Article detail · 2024
GIS-based multi-influencing factor (MIF) application for optimal site selection of solar photovoltaic power plant in Nashik, India
- Year
- 2024
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Environmental Sciences Europe
- Catalog match (ISSN) Environmental Sciences Europe
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Abstract The significant natural energy sources for reducing the global usage of fossil fuels are renewable energy (RE) sources. Solar energy is a crucial and reliable RE source. Site selection for solar photovoltaic (PV) farms is a crucial issue in terms of spatial planning and RE policies. This study adopts a Geographic Information System (GIS)-based Multi-Influencing Factor (MIF) technique to enhance the precision of identifying and delineating optimal locations for solar PV farms. The choice of GIS and MIF is motivated by their ability to integrate diverse influencing factors, facilitating a holistic analysis of spatial data. The selected influencing factors include solar radiation, wind speed, Land Surface Temperature (LST), relative humidity, vegetation, elevation, land use, Euclidean distance from roads, and aspect. The optimal sites of solar PV power plant delineated revealed that ‘very low’ suitability of site covering 4.866% of the study area, ‘low’ suitability of site 13.190%, ‘moderate’ suitability of site 31.640%, ‘good’ suitability of site 32.347%, and ‘very good’ suitability of site for solar PV power plant encompassing 17.957% of the study area. The sensitivity analysis results show that the solar radiation, relative humidity, and elevation are the most effective on the accuracy of the prediction. The validation of the results shows the accuracy of solar PV power plant prediction using MIF technique in the study area was 81.80%. The integration of GIS and MIF not only enhances the accuracy of site suitability assessment but also provides a practical implementation strategy. This research offers valuable insights for renewable energy policymakers, urban planners, and other stakeholders seeking to identify and develop optimal locations for solar energy power farms in their respective regions.
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Citations
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59 citations
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4 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Application of Z-number based fuzzy MCDM in solar power plant location selection problem in Spatial planning 2024
- Application of Z-number based fuzzy MCDM in solar power plant location selection problem in Spatial planning 2024
- Mikroklimatik Farklılıkların Fotovoltaik Panel Verimliliği Üzerine Etkisi: Tipik Meteorolojik Erzurum Yılı İçin Ova İçi ve Yamaç Yerleşimlerinin Karşılaştırmalı Analizi 2026
- Optimum location selection for photovoltaic power plants based on Best-Worst Method: Example of Karatay district Konya, Türkiye 2026