, Geographical Information Systems, levelized electric cost, decision making, Latin America, renewable energies. I. INTRODUCTION According to the conclusions of the World Energy Outlook Report, over 1.6 billion people in developing countries do not have access to electricity in their home [1]. Electricity is indispensable in most of the daily activities, such as lighting, refrigeration and running of household appliances, and so, is particularly crucial to improve quality of life. Un-electrified communities are usually remote and scattered, and grid extension is not always feasible. In those cases, renewable stand alone technologies arise as potential and competitive solutions to fulfil local electricity demands. Renewable energies are generated from natural resources and are naturally replenished. Renewable energy sources (RES) include wind, sun, waves, tides, biomass and geothermal heat, being the sun the ultimate source of this type of energy. RES are characterized by a wider geographical dispersion compared to conventional sources of energy, making the potential of indigenous RES in a region usually higher than the availability of oil or gas, whose world wide distribution is clearly concentrated in a few countries. Therefore, using renewable energies means that we are taking advantage of indigenous resources and becoming less dependent on energy imports. The paper is organised as follows: a brief state of the art of GIS and renewable energies is presented first; secondly, the huge importance of the use of GIS in the development of renewable energies applications in Latin America is highlighted; finally, the achievements made by our team in the constant development of a GIS model for rural electrification with renewable energies (IntiGIS) are described. II. GEOGRAPHICAL INFORMATION SYSTEMS AND RENEWABLE ENERGIES There is no doubt about the spatial dimension of RES. In addition to the fact of being on-site located sources of energy, the use of RES could promote the local development in the rural regions of less-developed countries, in terms of improving living conditions, encouraging the farming sector and stimulating new social and industrial activities. Spatial and temporal variability of RES could also influence in how adequate the coupling between energy sources potential and electricity demand is planned. Therefore, RES assessment studies must always be linked to the territory and include a rigorous analysis of the geographical reality, taking into account economic, social and environmental aspects. In order to involve the territorial dimension in energy planning processes, GIS has been successfully used in several cases as the main analysis tool [2]. In this sense, we will highlight some relevant examples that contribute to understand the special relations between renewables and GIS. A. Geographical Information Sytems applied to rural electrification One of the first contributions to this field was made by Ariza López [3]. In his study, the competitiveness of the stand alone photovoltaic systems versus grid electricity supply is evaluated. As a result, the studied territory, a province in Southern Spain, is classified upon which electrification option minimises the produced kwh cost. The analysis does not consider the real location of the demand, although GIS functions allow doing so, but it is based on different scenarios in which the most influential economic parameters vary (subsidies, interest rates, ecotaxes, etc.). Taking the resulting scenarios, several demand values ranging from 5 to 50kWh are considered. The results are

2 presented both, numerically and cartographically, the last one by means of Boolean maps. Another substantial contribution was made by Muselli [4]. In this case, four different technological options for the electrification of remote areas in Corsica Island are considered: stand alone PV/Batteries systems, Hybrid PV/Batteries/Back-up generator systems, engine generator providing the load and extension of the electric power grid. The comparison is based upon the optimization of the systems configuration with a Loss of Load Probability equal to zero. In the study made by Fronius [5] a software based on GIS technology and rural planning oriented is presented. The software is composed by two modules: LAPER and GIS. The first one is used in the definition of the electrification optimum model and costs calculation, while the second one provides interfaces and stores the data. The software compares the costs associated with all the chosen technologies with the cost of grid proposed by the user. As a result, the proposed grid is replaced by the selected distributed system, minimising the inversion costs. The contribution made by Byrne [6] is really valuable since it makes clear how powerful the GIS calculation capacity is, managing an enormous variety of values for the input variables. The aim in this work is the definition of small scale renewable energy options to meet the electricity needs in Western China rural communities. Its methodology is based on a performance assessment of twenty small wind, photovoltaic and wind-photovoltaic hybrid configurations, defined by simulation. This tool is called Rural Renewable Energy Analysis and Design (RREAD) and calculates the LEC value using spreadsheets. It assesses the available resource using hourly wind and radiation data. The demand is defined by means of statistical analysis and interviews that help in the definition of the load profile and several scenarios for growing demand. Finally, ArcView GIS is used to spatially link the resulting information about resources and the LEC value for every technology. B. Latin-american experiences Undoubtedly, Latin America is an especially propitious region for rural electrification studies and projects based on renewable energies using GIS. Apart from the advantages given by this tool to the RES assessments regardless of the particular location, in Latin America both the high figures of rural population without access to electricity (10% of total population in 2005 according to the World