程锋,吕干云,李思萱,叶加星,章心因,彭震
CHENG Feng,LYU Ganyun,LI Sixuan,YE Jiaxing,ZHANG Xinyin,PENG Zhen

• 1:南京工程学院电力工程学院
• 2:国网江苏江宁区供电分公司
• 3:江苏方天电力技术有限公司

摘要(Abstract)：

拓扑结构是支撑配电网运行分析与控制决策的基础，易受运行操作影响而频繁变动，现有识别方法多依赖单一量测特征，难以兼顾长期趋势与短时波动特性。为此，提出一种基于双维特征参量的中压配电网拓扑识别方法。该方法从电压序列的变化趋势与波动模态两方面构建特征空间；基于双维特征参量，聚类划分电气距离相近的节点为同一簇；在簇内构建径向基函数核相似性矩阵并结合最大生成树算法生成簇内拓扑；通过簇间节点对的核相似性的阈值判定确定簇间连接关系以实现线路拓扑识别。算例结果表明，该方法能够实现中压配电网拓扑结构的准确识别，且在量测噪声下保持稳定。
The network topology is fundamental to operation analysis and control decision making in distribution networks; however, it changes frequently due to switching operations. Existing identification methods mostly rely on single measurement features and thus cannot simultaneously capture long-term trends and short-term fluctuation characteristics. To address this issue, a topology identification method for medium-voltage distribution networks based on two-dimensional feature parameters is proposed. The method constructs a feature space from two aspects: the variation trend and fluctuation patterns of voltage time series. Based on the two-dimensional feature parameters, nodes with similar electrical distance are clustered into the same group. Within each cluster, a radial basis function(RBF) kernel similarity matrix is constructed, and the intra-cluster topology is obtained using the maximum spanning tree algorithm. The inter-cluster connections are determined by thresholding the kernel similarity between node pairs from different clusters, thereby achieving network topology identification. Case study results demonstrate that the proposed method can accurately identify the topology of medium-voltage distribution networks and remains robust under measurement noise.

关键词(KeyWords)： 中压配电网;拓扑识别;双维特征;径向基函数;最大生成树算法
medium-voltage distribution network;topology identification;two-dimensional feature;RBF;maximum spanning tree algorithm

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金（51577086）;; 江苏“六大人才高峰”项目（TD-XNY004）;; 江苏省高校科研重大项目（19KJA510012）

作者(Author): 程锋,吕干云,李思萱,叶加星,章心因,彭震
CHENG Feng,LYU Ganyun,LI Sixuan,YE Jiaxing,ZHANG Xinyin,PENG Zhen

