Multi-criteria decision making for solar site selection in Punjab, India: An evaluation of site suitability using hybrid MCDM techniques towards the goal of sustainable energy development
Tanu Sharma, Amit Sarin
Abstract
The rising energy demand, coupled with the necessity to shift to cleaner energy sources, has made solar energy a pivotal solution for sustainable development. However, identifying optimal sites for solar installations is a complex task that requires the evaluation of multiple, often conflicting, criteria. While Punjab, India, possesses substantial solar potential, systematic and data-driven approaches to identify optimal solar sites remain limited. To address this gap, the present study is the first to apply a hybrid Multi-Criteria Decision-Making (MCDM) framework for solar site selection in Punjab, India, while also integrating underexplored social and economic factors. A comprehensive set of 14 criteria—spanning climatic, technical, economic, environmental, and social dimensions—was used to evaluate seven potential sites: Amritsar, Ludhiana, Patiala, Bathinda, Jalandhar, Mansa, and Gurdaspur. The Analytic Hierarchy Process (AHP) was employed to assign weights to these criteria based on their relative importance. These AHP-derived weights were then integrated with four advanced MCDM techniques—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), Elimination and Choice Expressing Reality (ELECTRE), and Data Envelopment Analysis (DEA)—to rank the alternative solar sites. The results indicated that Bathinda and Mansa consistently emerged as the top-ranked locations due to their high solar irradiance, low land costs, and proximity to infrastructure. Patiala and Gurdaspur also performed well, offering balanced socio-environmental benefits, whereas Amritsar and Ludhiana ranked lower across all methods. AHP-derived weights highlighted solar irradiance (27.0%), land cost (16.8%), and transmission proximity (13.8%) as the most influential factors. To assess the consistency and reliability of the rankings generated by the four hybrid MCDM methods, rank correlation analysis was performed. The results showed strong agreement among the methods, with Spearman’s coefficients ranging from 0.82 to 0.96 and Kendall’s tau values between 0.62 and 0.91, confirming the robustness of the site selection outcomes. By focusing on Punjab’s unique context and incorporating broader socio-economic dimensions, this work adds novelty to the field. Ultimately, the study provides a reliable decision-support framework for policymakers and investors to identify optimal solar sites in Punjab, thereby contributing to the state’s sustainable energy development.