Selection of Optimal Renewable Energy Resources Using TOPSIS-Z Methodology

Abstract

An innovation of Renewable Energy (RE) sources promises to bring down costs and starts to deliver a clean energy future without compromising reliability. Renewable energy resource selection comes under the domain of multi-criteria decision making (MCDM) problem as it includes multi-conflicting criteria, namely social, technological, environmental, economic, and political. MCDM methodologies are used in order to select preferred alternative resources because of the presence of complexities in energy planning and energy projects. This paper presents an integrated TOPSIS-Z MCDM method for the selection of optimal RE. The pairwise decision matrix is formed by the decision-makers (DM), which is represented in the Z-number, and weights are evaluated. TOPSIS is used to evaluate and rank suitable RE sources. To validate the efficacy of the proposed methodology, Spearman’s Rank Correlation Coefficient (SRCC) is used and the proposed methodology is compared with various other MCDM methods such as ARAS, VIKOR, and COPRAS.