Applying the ELECTRE III Method for Optimal Site Selection of a Solar Power Plant in Pythagorean Neutrosophic Programming

Abstract India's 2030 renewable energy ambitions have been reduced from 500 gigawatts from non-fossil sources. India accepted its UNFCCC duties before the COP26 summit in Glasgow in November 2022, including the goal of reducing carbon emissions by one billion tons by the end of the decade. As a clean, affordable alternative, solar energy is being explored, therefore choosing the best site for a solar power plant (SSP) is vital. The study application handles imprecise, unclear, and uncertain criteria using preference neighborhood-elimination and choice translating reality (PN-ELECTRE) decision-making (DM). We tackle multi-criteria decision-making (MCDM) problems with imprecise or ambiguous data utilizing this technique. Group decision support and Pythagorean neutrosophic numbers (PNNs) are used in PN-ELECTRE III. A balanced decision-making method is needed to resolve SPP location ambiguity. The suggested DM support system smoothly integrated economic, social, environmental, and technological issues into two phases. The increased demand for renewable energy and the difficulty of finding suitable solar power facility sites prompted the research. The Bundelkhand region of India shows how the recommended technique might help policymakers and investors choose renewable energy. It effectively incorporates several criteria and overcomes inaccurate data. The study found that the proposed technique solves the SPP placement problem.