Abstract
Considering the goals of carbon peaking and carbon neutrality, along with their related policies, pumped storage power stations are set to develop quickly in China. The comprehensive performance of pumped storage power stations must urgently be evaluated, which can help investors in decision making and provide a reference for policymakers. In this paper, a hybrid novel fuzzy multicriteria decision-making (MCDM) method combining the fuzzy best worst method (BWM) and fuzzy TOPSIS was proposed for the comprehensive performance evaluation of pumped storage power stations in China. The fuzzy BWM was utilized to determine the criteria weights describing the comprehensive performance of pumped storage power stations, while the fuzzy TOPSIS was used to rank the comprehensive performance of pumped storage power stations. The index system for the comprehensive performance evaluation of pumped storage power stations in China incorporated economic, social, and environmental aspects. The comprehensive performance of four pumped storage power stations in China was empirically evaluated using the proposed hybrid novel fuzzy MCDM method, and the results indicate that pumped storage power station PSPS2 exhibited the best comprehensive performance, followed by pumped storage power stations PSPS1 and PSPS4, whereas pumped storage power station PSPS3 had the worst comprehensive performance. A sensitivity analysis and comparative analysis were also conducted. The results indicate that the proposed hybrid novel fuzzy MCDM method, combining the fuzzy BWM and fuzzy TOPSIS for comprehensive performance evaluation of pumped storage power stations, is robust and effective.
Highlights
Many countries have proposed the development goal of carbon neutrality
A variety of common multicriteria decision-making (MCDM) methods have important application value in alternative ranking, such as Multi-Attributive Border Approximation area Comparison (MABAC), Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS), Complex Proportional Assessment (COPRAS), Multi-Attributive Ideal–Real Comparative Analysis (MAIRCA) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI), and different methods have their own advantages and disadvantages
Empirical analysis focusing on four pumped storage power stations in China was performed, and the results indicate that the pumped storage power station PSPS2 has the best comprehensive performance, followed by the pumped storage power station PSPS1 and PSPS4, and the pumped storage power station PSPS3 has the worst comprehensive performance
Summary
Many countries have proposed the development goal of carbon neutrality. To actively address climate change, China proposed the goals of carbon peaking and carbon neutrality in October 2020, with the aim of peaking CO2 emissions before 2030 and neutralizing CO2 emissions before 2060 [1]. One contribution of this paper is its proposal of a hybrid novel fuzzy MCDM method for the comprehensive performance evaluation of pumped storage power stations, which combines the fuzzy best worst method (BWM) and the fuzzy technique for order preference by similarity to an ideal solution (TOPSIS). The former is used to determine the weights of the comprehensive performance evaluation criteria of pumped storage power stations, which allows the ambiguity and intangibility of decision makers to be considered, whereas the latter is employed to rank the comprehensive performance of pumped storage power stations. The remainder of this paper is structured as follows: Section 2 presents the literature review; Section 3 builds the comprehensive performance evaluation index system of pumped storage power stations; Section 4 introduces the proposed hybrid novel fuzzy MDCM method for the comprehensive performance evaluation of pumped storage power stations, which includes fuzzy BWM and fuzzy TOPSIS; Section 5 conducts an empirical analysis of four pumped storage power stations in China; Section 6 discusses the results; Section 7 concludes the paper
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