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Geolocation of photovoltaic farms using Geographic Information Systems (GIS) with Multiple-criteria decision-making (MCDM) methods: Case of the Ecuadorian energy regulation

Authors: Villacreses, Geovanna; Martínez Gómez, Javier; Jijón, Diego; Cordovez, Martin;

Geolocation of photovoltaic farms using Geographic Information Systems (GIS) with Multiple-criteria decision-making (MCDM) methods: Case of the Ecuadorian energy regulation

Abstract

Human needs and their production processes require energy services to be developed. In recent years, there has been a great interest in counteracting the use of fossil fuels to satisfy these needs. As part of the worldwide proposed initiatives, there is the use of renewable resources. In Latin America, renewable energy represents a large share of electric energy generation sources. In the case of the Ecuadorian energy regulation, it is necessary to generate at least 1 MW to be considered as a solar farm. Under this framework, Ecuador has a project for installing 91 photovoltaic power plants, fifteen of which will be solar farms and the rest solar power plants with relatively low generation capacity. Currently, in Ecuador, photovoltaic projects are randomly distributed in the territory which shows a lack of adequate criteria for their location. The first step to promote the use of solar sources is identifying the potential, which can be estimated with the use of spatial tools such as Geographic Information Systems (GIS) with Multiple-criteria decision-making (MCDM). This research aims to locate appropriate sites for installing photovoltaic solar farms based on the Ecuadorian energy regulation and combining GIS with MCDM techniques. Thus, nine factors and four restrictions were used for the analysis. Factors were weighted using the Analytic Hierarchy Process method. Once weighted, seven MCDMs were applied to select sites with solar potential. Subsequently, an analysis of seven results was performed using the Pearson correlation coefficient, followed by the absolute error analysis. By the coefficient of Pearson, it is demonstrated that there are methods with a high correlation between them. It is explained by the fact that they have many pixels with similar values, but these values are independent of geographical location. Regarding the results, Loja and part of the provinces in the center north of the country, Pichincha, Santo Domingo de los Tsáchilas, and Cotopaxi are the most adequate because of its great global solar radiation, wind speed, and temperature to cold the solar panels. Universidad International SEK

Country
Spain
Keywords

Geolocation, Solar farms, Geographic Information Systems (GIS), Energías renovables/Energías alternativas, TK1-9971, Multiple criteria decision making (MCDM), Alternative energies, Electrical engineering. Electronics. Nuclear engineering, Multicriteria evaluation (MCE)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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