Optimal siting of shared energy storage projects from a sustainable development perspective: A two-stage framework

被引:10
|
作者
Wang, Yaping [1 ]
Gao, Jianwei [1 ]
Guo, Fengjia [2 ]
Meng, Qichen [1 ]
机构
[1] North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
[2] Capital Univ Econ & Business, Sch Management & Engn, Beijing 100070, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Shared energy storage; Optimal siting; Power attraction model; Large-scale group decision making; Sustainable development perspective; Probabilistic uncertain linguistic term sets; GROUP DECISION-MAKING; LINGUISTIC TERM SETS; EXTENDED EDAS METHOD; SITE SELECTION; INFORMATION; STATION; WASPAS; MODEL; PLANT;
D O I
10.1016/j.est.2023.110213
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The rapidly increasing installed renewable energy capacity has drawn greater attention to energy storage technology in China. However, the commercial implementation of energy storage is constrained by several obstacles. One potential solution to overcome these constraints is the shared energy storage model. The optimal location layout plays a crucial role in addressing the strategic decision problem of sustainable development. Therefore, a two-stage multi-criteria decision-making model is proposed to identify the optimal locations of shared energy storage projects in this work. In the first stage, the power attraction model is established to determine the macroscopic layout of shared energy storage. In the second stage, a large-scale group decision making (LSGDM) framework is developed to select the optimal micro location. The empirical study conducted in China reveals that Shandong, Henan, and Hebei provinces exhibit greater power flow attraction, from which eight alternatives are selected as site preferences and evaluated by twenty experts. Based on the improved EDAS method, the evaluation score function values of the eight alternatives are 0.497, 0.5, 0.476, 0.499, 0.507, 0.477, 0.506, and 0.498, respectively. Specifically, A5 in Rao Yang County, Hengshui City and A7 in Qing Long Manchu Autonomous County, Qinhuangdao City are preferred locations. Furthermore, the dependability and stability of the model are illustrated through the sensitivity analysis and comparative analysis. This model not only assists in determining the layout of shared energy storage but also contributes to the theoretical study of geographic information system and LSGDM.
引用
收藏
页数:19
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