A Multi-Criteria Decision-Making Approach for Energy Storage Technology Selection Based on Demand

Xiaotong Qie, Rui Zhang, Yanyong Hu, Xialing Sun and Xue Chen
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Xiaotong Qie: School of Management, China University of Mining and Technology, Beijing 100083, China
Rui Zhang: School of Management, China University of Mining and Technology, Beijing 100083, China
Yanyong Hu: School of Management, China University of Mining and Technology, Beijing 100083, China
Xialing Sun: School of Management, China University of Mining and Technology, Beijing 100083, China
Xue Chen: School of Management, China University of Mining and Technology, Beijing 100083, China

Energies, 2021, vol. 14, issue 20, 1-29

Abstract: Energy storage technologies can reduce grid fluctuations through peak shaving and valley filling and effectively solve the problems of renewable energy storage and consumption. The application of energy storage technologies is aimed at storing energy and supplying energy when needed according to the storage requirements. The existing research focuses on ranking technologies and selecting the best technologies, while ignoring storage requirements. Here, we propose a multi-criteria decision-making (MCDM) framework for selecting a suitable technology based on certain storage requirements. Specifically, we consider nine criteria in four aspects: technological, economic, environmental, and social. The interval number, crisp number, and linguist terms can be transformed into a probabilistic dual hesitant fuzzy set (PDHFS) through the transformation and fusion method we proposed, and a suitable technology can be selected through distance measurements. Subsequently, the proposed method is applied in a representative case study for energy storage technology selection in Shanxi Province, and a sensitivity analysis gives different scenarios for elaboration. The results show that the optimal selection of energy storage technology is different under different storage requirement scenarios. The decision-making model presented herein is considered to be versatile and adjustable, and thus, it can help decision makers to select a suitable energy storage technology based on the requirements of any given use case.

Keywords: energy storage technology; technology selection; multi-criteria decision making; probabilistic dual hesitant fuzzy set; storage requirement (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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