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ISSN 0254-0096 CN 11-2082/K

太阳能学报 ›› 2022, Vol. 43 ›› Issue (3): 101-110.DOI: 10.19912/j.0254-0096.tynxb.2021-0485

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含储能的三端SOP对主动配电网的潮流优化研究

于文山1, 黎明2, 由蕤1   

  1. 1.青岛大学电气工程学院,青岛 266071;
    2.中国海洋大学工程学院,青岛 266100
  • 收稿日期:2021-05-06 发布日期:2022-09-28
  • 通讯作者: 由 蕤(1984—),男,博士、副教授,主要从事风力发电机组控制、分布式发电与微电网方面的研究。yourui1984@163.com
  • 基金资助:
    山东省重点研发计划(重大科技创新工程)(2019JZZY010902); 山东省自然科学基金(ZR2020ME197); 国家自然科学基金(51761135014)

POWER FLOW OPTIMIZATION STUDY ON ACTIVE DISTRIBUTION NETWORK BASED ON THREE-TERMINAL SOP WITH ENERGY STORAGE SYSTEM

Yu Wenshan1, Li Ming2, You Rui1   

  1. 1. College of Electrical Engineering, Qingdao University, Qingdao 266071, China;
    2. College of Engineering, Ocean University of China, Qingdao 266100, China
  • Received:2021-05-06 Published:2022-09-28

摘要: 提出一种含储能的三端智能软开关(SOP)对主动配电网的潮流优化策略,建立以SOP传输的有功功率、无功功率为决策变量,多种约束条件下配电网总有功损耗最小、电压偏差最小的多目标优化数学模型,采用多目标粒子群优化算法求取全局最优解,对SOP的最优接入位置进行选取,实现主动配电网总有功损耗的降低和电压水平的改善。最后,将不同类型的SOP对改进的IEEE 33节点系统的优化效果进行详对比分析,从配电网的潮流优化、经济效益提升2个方面验证所提优化策略的有效性。

关键词: 储能, 主动配电网, 分布式电源, 多目标粒子群优化算法, 三端智能软开关

Abstract: A power flow optimization strategy of the active distribution network including three-terminal SOP with energy storage system is proposed in this paper. A multi-objective optimization mathematical model, whose decision variables are the SOP active power and reactive power, is built. Under various constraints, the minimum active power loss and minimum voltage deviation are obtained in the distribution network. The multi-objective particle swarm optimization algorithm is used to obtain the global optimal solution. The SOP optimal installation location is selected. The active distribution network active power loss is reduced, and the voltage level is improved. Finally, the optimization effects on the improved IEEE 33-node system from different types of SOP are compared and analyzed in detail. The effectiveness of the proposed optimization strategy is verified in the aspects of the distribution network power flow optimization and economic benefit improvement.

Key words: energy storage, active distribution network, distributed generation, multi-objective particle swarm optimization algorithm, three-terminal soft open point

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