A Fuzzy Decision-Making Methodology for Assessment of Solar Energy Plant Location Selection Criteria

Abstract

According to the current technical knowledge, Renewable Energy Sources (RESs) have a crucial place for both industry and the environment considering their carbon emission values, risks and damage to the environment compared to fossil fuels and nuclear energy. Among them, Solar Energy (SE) is one of the cleanest RES due to its sustainable production environment and low carbon emission rates. Considering these advantages, Solar Energy Plants (SEPs) also have some disadvantages, such as land use, geographical conditions, and the supply of the components. Through that, SEP location selection is an essential and critical issue for the investors, which is related to many conflicting criteria. Moreover, exact evaluations for these criteria are not realistic when the system's locations and investment ecosystem are considered. Thus, the problem can be regarded as a complex decision-making problem due. Therefore, in this study, a preliminary investigation for calculating the importance of the criteria for the SEP location selection problem is analyzed using the Cognitive Mapping Method (CMM). To involve the uncertainty of the input data in the mathematical operations, Spherical Fuzzy Sets (SFSs) are integrated to increase the flexibility of the proposed method. The proposed method gives the ability to investigate complex relations between the criteria under highly uncertain environment, including indeterminacy and data inconsistency. The proposed methodology is applied to the Türkiye ecosystem, and the criterion "Land Acquisition"is determined as the most important one. © 2022 IEEE.