A novel PROMETHEE method based on GRA-DEMATEL for PLTSs and its application in selecting renewable energies

Abstract

Environmental pollution has become a critical social problem in China. Evaluating and selecting suitable renewable energy sources for a city is vitally essential for its long-term sustainable development. Identifying the key factors that influence the evaluation system is another crucial process. Therefore, we address the evaluation problem using two steps: (1) applying a decision-making trial and evaluation laboratory (DEMATEL) method to analyze the relevant factors and (2) ranking the factors by the preference ranking organization method for enrichment of evaluations (PROMETHEE). As a result, we introduce a new DEMATEL method based on grey relation analysis (GRA) via objective data in a decision matrix. The new method not only avoids the instability of the traditional DEMATEL method by applying experts' subjective opinions to compare two factors but also addresses the challenges faced by decision-makers when making pairwise comparisons when the number of factors is too large. Moreover, because the PROMETHEE method effectively solves complex decision problems, we also propose a new PROMETHEE method concerning probabilistic linguistic term sets (PLTSs) to rank and select suitable renewable energies. To analyze the stability of the decision result, we present a novel mixed-integer linear programming (MILP) method that investigates the ranking results for all the factors simultaneously, rather than using only one as in traditional methods. Finally, we implement our method to evaluate renewable energy options in a western Chinese city, and the results show that our method is effective and reasonable in solving complex decision problems.