Solar Power Plant Location Selection Problem Using the ELECTRE-III Method in a Pythagorean Neutrosophic Programming Approach: A Case Study on Green Energy in India

India has set an ambitious target of generating 500 GW of renewable energy capacity from non-fossil fuel sources by 2030. It has also committed, under the United Nations Framework Convention on Climate Change (UNFCCC), to reducing carbon emissions by one billion tonnes by the end of the decade, as announced at the COP26 conference held in Glasgow in November 2022. Researchers are continually searching for inexhaustible and affordable energy sources. Solar energy is among the greenest and cleanest sources of energy. The most important factor in utilizing solar energy is the location of the solar power plant. The main objective of this study is to find the best location for a new solar power plant in a specific region called the Bundelkhand region of Uttar Pradesh in India. Here, we offer an extension of the ELECTRE-III method as a two-phase Pythagorean neutrosophic elimination and choice translating reality (PN-ELECTRE-III) method to adapt with fuzzy, ambiguous, unsure, and indeterminate criteria. The Pythagorean neutrosophic numbers (PNNs) are used by the group decision support system of PN-ELECTRE III to measure the performance of the alternatives. The options are entirely outclassed in the subsequent stage in view of the past stage's evaluations of them. By defining PNN, we describe the technique of indifference threshold, preference threshold, and veto threshold functions, which provide a more stable basis to drop outranking relations. By calculating the concordance credibility, discordance credibility, and net credibility degrees of each alternative, the ranking module of the PN-ELECTRE III approach is made simpler. In order to confirm the applicability of the strategy suggested in this paper, the location selection problem for solar plants is finally solved.