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基于电气特性分析的中压配电网拓扑变动分段辨识

Segment Identification of Topology Changes in Medium Voltage Distribution Network Based on Electrical Characteristics Analysis
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摘要 针对量测数据不足且大量分布式电源接入的配电网难以进行拓扑结构辨识的问题,提出了一种基于电气特性分析的拓扑结构分段辨识方法,以提高拓扑结构辨识准确度。首先将“超节点”概念引入配电网,通过分析拓扑改变后节点注入功率的变化,确定发生改变的拓扑范围。通过对分布式电源接入时配电网功率传输特性和电压幅值特性的分析,利用双重验证和补充识别辨识分段线路,并采用二次辨识校正末段线路,最后采用循环迭代法识别分段线路连接关系。仿真结果表明所提方法能够提高拓扑辨识准确度,在量测装置允许的误差范围内鲁棒性好。 In order to solve the problem of topology identification in distribution networks with insufficient measurement data and large number of distributed power sources,a segmentation identification method of topology structure based on electrical characteristic analysis is proposed to improve the accuracy of topology structure identification.Firstly,the concept of“super node”is introduced into the distribution network,and the scope of topology change is determined by analyzing the change of node injected power after topology change.Through the analysis of the power transmission characteristics and voltage amplitude characteristics of the distribution network when the distributed generation is connected,the segmented lines are identified by double verification and supplementary identification,and the final line is corrected by secondary identification.Finally,the loop iteration method is used to identify the connection relationship of the segment line.Simulation results show that the proposed method can improve the accuracy of topology identification and has good robustness within the allowable error range of the measurement device.
作者 杨舒航 李诗伟 吴红斌 蒋思成 魏英杰 YANG Shuhang;LI Shiwei;WU Hongbin;JIANG Sicheng;WEI Yingjie(Anhui Province Key Laboratory of Renewable Energy Utilization and Energy Saving,Hefei University of Technology,Hefei 230009;Shanghai Pudong Electric Power Supply Company,State Grid Corporation,Shanghai 200120)
出处 《电气工程学报》 CSCD 2023年第4期217-227,共11页 Journal of Electrical Engineering
基金 国家自然科学基金区域创新发展联合基金(U19A20106) 安徽省自然科学基金(2008085UD10)资助项目。
关键词 配电网 拓扑辨识 电气特性 超节点 分段辨识 Distribution network topology identification electrical characteristics super node segment identification
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