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Solar PV power plant site selection using a GIS-based non-linear multi-criteria optimization technique

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Abstract

The ongoing rise in energy consumption imposed serious environmental challenges by using fossil fuels. The use of renewable energy sources is being increasingly explored as a potential answer for achieving sustainable energy production and minimizing adverse environmental effects. In the modern day, photovoltaic (PV) systems are viewed as a possible replacement for fossil fuels as a clean energy source. The installation of solar PV power plants requires vast land and huge investment. Therefore, it is necessary to select a suitable site to achieve maximum efficiency and low cost. A feasible location of photovoltaic (PV) system must consider certain criteria including land restrictions, access to roads, and transmission lines. This study analyzed ten factors grouped into four categories: geographic, technical, economic, and flood susceptibility criterion. The data of each factor is extracted from various governments, United Nation (UN), and non-government organizational bodies. Weights were assigned to ten factors by using a non-linear multi-criteria optimization technique called full consistency method (FUCOM). A geographic information system (GIS) software, ESRI ArcGIS pro, performs the weighted overlay analysis of the ten factors with weighted importance calculated by the above technique. A suitability map is created showing that a total of 2.02% of the country’s area is suitable for PV power plants, which are further divided into five suitability classes. The results highlight the distribution of suitable sites for the construction of solar PV power plant throughout the country. A sensitivity analysis is performed to highlight the impact of the factor on the final suitability map. These findings can promote the future widespread development and application of solar energy resources.

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Contributions

AK: data processing, analysis and writing. YA: conceptualization, methodology and supervision. DP: supervision on statistical analysis, revision, visualization, and editing.

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Correspondence to Dragan Pamucar.

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The authors declare no competing interests.

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Khan, A., Ali, Y. & Pamucar, D. Solar PV power plant site selection using a GIS-based non-linear multi-criteria optimization technique. Environ Sci Pollut Res 30, 57378–57397 (2023). https://doi.org/10.1007/s11356-023-26540-1

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  • DOI: https://doi.org/10.1007/s11356-023-26540-1

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