杨悦, 陈宇航, 成龙, 孙玮澳, 顾欣然, 郜佳兴, 单继忠. 考虑节点功率储备与GIN中心性的主动配电网动态集群电压控制[J]. 电网技术, 2024, 48(2): 618-629. DOI: 10.13335/j.1000-3673.pst.2022.2520
引用本文: 杨悦, 陈宇航, 成龙, 孙玮澳, 顾欣然, 郜佳兴, 单继忠. 考虑节点功率储备与GIN中心性的主动配电网动态集群电压控制[J]. 电网技术, 2024, 48(2): 618-629. DOI: 10.13335/j.1000-3673.pst.2022.2520
YANG Yue, CHEN Yuhang, CHENG Long, SUN Weiao, GU Xinran, GAO Jiaxing, SHAN Jizhong. Power Reserve and GIN Centrality of Buses Considered Dynamic Cluster Voltage Control of Active Distribution Networks[J]. Power System Technology, 2024, 48(2): 618-629. DOI: 10.13335/j.1000-3673.pst.2022.2520
Citation: YANG Yue, CHEN Yuhang, CHENG Long, SUN Weiao, GU Xinran, GAO Jiaxing, SHAN Jizhong. Power Reserve and GIN Centrality of Buses Considered Dynamic Cluster Voltage Control of Active Distribution Networks[J]. Power System Technology, 2024, 48(2): 618-629. DOI: 10.13335/j.1000-3673.pst.2022.2520

考虑节点功率储备与GIN中心性的主动配电网动态集群电压控制

Power Reserve and GIN Centrality of Buses Considered Dynamic Cluster Voltage Control of Active Distribution Networks

  • 摘要: 为应对大规模分布式光伏(photovoltaic,PV)接入引起的主动配电网电压越限问题,降低控制策略的时序复杂性,提出一种考虑节点功率储备与节点影响力(global importanceof each node,GIN)的主动配电网动态集群电压控制方法。首先,通过考虑系统各节点的功率储备度,定义聚类算法的电压灵敏度-功率储备度(voltage sensitivity-power reserve,VS-PR)综合电气距离量度。进而,以GIN算法改进亲和力传播(affinity propagation,AP)聚类算法,实现网络集群划分与主导节点选取。然后,建立主动配电网集群电压控制模型,并通过动态粒子群算法(dynamic particle swarm optimization,D-PSO)进行模型求解。最后,通过建立基于MATLAB 2021b平台的IEEE 33节点仿真算例对比分析,验证了所提动态集群划分与电压控制方法的正确性和有效性。

     

    Abstract: To deal with the voltage over-limit problem of active distribution network caused by large-scale distributed photovoltaic (PV) access and reduce the time complexity of the control strategy, a dynamic cluster voltage control method considering power reserve and global importance of each node (GIN) in active distribution network was proposed. First, by considering the power reserve of each bus in the system, the voltage sensitivity-power reserve (VS-PR) comprehensive、electrical distance measure of the clustering algorithm is defined. Furthermore, the GIN algorithm is used to improve the affinity propagation (AP) clustering algorithm to realize network cluster division and dominant bus selection. Then, the active distribution network cluster voltage control model is established, and the model is solved by dynamic particle swarm optimization (D-PSO). Finally, the correctness and effectiveness of the proposed dynamic cluster division and voltage control method are verified by establishing a comparative analysis of IEEE 33-bus simulation examples based on the MATLAB 2021b platform.

     

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