Energy Outlook, which accounts for millions) and the high diversity and geographical complexity of renewable resources (resulting in the richness and variability), make GIS a suitable tool in energy planning and RES promoting activities. In this sense, we would present two examples of GIS application in renewable energies planning in Latin American area. The first one is GISA-SOL, developed by the Federal University of Pernambuco in collaboration with CHESF (one of the most important energy companies of Brazil)[7]. GISA-SOL is a GIS for planning and management renewable energy sources (wind power, biomass and PV systems) in rural regions of Northeast of Brazil. There are two modules: the planning module, oriented towards the identification of the best sites for new renewable power plants; and the management module, which focuses in PV installed systems in the frame of PRODEEM (energy development program). The other example is the application of Woodfuel Integrated Supply/Demand Overview Mapping (WISDOM) in Mexico [8]. This project has been developed by Food and Agriculture Organization (FAO), in cooperation with the Centre for Ecosystem Research of the National Autonomous University of Mexico (UNAM). WISDOM is a spatially explicit method for determining woodfuel priority areas. This GIS-based tool analyzes the spatial pattern in energy demand and supply including: the assembling of existing but dispersed information into single data sets, a modular integration of data sets, based on the analysis of key variables associated with woodfuel demand and supply patterns, and a multiple-scale and spatially explicit representation of the results. The result is a ranking of areas where several criteria are satisfied. C. CIEMAT and Latin-american GIS projects Our group is in permanent contact with Latin American scientific groups, interchanging researchers and developing projects. In this sense, we could mention the projects and collaborations made with Brazil, Cuba, Colombia, Argentina, Chile, Mexico or Guatemala. In particular, we will specify in the following paragraphs some of the activities on this field of gtiger at Research Center for Energy, Environment and Technology (CIEMAT), where we participate and/or lead the following projects: Renewable Energies Use Optimization in Towers of Paine National Park: bases to a methodological model. Developed by Professor Kustmann from the University of Magallanes in Chile. GIS application in the integration of renewable energies in electricity production in rural communities: Cuban municipality of Guamá case study [9], made by I. Pinedo. The main results of this project and the model specifications will be explained in the next section. In the same area the study Land use and renewable energies planning using GIS in Guamá municipality was made by the researcher María Rodríguez from the Electrical National Union, Cuba. Hybrid Systems design methodology for the generation of electrical energy: analysis of its viability using Geographical Information Systems. Paul A. Manrique, Universidad del Valle, Cali (Colombia). Design and implementation of an integrated modelling platform for energy planning- Sustainable environment and development: case study Colombia. Ricardo Quijano, National University of Colombia.

3 Rural electrification in the municipality of Coban, department of Alta Verapaz (Guatemala), in collaboration with the Spanish NGO Energy Without Borders and wrote by students of the M.Sc. Renewable Energy and Environment (Industrial and Electrical Engineering, Technical University of Madrid) National Renewable Energy Resources Laboratory, developed by the Institute of Electrical Research of Mexico. This permanent demand by Latin America has been one of the main driven forces for our team to decide in making a functional and conceptual change in the rural electrification model, evolving from SOLARGIS methodology to the new IntiGIS Project. III. INTIGIS The rural electrification method presented here aims to define the most competitive technology in every nonelectrified community in the studied region. In order to succeed on this task, several technical and economic variables are considered, as well as estimated loads and energy resource data. All this parameters can be linked to the territory and therefore, GIS represents a valuable tool capable of representing and modelling the large amount of required data, based on the integration of both cartographic and numeric data. Several technology systems capable of meeting the existing demand are compared, based on renewable energy sources as well as on fossil fuels, individual as well as central systems. The competitiveness of the technologies in every community is measured in terms of its Levelized Electric Cost (LEC), which expresses the cost of producing electricity in /kwh. The cost value includes investment, installation, operating and maintenance and the costs of a required infrastructure. For costs having a non-annual basis, a yearly value considering the lifetime of that particular equipment is used, defined by the introduction of the actualization factor.the output of the model is the definition of the most competitive technology in each location. In this section of the paper, we will focus on the rural electrification model that our group, gtiger, has developed. Firstly, we will describe how the methodology was designed within a European project by several Research Centers in the middle nineties. In the second part, we will discuss the improvements made in relation to uncertainties management, which as a result made the model much more stable. Later, the recent changes, along with the last applications of the GIS approach in Latin-American countries, will be presented. A. Middle nineties: SOLARGIS The SOLARGIS methodology was designed by a consortium of European Research Centers within the EU JOULÉ Program [10]. The mayor goal of SOLARGIS project (Integration of renewable energies for decentralized electricity production in regions of EEC and developing countries), was the demonstration of GIS viability in