Optimal configuration of energy storage in an active distribution network based on improved multi-objective particle swarm optimization

被引:0
|
作者
Yan Q. [1 ]
Dong X. [1 ,2 ]
Mu J. [1 ]
Ma Y. [1 ]
机构
[1] College of Electrical Engineering, Shaanxi University of Technology, Hanzhong
[2] Department of Electrical Engineering, Tsinghua University, Beijing
关键词
active distribution network; energy storage system; grid vulnerability; multi-objective particle swarm optimization; optimal configuration;
D O I
10.19783/j.cnki.pspc.211106
中图分类号
学科分类号
摘要
The use of energy storage systems (ESS) can guard against many hazards caused by distributed power sources joining the distribution network, and the reasonable configuration of ESS is a prerequisite for their effective application. In this paper, considering the coupling between planning and operation, a multi-objective site selection and capacity model for ESS in a distribution network with distributed generation (DG) is established from three aspects: grid vulnerability measurement indicators, active power loss, and ESS-rated capacity. A reformative multi-objective particle swarm arithmetic is devised. The arithmetic introduces a quasi-adversarial learning strategy in the population update process to enhance the coverage and convergence rate of the solution, and adopts an adaptive split strategy to separate prematurely clustered particles according to the number of iterations, thereby enhancing the diversity of particles. This has the ability to escape the local optimum while ensuring astringency. Through analysis on the IEEE-33 node power distribution system, the rationality of the proposed model and algorithm in optimizing the location and capacity and operational strategy of distributed energy storage is verified, and it can effectively improve the operating economy and vulnerability of a power grid with a stronger global search capability. © 2022 Power System Protection and Control Press. All rights reserved.
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页码:11 / 19
页数:8
相关论文
共 31 条
  • [1] MIAO Youzhong, LI Shunxin, LEI Weimin, Et al., Reliability evaluation of distribution network with distributed generation considering customer sectors, Journal of Electric Power Science and Technology, 35, 2, pp. 93-99, (2020)
  • [2] ZHANG Ying, KOU Lingfeng, JI Yu, Et al., Hierarchical and partitioned optimal control of distribution networks considering the coordination between energy storage and distributed generation systems, Electric Power, 54, 2, pp. 104-112, (2021)
  • [3] XING Haijun, XIE Baojiang, QIN Jian, Et al., Active distribution network optimal operation considering conservation voltage reduction, Electric Power, 54, 11, pp. 76-81, (2021)
  • [4] TANG Chenghong, LI Shufeng, CHEN Yonghua, Et al., State estimation of active distribution system considering DGs, Guangdong Electric Power, 34, 3, pp. 60-67, (2021)
  • [5] LIU Chang, ZHUO Jiankun, ZHAO Dongming, Et al., A review on the utilization of energy storage system for the flexible and safe operation of renewable energy microgrids, Proceedings of the CSEE, 40, 1, pp. 1-18, (2020)
  • [6] KOU Lingfeng, ZHANG Ying, JI Yu, Et al., Typical application scenario and operation mode analysis of distributed energy storage, Power System Protection and Control, 48, 4, pp. 177-187, (2020)
  • [7] WANG Chengshan, WU Zhen, LI Peng, Prospects and challenges of distributed electricity storage technology, Automation of Electric Power Systems, 38, 16, pp. 1-8, (2014)
  • [8] ZHANG Mingxia, YAN Tao, LAI Xiaokang, Et al., Technology vision and route of energy storage under new power grid function configuration, Power System Technology, 42, 5, pp. 1370-1377, (2018)
  • [9] LI Jianlin, MA Huimeng, YUAN Xiaodong, Et al., Overview on key applied technologies of large-scale distributed energy storage, Power System Technology, 41, 10, pp. 3365-3375, (2017)
  • [10] JIANG Y, KANG L, LIU Y., Optimal configuration of battery energy storage system with multiple types of batteries based on supply-demand characteristics, Energy, (2020)