An intuitionistic fuzzy based hybrid decision-making approach to determine the priority value of indicators and its application to solar energy feasibility analysis

Abstract

Solar plant feasibility involves assessing its practicality and viability for successful development and operation. It involves evaluating various factors to determine whether the project is technically, economically, and environmentally feasible. Feasibility analysis considers solar resource availability, site selection, technology options, financial viability, grid integration, regulatory compliance, and potential risks. By conducting a comprehensive feasibility study, developers can determine if a solar plant is a feasible and sustainable solution to generating renewable energy at a specific location. An intelligent mitigation measure is proposed in this paper to control the trade-off by using certain indicators that have the greatest influence on the feasibility of a solar power plant. This study proposes a novel subjective weighting technique known as the Intuitionistic Fuzzy Consistency Method (IF-FUCOM) to achieve the highest degree of precision when considering fuzziness. Intuitionistic Fuzzy Set (IFS) handles imprecise information flexibly. Therefore, the IFS has gained interest from experts and is being applied to various fields, especially decision-making. Furthermore, the study identifies the local weights of alternatives using the Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP). This study proposed a hybrid method, IF-FUCOM-AHP, for determining the global weight. Its robustness and effectiveness are demonstrated by comparing the proposed fuzzy model with three existing hybrid methods and developing a novel index for evaluating solar project feasibility and location. Finally, a scenario analysis and sensitivity analysis of different options are conducted for different solar power plants. The benefit of the suggested approach lies in its IFS utilization. This method resolves the issue by delineating the non-membership and membership degrees of elements within a fuzzy set, while also providing a means to articulate a particular level of uncertainty.