Putting into practice a decision-making framework for a thorough performance and location evaluation of solar photovoltaic plants in India from distinctive climate zones

Abstract

Solar energy utilization has evolved tremendously in many countries to compete with conventional energy sources due to abundant availability, ongoing module price declines, and efficiency gains. Besides these advantages, most solar power plants continue to underperform due to various technical and environmental factors. Some solar projects in India even failed to meet the generation targets. Hence, to achieve sustainable development goals and be future-ready, solar power plants must be sustainably developed for power generation. One should focus on every sustainable aspect before constructing a powerplant, i.e., proper location selection. This study focuses on this problem and considers seven solar photovoltaic plants from different climatic zones in India to compare their performance and location criteria using fuzzy multi-criteria decision-making methods. Fuzzy Stepwise Weight Assessment Ratio Analysis is used to determine the criteria significance, while Fuzzy COmplex PRoportional ASsessment and Fuzzy ELimination Et Choix Traduisant la REalité (ELimination Et Choice Translating REality) are used to rank the seven solar photovoltaic plants. Given solar photovoltaic plants' high initial investment cost, economic criteria precede all other evaluation criteria in assessment, followed by technical, environmental, and connectivity criteria. The social criteria are neglected here because of the minor societal concerns about deploying solar photovoltaic plants. According to the results, the Unchahar solar photovoltaic plant (from the composite climatic zone) outperforms other selected photovoltaic plants and is determined to be the most appropriate plant. This is due to the lowest levelized cost of energy and lowest total cost for the Unchahar solar photovoltaic plant, as these criteria are the most significant per the study. This study's findings will be useful to energy decision-makers and may serve as a reference for constructing and developing future solar plants. Further, this study will make recommendations for future solar photovoltaic plant development. The study also includes sensitivity analysis to determine the data's robustness. This study is very robust, as the normalized alternative is constant for each criterion, and the ranking remains the same.