DOI: 10.19585/j.zjdl.202609009

参考文献(References)：

• [1]夏澍，王乃盾，史媛，等.电缆配电网的线-变-表拓扑异常辨识方法[J].电力系统保护与控制，2019,47(11):44-50.Xia Shu,Wang Naidun,Shi Yuan,et al.Line-transformermeter topology anomaly identification method for cable distribution network[J]. Power System Protection and Control,2019,47(11):44-50.
• [2]刘迪，张强，吕干云，等.基于支路有功功率的配电网拓扑辨识方法[J].电力工程技术，2021,40(3):92-98.Liu Di,Zhang Qiang,Lyu Ganyun,et al.Distribution network topology identification method based on branch active power[J]. Jiangsu Electrical Engineering,2021,40(3):92-98.
• [3]张津铭，赵健，唐维溢，等.动态拓扑下基于终端数据挖掘的配电网异常节点检测[J].智慧电力，2024,52(7):1-9.Zhang Jinming,Zhao Jian,Tang Weiyi,et al. Abnormal node detection in distribution network based on terminal data mining in dynamic topology[J].Smart Power,2024,52(7):1-9.
• [4]陈沛东，曹华珍，何璇，等.中压配电网近邻交互式分布式拓扑辨识算法[J].电力工程技术，2023,42(2):139-146.Chen Peidong,Cao Huazhen,He Xuan,et al.Distributed topology identification algorithm of medium-voltage distribution network based on neighboring interaction[J]. Jiangsu Electrical Engineering,2023,42(2):139-146.
• [5]程嘉诚，刘子琛，王琰迪，等.基于事件触发机制的配电网拓扑-状态联合估计[J].浙江电力，2025,44(9):92-101.Cheng Jiacheng,Liu Zichen,Wang Yandi,et al.Joint topology and state estimation for distribution networks using an event-triggered mechanism[J]. Zhejiang Electric Power,2025,44(9):92-101.
• [6]谭伟涛，彭里卓，章天晗，等.基于半监督对抗学习的配电网动态拓扑开关状态鲁棒辨识[J].电力系统自动化，2025,49(18):43-54.Tan Weitao,Peng Lizhuo,Zhang Tianhan,et al. Robust identification of switch states in dynamic topology of distribution network based on semi-supervised adversarial learning[J].Automation of Electric Power Systems,2025,49(18):43-54.
• [7]张丽，王建，许守东，等.基于XGBoost特征筛选和决策树多标签分类的配电网拓扑辨识方法[J].电网与清洁能源，2025,41(2):10-21.Zhang Li,Wang Jian,Xu Shoudong,et al.A topology identification method for distribution networks based on XGBoost feature selection and decision tree multi-label classification[J]. Power System and Clean Energy,2025,41(2):10-21.
• [8]龙寰，石子晴，赵景涛，等.基于多标签分类与卷积神经网络的配电网拓扑辨识[J].高电压技术，2024,50(10):4520-4529.Long Huan,Shi Ziqing,Zhao Jingtao,et al.Topology identification of distribution network based on multi-label classification and CNN[J].High Voltage Engineering,2024,50(10):4520-4529.
• [9]喻旻，余仁山，林志刚，等.基于FM-EEMD信号分解的站线变关系识别[J].华东交通大学学报，2020,37(1):88-93.Yu Min,Yu Renshan,Lin Zhigang,et al.Substation-linetransformer relationship distinction based on FM-EEMD signal decomposition[J]. Journal of East China Jiaotong University,2020,37(1):88-93.
• [10]黄毕尧，张明，李建岐，等.联合高低频电力线通信的中压配电网拓扑自动识别方法[J].高电压技术，2021,47(7):2350-2358.Huang Biyao,Zhang Ming,Li Jianqi,et al.Automatic identification of medium-voltage power distribution network topology based on high and low frequency power line communication[J]. High Voltage Engineering,2021,47(7):2350-2358.
• [11]任鹏哲，刘友波，刘挺坚，等.基于互信息贝叶斯网络的配电网拓扑鲁棒辨识算法[J].电力系统自动化，2021,45(9):55-62.Ren Pengzhe,Liu Youbo,Liu Tingjian,et al.Robust identification algorithm for distribution network topology based on mutual-information Bayesian network[J].Automation of Electric Power Systems,2021,45(9):55-62.
• [12]郝金宝，王亮，王鹏，等.基于有限遥测数据的中压有源配电网拓扑识别[J].电工电气，2024(8):42-47.Hao Jinbao,Wang Liang,Wang Peng,et al. Topology identification of medium voltage active distribution network based on limited telemetry data[J]. Electrotechnics Electric,2024(8):42-47.
• [13]谢宏，张华赢，梁晓锐，等.基于关系图卷积神经网络的新能源配电台区拓扑识别方法[J].电测与仪表，2024,61(7):94-102.Xie Hong,Zhang Huaying,Liang Xiaorui,et al. A topology identification method based on relational-graph convolutional network for distribution substation area with high renewables[J]. Electrical Measurement&Instrumentation,2024,61(7):94-102.
• [14]王子豪，余涛，黄毅，等.基于u-shaplets特征子序列的新型低压配电网拓扑识别方法[J].电测与仪表，2025,62(11):68-79.Wang Zihao,Yu Tao,Huang Yi,et al.A novel topology recognition method for low-voltage distribution network based on u-shaplets feature subsequences[J]. Electrical Measurement&Instrumentation,2025,62(11):68-79.