contributing to the RES integration in rural electrification programs. It also aimed to develop the needed tools to evaluate the renewable energy technologies potential and to conduct several regional studies. SOLARGIS considered two main types of electrification systems: stand alone systems for the electrification of isolated houses (based on the used of PV, diesel or wind) and hybrid systems for the electrification of small villages. The comparison of the former was made on the basis of the cost of the produced electricity for a given demand, which was also compared to the cost of connecting the villages to the existing Medium Voltage (MV) grid. The first step of the analysis was the construction of a regional database that gathered information related to the locally available wind and solar resource, the electricity demand to be covered and its spatial distribution, the location of the existing electric grid, the terrain characteristics, aerial photography, GPS data, etc. After all the information was collected, the Geographical Information System (GIS) and a set of technical and economical evaluation tools linked to the GIS database were used to introduce the defined constrains and to perform the analysis. These constrains were mainly based on the capacity factor, which was defined on the basis of a technical and environmental assessment. Using the tools available within the GIS environment and according to the established rules, High Potential Areas were highlighted (Fig. 1, left). Later and focusing on these areas, both the regional potential and integration studies were performed at a local scale. The local scale studies were not elaborated within JOULE program but were developed by the different Figure 1. SOLARGIS model evolution: first versus second version.

4 Figure 2. Application to Lorca. Best electrification system. participants. This version was developed using a UNIX platform, with Arc Macro Language (AML), the ArcINFO language. B. 2000: SOLARGIS II The collaboration established between CIEMAT and UPM (Technical University of Madrid) stood the framework for a significant improvement in SOLARGIS methodology. The objective of this project was to minimize and/or to control the uncertainties through the in depth study of the technical and economic parameters involved, focusing on load treatment, results control and interface design. At this stage, the demand characterization became the fundamental axis and the methodology was fully implemented in a GIS environment (Fig. 1, right). This new conception of the model was tested in Lorca municipality (Murcia, Spain) because this region had a significant amount of isolated houses not connected to national grid and also because there were previous assessment studies about wind and solar resources made by CIEMAT. Besides the definition of a new methodological structure, the result of the project (Fig. 2) showed the spatial distribution of the most competitive technologies (PV, wind, connection to existing grid, individual and central diesel) in the studied area. Special mention needs to be paid to the spatial sensitivity analysis (SSA) implemented within this version of SOLARGIS methodology [11]. The SSA, used to check the stability of the results, was based on three stages. The first one included the determination of the main influencing parameters by a sensitivity analysis of each technology LEC values. The second one focused on the spatial dimension, using the parameters found in the previous stage and assessing how its value change influenced the distribution of rural electrification potential. Finally, the third one was the study of the spatial behavior of the previous stage in order to determine the stability of the obtained results. In Fig.3 an example of SSA in Lorca is presented. In the upper graph, it can be noticed how an increase in the demand value (represented on the X axis, value equals to 1 means reference demand value) would lead to the renewable energy technologies competitiveness loss. In the bottom maps, the spatial distribution of the most competitive technologies with two different demand values (the reference value and a 45% growth) is represented. C. IntiGIS Nowadays, gtiger keeps on working in the development of SOLARGIS concepts in the framework of IntiGIS Project. The main goal of this project is to define a more dynamic, flexible, interoperable and modular tool. This new approach includes innovations in methodological aspects as well as the incorporation of new renewable technologies, the simplification of required parameters, the design of a friendly user interface windows based, the feasibility analysis of a web service and the application to new areas, specially to Latin America countries like Cuba, Guatemala or Colombia. We are also working effortful in the adaptation of the software to the new ARCGIS TM concept and in the implementation of a SSA module. We would like to conclude this section presenting the application of IntiGIS model to a rural electrification study in a Cuban municipality. The aim of this study was to define which technology is the most appropriate to be adopted by particular group of un-electrified communities, consistently with the main objectives of IntiGIS methodology, but also to adjust the whole process to the particularities of the Cuban context. Before 1959, the date when actual government took power, only 56% of the total population in the island had access to electricity. In 2002, this figure increased to more than 95%. However, the dependence upon imported oil and the fall of Socialist Block in 1991 have driven to an important energetic crisis. In 2004, a new crisis affected the National grid system (SEN) caused by a major breakdown in the main thermal power plants, high fuel consumption rates, and the bad conditions in transmission and distribution lines. In order to overcome the crisis and minimize the electric blackouts, the Government placed diesel generators in Figure 3. Most competitive technology for rural electrification in Lorca (Spain). Demand spatial sensitivity analysis.

