Hierarchical Optimal Control Method for Active Distribution Network with Mobile Energy Storage

被引:0
|
作者
Li J. [1 ]
Wang D. [1 ]
Fan H. [1 ]
Yang D. [2 ]
Fang R. [2 ]
Sang Z. [2 ]
机构
[1] State Key Laboratory of Advanced Electromagnetic Engineering and Technology (Huazhong University of Science and Technology), Wuhan
[2] Economic Research Institute of State Grid Hubei Electric Power Co., Ltd., Wuhan
关键词
Active distribution network; Bi-level optimization; Improved quantum particle swarm optimization; Mobile energy storage system; Peak load shifting; Reactive power optimization;
D O I
10.7500/AEPS20211008005
中图分类号
学科分类号
摘要
Mobile energy storage technology has the advantages of strong flexibility and wide application scenarios. In addition to emergency power supply, mobile energy storage technology also has good application prospects in distribution network in peak load shifting, improving power quality, and so on. In view of the optimal operation of the active distribution network with the integration of distributed generation, this paper proposes a hierarchical control strategy for an active distribution network that integrates mobile energy storage dispatch and reactive power optimization by making full use of the daily idle situation of mobile energy storage. The upper-level optimization model integrates the optimal net load variance and total operation cost of mobile energy storage, and the lower-level optimization model considers mobile energy storage dispatch in conjunction with reactive power optimization, with the objectives of minimizing grid voltage deviation, network loss cost and migration cost. In addition, this paper considers that the model has multidimensional nonlinear characteristics, introduces quantum behavior and probabilistic expression characteristics, proposes an improved quantum particle swarm algorithm, adopts quantum bits to encode the current position of particles, and uses quantum behavior evolution equation to realize the search for the optimal position of particles, which improves the convergence speed and the accuracy of the algorithm to find the optimal position. Finally, a simulation analysis is conducted with the IEEE 33-bus distribution system to verify the effectiveness of the proposed control strategy and algorithm. © 2022 Automation of Electric Power Systems Press.
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页码:189 / 198
页数:9
相关论文
共 36 条
  • [1] WANG Yang, Study on optimal operation strategies for active distribution network, (2016)
  • [2] SUN Weiqing, PEI Liang, XIANG Wei, Et al., Evaluation method of system value for energy storage in power system, Automation of Electric Power Systems, 43, 8, pp. 47-55, (2019)
  • [3] XIAO Kaichao, Mobile energy storage planning and scheduling under different scenario in distribution network, (2021)
  • [4] SUN Weiqing, LIU Wei, ZHANG Jie, Collaborative optimization for dynamic reconfiguration of distribution network and mobile energy storage in background of high proportion of renewable energy, Automation of Electric Power Systems, 45, 19, pp. 80-90, (2021)
  • [5] WANG Yufei, ZHENG Yunping, XUE Hua, Et al., Optimal dispatch of mobile energy storage for peak load shifting based on enhanced firework algorithm, Automation of Electric Power Systems, 45, 5, pp. 48-56, (2021)
  • [6] KWON S Y, PARK J Y, KIM Y J., Optimal V2G and route scheduling of mobile energy storage devices using a linear transit model to reduce electricity and transportation energy losses, IEEE Transactions on Industry Applications, 56, 1, pp. 34-47, (2020)
  • [7] SUI Quan, LIN Xiangning, TONG Ning, Et al., Economic dispatch of active distribution network based on improved two-stage robust optimization, Proceedings of the CSEE, 40, 7, pp. 2166-2179, (2020)
  • [8] KIM J, DVORKIN Y., Enhancing distribution system resilience with mobile energy storage and microgrids, IEEE Transactions on Smart Grid, 10, 5, pp. 4996-5006, (2019)
  • [9] RONG S, CHEN X G, GUAN W L, Et al., Coordinated dispatching strategy of multiple energy sources for wind power consumption, Journal of Modern Power Systems and Clean Energy, 7, 6, pp. 1461-1471, (2019)
  • [10] LIN Li, ZOU Lanqing, ZHOU Peng, Et al., Multi-angle economic analysis on deep peak regulation of thermal power units with large-scale wind power integration, Automation of Electric Power Systems, 41, 7, pp. 21-27, (2017)