• [15]宋卓然，李剑峰，范宇航，等.“双碳”目标下电热-电蓄热接入配电网拓扑多目标规划[J].电力建设，2024,45(4):57-65.Song Zhuoran,Li Jianfeng,Fan Yuhang,et al.Multiobjective planning of electric heating-electric heat storage device access to distribution network topology under dual carbon target[J]. Electric Power Construction,2024,45(4):57-65.
• [16]陈培育，金尧，郑骁麟，等.基于可观性和可计算性的配电网关键量测识别方法[J].智慧电力，2024,52(3):110-116.Chen Peiyu,Jin Yao,Zheng Xiaolin,et al.Identification of critical measurement for distribution network based on observability and computability[J]. Smart Power,2024,52(3):110-116.
• [17]顼佳宇，王方敏，李冰，等.计及灵活性资源传输的配电网灵活性供需协同规划方法[J].电力建设，2025,46(6):76-91.Xu Jiayu,Wang Fangmin,Li Bing,et al. Collaborative planning method for flexibility supply and demand in distribution networks considering flexible resource transmission[J].Electric Power Construction,2025,46(6):76-91.
• [18]Dalavi F,Golshan M E H,Hatziargyriou N D.A review on topology identification methods and applications in distribution networks[J].Electric Power Systems Research,2024,234:110538.
• [19]Li M,Lei W.A general topology identification framework for distribution systems using smart meter andμ-PMU measurements[J]. International Journal of Electrical Power and Energy Systems,2022,139:108019.
• [20]Fu H,Junhong L,Daolu Z,et al.Low voltage power line physical topology recognition method based on data drive[J].Journal of Physics:Conference Series,2023,2532(1):012006.
• [21]黄飞，杨宏锐，戴健，等.基于电压聚类排序的中压配电网拓扑在线辨识方法[J].电工电能新技术，2023,42(9):77-85.Huang Fei,Yang Hongrui,Dai Jian,et al.Online topology identification method for medium voltage distribution network based on voltage clustering and sorting[J].Advanced Technology of Electrical Engineering and Energy,2023,42(9):77-85.
• [22]陈锦铭，蒋玮，袁宇波，等.基于电压一阶差分离群点关联分析的配电网线变关系诊断[J].电力系统保护与控制，2024,52(18):158-168.Chen Jinming,Jiang Wei,Yuan Yubo,et al. Distribution network line-transformer relationship diagnosis based on first-order voltage difference and outlier association analysis[J]. Power System Protection and Control,2024,52(18):158-168.
• [23]唐泽洋，周鲲鹏，曹侃，等.基于配电网运行数据的线变关系校验方法[J].高电压技术，2018,44(4):1059-1068.Tang Zeyang,Zhou Kunpeng,Cao Kan,et al. Substation area topology verification method based on distribution network operation data[J]. High Voltage Engineering,2018,44(4):1059-1068.
• [24]蒋玮，汤海波，祁晖，等.基于集成深度神经网络的配电网联络关系辨识技术[J].电力系统自动化，2020,44(1):101-108.Jiang Wei,Tang Haibo,Qi Hui,et al.Distribution network connectivity recognition based on ensemble deep neural network[J].Automation of Electric Power Systems,2020,44(1):101-108.
• [25]凌佳凯，章逸舟，胡金峰，等.基于CNN-LSTM-Attention的配电网拓扑实时辨识方法[J].浙江电力，2024,43(3):84-94.Ling Jiakai,Zhang Yizhou,Hu Jinfeng,et al.A real-time topology identification method of distribution networks based on CNN-LSTM-Attention[J]. Zhejiang Electric Power,2024,43(3):84-94.
• [26]Zhang M,Luan W,Guo S,et al. Topology identification method of distribution network based on smart meter measurements[C]//2018 China International Conference on Electricity Distribution(CICED),2018,Tianjin,China.IEEE,2018:372-376.
• [27]童力，梁海维，邹旭东，等.基于数据驱动的配电网拓扑识别及线路阻抗估计[J].浙江电力，2022,41(1):10-18.Tong Li,Liang Haiwei,Zou Xudong,et al.Date-driven distribution network topology identification and line impedance estimation[J].Zhejiang Electric Power,2022,41(1):10-18.
• [28]刘刚，高成龙，胡万君，等.基于改进的连续局部枚举采样和径向基函数响应面法的变压器静电环结构优化设计[J].电工技术学报，2023,38(23):6266-6278.Liu Gang,Gao Chenglong,Hu Wanjun,et al. Optimized design of transformer electrostatic ring based on radial basis function response surface method with enhanced successful local enumeration sampling[J]. Transactions of China Electrotechnical Society,2023,38(23):6266-6278.