An Integrated GIS–MCDM Framework Using BWM, SWARA, and MARCOS for Optimal Solar Power Plant Site Selection in Fars Province - Iran

Abstract. The transition toward renewable energy sources is essential for achieving environmental sustainability and mitigating climate change. Among various alternatives, photovoltaic (PV) solar energy stands out due to its high efficiency, low environmental impact, and vast potential for electricity generation. This study presents an integrated GIS based multi-criteria decision-making (MCDM) framework to identify optimal locations for solar power plant development in Fars Province, Iran. Nine spatial and environmental criteria including direct normal irradiation (DNI), photovoltaic potential, temperature, rainfall, slope, elevation, and distances from roads, faults, and urban areas were considered. To determine the relative importance of the criteria, two advanced weighting methods, Best Worst Method (BWM) and Stepwise Weight Assessment Ratio Analysis (SWARA), were applied, and their results were fused using the Dempster-Shafer evidence theory to enhance decision reliability. The weighted criteria were then integrated through the MARCOS model to produce a comprehensive land suitability map. The results indicate that approximately 39% of the study area falls into the high and very high suitability categories for solar power plant installation. The proposed hybrid framework effectively combines expert judgment and quantitative analysis, offering a reliable and replicable model for sustainable solar energy planning and decision making in similar regions.