5 almost 70% of the municipalities. Guamá, located in the South East of the island, was the chosen municipality to perform the analysis, mainly due to two related facts: its remoteness and its electrification rate. Guamá has less than inhabitants and 132 communities, and while 20% of the communities are connected to the national grid, half of the communities are still un-electrified, representing almost 12% of total population. The structure of the tool is linear. Cartographic and numeric input data must be provided in order to calculate the capacity factor firstly and the LEC secondly. At this stage, the GIS performs spatial analysis using its cartographic functions. The output data reflects the most competitive technology to be adopted in the considered communities. The entire application development has been made with ArcGIS software. 1) Geographical Database To be able to define the most appropriate technology, the software requires several input data. All the cartographic information is implemented into geographical surfaces, each composed of a meshed structure of basic cells (grid) with a 500x500m spatial resolution. The required input surfaces are: distances to the existing MV network, household density and solar radiation. In order to assess the distance to the existing grid, information from GTOPO30 digital elevation model and MV digitalized network were used. The slope was calculated and used as a cost layer in order to approximate the results to real distance (Fig. 4a). a) b) c) Figure 4. Geographical input data. a) distances to MV grid; b) households per community; c)global solar annual radiation. The number of inhabitants per community and the exact position of every community in Guamá was defined in earlier studies [12](Fig. 4b). The global annual solar irradiation data was obtained from SWERA project, freely available from their webpage [13]. These data provide monthly and annual average daily total solar resource expressed in terms of kw/m 2 per day for each month with a resolution of 10 by 10 km on a flat surface. The solar data in tilted surface was calculated through a routine implemented in MATLAB (Fig. 4c). 2) Load Data The rural load per household was defined in previous studies [12] on the basis of interviews to the inhabitants of already electrified communities. Considering number of appliances, power consumption and ratio of use, the average consumption per household was obtained: 400Wh in the case of communities electrified by diesel generators and 900Wh for those connected to the national grid. These values have been taken as the input load values, the first one to size diesel technologies and the last to size grid extension and photovoltaic systems. Both values reflect low load factor, characteristic of rural settlements in developing countries. In the case of diesel powered communities, constrains in fuel availability are also reflected by the even lower domestic consumption. 3) Technology characterization and LEC calculation Several technology systems capable of meeting the existing demand are compared at regional scale in terms of LEC value: individual systems to electrify single households (PV and diesel) and central systems to electrify communities (diesel and connection to the existing grid). Some technical and economic values need to be defined. Those values are related to efficiencies, fuel consumption, fuel price, electric tariff, batteries parameters and also the initial investment and O&M costs as well as lifetime for every feasible technology. The chosen values have been defined according to previous studies performed in the Cuban context, similar analysis, technological state and experimental values. The determination of the installed power for each type of system is based on the calculation of the capacity factor. The next stage of the methodology is to obtain the LEC (expressed in /kwh) in order to determine the cost associated with the generation of electrical power from the resources to meet a particular demand. The cost value includes investment, installation, operating and maintenance and the costs of a required infrastructure. For costs having a non-annual basis, a yearly value considering the lifetime of that particular equipment is used applying 4% as the actualization rate. Once the GIS has calculated all the needed information layers (capacity factors, costs, etc.) spatial analysis functions are implemented in order to define the most competitive technology in every remote site. It is not just the cost per kwh that makes a technology the most competitive one in economic terms, but also the cost of those technologies in competition with it.

