Optimal planning method of multi-energy storage systems based on the power response analysis in the integrated energy system

被引:5
|
作者
Gao, Mingfei [1 ]
Han, Zhonghe [1 ,2 ]
Zhao, Bin [1 ,4 ]
Li, Peng [2 ,3 ]
Wu, Di [1 ,2 ]
Li, Peng [2 ,3 ]
机构
[1] North China Elect Power Univ, Sch Energy Power & Mech Engn, Dept Power Engn, Baoding 071003, Hebei, Peoples R China
[2] North China Elect Power Univ, Hebei Key Lab Low Carbon & High Efficiency Power G, Baoding 071003, Hebei, Peoples R China
[3] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding 071003, Hebei, Peoples R China
[4] Changsha Univ Sci & Technol, Coll Energy & Power Engn, Changsha 410114, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-energy storage system; Integrated energy system; Optimal planning; Power response; Storage type selection; OPTIMIZATION;
D O I
10.1016/j.est.2023.109015
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 application of Integrated Energy Systems (IES) in establishing low-carbon, safe, and efficient energy supply systems has gained significant attention in recent years. However, as an energy stability link in IES, there is a lack of mature theoretical methods for energy allocation and optimal planning in the current multi-energy storage system (MESS) research. Hence, this paper proposes a method for configuring the capacity and selecting storage types in MESS within the IES. By considering the power response characteristics of different storage media, a combined ESMD-MPSO model is established that aims to enhance the economy and extend the service life of MESS. The model could allocate the power to the energy storage devices based on their power response capabilities and economic evaluation. Additionally, MESS application scenarios in both islanded and grid-connected IES are established. Highly adaptable energy storage devices are selected using the Analytic Hierarchy Process and the Fuzzy Comprehensive Evaluation method, resulting in four different multi-energy storage schemes for analysis. The results demonstrate that the method enables the determination of cost-optimal energy storage combination and capacity configuration for both scenarios. Furthermore, compared to existing methods, the approach achieves a 22.1 % and 9.6 % improvement in annual average costs for the two scenarios. This research could provide guidance for the planning and development of multi-energy storage systems within the IES.
引用
收藏
页数:17
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