Complex Fuzzy Logic Model for Renewable Energy location Selection

CFLM

Abstract

Renewable energy plays a pivotal role in shaping 21st-century society. Among its various forms, solar energy—convertible into usable power through solar panels—is widely regarded as the most vital, accessible, and cleanest energy source, with minimal adverse impact on the environment. Though, to maximize its benefits, solar energy must be utilized strategically and installed in optimal locations, offering significant opportunities for economic growth and sustainable development. The objective of this paper is to optimize solar energy site selection by employing complex fuzzy logic in conjunction with a Multiple Criteria Decision-Making (MCDM) framework. The approach relies on expert judgment to define complex membership values for each criterion across the alternative and ideal locations. In this approach, complex fuzzy logic was first applied, taking into account the opinions of an expert team to determine complex membership values for the ideal location based on five independent criteria. The same method was then used to determine complex membership values for each alternative. A complex fuzzy distance formula was subsequently applied to identify the optimal solution. Overall, the results demonstrate that integrating complex fuzzy logic, and MCDM provides higher accuracy and effectiveness in identifying optimal solar locations.