LOCATION INDICATION FOR PHOTOVOLTAIC SOLAR POWER PLANTS BASED ON CRITERIA APPLIED IN A GEOGRAPHIC INFORMATION SYSTEM
A SYSTEMATIC REVIEW
DOI:
https://doi.org/10.59627/cbens.2024.2447Keywords:
Renewable energy, Multicriteria decision support (MDS), Parsifal SoftwareAbstract
In the last decade, due to the decrease in the price of photovoltaic modules, there has been an exponential growth in the number of installations of Photovoltaic Solar Generating Plants (PVGPs) worldwide, increasing from 136.57 GW (2013) to 1,046.61 GW in 2022. However, due to the large amount of land required for these installations, research in different countries has highlighted the importance of carrying out analyses that incorporate different criteria to identify the most suitable locations for the construction of these systems. This article systematically reviews research that applies the Multicriteria Decision Support (MDS) methodology combined with a Geographic Information System (GIS) to identify the location of UFVs. The aim is to understand the general context of these studies, which MDS methods and criteria are most frequently used to support this decision-making process. For this purpose, the databases Scopus, Web of Science and ScienceDirect were selected, from 2014 to September 2023. The material was systematized using Parsifal software and, after evaluation, 38 articles were selected for data extraction. The results show that the Asian continent has conducted the largest number of studies in this field. In addition, the Analytical Hierarchy Process (AHP) AMD method has been the most widely used, while technical and economic issues are the criteria generally considered most relevant in site selection. Finally, among the gaps identified, it was noted that the methodology reviewed has been applied with greater emphasis in areas of smaller territorial extension and that, despite the frequent use of the AHP method, there are several other AMD methods that could be better explored. It is also worth noting that the social criterion was little addressed in the studies analyzed, despite its relevance to the tripod of environmental, social, and economic sustainability.
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References
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Fard, M. B., Moradian, P., Emarati, M., Ebadi, M., Chofreh, A. G., Klemes, J., 2022. Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province. Renewable and Sustainable Energy Reviews, v. 169, p. 112923.
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Gomes, L. F. A. M.; Gomes, C. F. S., 2019. Princípios e métodos para tomada de decisão: enfoque multicritério. 6. ed. São Paulo: Atlas, p. 360.
Gomes, R. C., Bias, E. S., 2018. Integração do Método AHP e SIG como instrumento de análise do nível de conservação ambiental em bacias hidrográficas. Geociências. São Paulo, SP, v. 37, n.1, p. 167 – 182.
Gül, M., Lo, H. W., Yücesan, M., 2021. Fermatean fuzzy TOPSIS-based approach for occupational risk assessment in manufacturing. Complex & Intelligent Systems, v.7, p. 2635-2653.
Guler, D., Charisoulis, G., Buttenfield, B. P., Yomralioglu, T., 2021. Suitability modeling and sensitivity analysis for biomass energy facilities in Turkey. Clean Technologies and Environmental Policy, v. 23, p. 2183–2199.
Haddad, B., Díaz-Cuevas, P., Ferreira, P., Djebli, A., Juan Pedro Pérez, J. P., 2021. Mapping concentrated solar power site suitability in Algeria. Renewable Energy, v. 168, p. 838-853.
