Enhanced site selection for solar power plants utilizing the geographic information system and pythagorean fuzzy analytical hierarchy process method

Abstract

The rising global energy demand and environmental concerns have made the transition to renewable and sustainable energy sources essential. Solar energy is a promising option due to its availability, cost-efficiency, and environmental compatibility. However, the efficiency of solar power plants (SPPs) strongly depends on optimal site selection involving multiple spatial and non-spatial criteria. This study introduces a hybrid approach integrating the Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) with Geographic Information Systems (GIS) to address uncertainty and subjectivity in multi-criteria decision-making (MCDM). Additionally, a comparative analysis between PF-AHP and Intuitionistic Fuzzy AHP (IF-AHP) was conducted, focusing on criterion weights and GIS-based suitability maps. Results show that IF-AHP produces nearly uniform weight distributions, making it less effective at prioritizing key factors such as solar radiation and access to transportation—both essential for efficient and cost-effective SPP planning. Conversely, PF-AHP offers a more differentiated that aligns with expert judgment and literature. The PF-AHP-based suitability map correctly identifies operational SPP regions in Eskişehir (Sivrihisar, Tepebaşı, Günyüzü, and Odunpazarı) as highly suitable. In contrast, the IF-AHP map misclassifies these same regions as poorly suitable, highlighting its limitations in spatial accuracy. The methodology was applied in Eskişehir, Turkey, using criteria such as solar radiation, slope, and proximity to restricted areas. Through GIS-based weighted overlay analysis, approximately 154 distinct areas—covering around 46.47 % of the study area—were identified as suitable for SPP installation. This approach provides a reliable and spatially transparent decision-support tool for sustainable energy planning.