6 In Guamá, the comparison of obtained LEC values showed a very high potential of remote sites to be electrified by means of photovoltaic systems: in 54 communities out of 58, individual photovoltaic systems represents the most competitive way of electrifying the households in terms of LEC value. The four remaining sites were suggested to be connected to the existing grid. Although in the rural electrification analysis performed for Guamá municipality just four systems were included, more technologies can be introduced in the analysis. For example, hydropower potential in the area is known to be high. However, it was not included in the analysis due to the lack of input data, although the flexibility of the language and the variety of implemented functions in the GIS would have permitted the introduction of other systems. 4) Spatial Sensitivity Analysis Although all the parameters and data included on the analysis were defined on the basis of state of the art, interviews and bibliography research, they are always affected by uncertainties. As the sources of uncertainty can not be eliminated or fully controlled, a sensitivity analysis would minimize their impact through the examination of how variations on input parameters affect the numerical results and technology ranking. The performed sensitivity analysis showed the impact on technology competitiveness than load changes could have. The variation on the demand did not produce a significant change on PV technology, but it lost competitiveness as long as the rest of technologies achieve lower prices. Connection to MV grid LEC value increases when the demand decreases. Individual and central diesel technologies were clearly affected by the growing demand, and decreased equally until a reduction of more than 80% when a high demand of 2700Wh is considered. Therefore, the increase in the demand can lead to the disappearance of the PV potential by means of making non-renewable technologies more competitive. IV. CONCLUSIONS In this paper, we tried to enhance the importance of renewable energies in planning a sustainable energy supply in rural areas, providing long term and stable access to electricity. The spatial characteristics of RES make GIS an especially adequate tool that could be used in their analysis and decision making process. In order to justify this idea, we have presented some of the existing applications developed within GIS environment. gtiger actively participates in the design and execution of projects focused on Latin American region. IntiGIS methodological development must be highlighted as a good example of GIS tool to promote the integration of renewable energies in rural electrification. Finally, we would like to emphasize two ideas: the role that could be played by GIS in the deployment of renewable energies and the necessity of adaptation of this type of applications to the new developments and trends in Geographical Information Technologies. REFERENCES [1] IEA, World Energy Outlook 2006, [2] J. Dominguez and J. Amador, "Geographical information systems applied in the field of renewable energy sources," Computers & Industrial Engineering. A Cluster on Planning and Management of Energy and Infrastructure Engineering Projects, vol. 52, no. 3, 2007, pp [3] F. J. Ariza Lopez, R. Lopez, and A. Lopez Pinto, "Territorial competitiveness of the stand alone photovoltaic systems versus grid electricity supply. A method and a study based on geographical information systems," Sol Energy, vol. 61, no. 2, 1997, pp [4] M. Muselli, G. Notton, P. Poggi, and A. Louche, "A Geographical Information System for the integration of stand-alone PV systems in remote areas," Proc. 14th European Photovoltaic Solar Energy Conference, 1997, pp [5] R. Fronius and M. Gratton, "Rural electrication planning software (LAPER)," IEE Conference Publication, vol. 5, no. 482, 2001, pp. [6] J. Byrne, A. Zhou, B. Shen, and K. Hughes, "Evaluating the potential of small-scale renewable energy options to meet rural livelihoods needs: A GIS- and lifecycle cost-based assessment of Western China's options," Energy Policy, vol. 35, no. 8, 2007, pp [7] C. Tiba, et al., "A GIS-based decision support tool for renewable energy management and planning in semi-arid rural environments of northeast of Brazil-general description and methodology," Proc. ISES Solar World Congress 2007: Solar Energy and Human Settlement, Tsinghua University Press, 2007, pp [8] O. Masera, A. Ghilardi, R. Drigo, and M. Angel Trossero, "WISDOM: A GIS-based supply demand mapping tool for woodfuel management," Biomass Bioenergy, vol. 30, no. 7, 2006, pp [9] I. Pinedo-Pascua, Aplicación de los Sistemas de Información Geográfica a la integración de las energías renovables en la producción de electricidad en las comunidades rurales. Caso de estudio: electrificación del municipio cubano de Guamá, CIEMAT, 2007, p. 87. [10] Solargis-Team, Solargis Handbook. Guidelines for the elaboration of regional integration plans for decentralized electricity production with renewable energies, Final report, European Commision., [11] J. Amador and J. Dominguez, "Spatial analysis methodology applied to rural electrification," Renew Energy, vol. 31, no. 10, 2006, pp [12] A. Shiota, Recommended Guidelines for the use of renewable energy in rural electrification, Japan International Cooperation Agency (JICA), [13] SWERA-Project, "Data for solar and wind renewable energy," Book Data for solar and wind renewable energy, Series Data for solar and wind renewable energy, SWERA-Project, 2001, pp.