基于互信息贝叶斯网络的配电网拓扑鲁棒辨识算法  

Robust Identification Algorithm for Distribution Network Topology Based on Mutual-information Bayesian Network

作　　者：任鹏哲 刘友波[1] 刘挺坚 何培东[2] 张扬帆 邓舒予 REN Pengzhe;LIU Youbo;LIU Tingjian;HE Peidong;ZHANG Yangfan;DENG Shuyu(College of Electrical Engineering,Sichuan University,Chengdu 610065,China;Metering Center of State Grid Sichuan Electric Power Company,Chengdu 610045,China)

机构地区：[1]四川大学电气工程学院,四川省成都市610065 [2]国网四川省电力公司计量中心,四川省成都市610045

出　　处：《电力系统自动化》2021年第9期55-62,共8页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(51977133)。

摘　　要：基于微型同步相量测量装置(μPMU),提出一种配电网拓扑识别新算法,通过贝叶斯网络(BN)拟合配电网拓扑、光伏、负荷及μPMU测量电压的非线性关系,引入最大互信息网格划分量度连续型节点区间,解决了BN处理连续型数据时需人为指定区间数目、难以适应较多连续型变量的问题。基于拉丁超立方抽样生成光、荷数据,保证了场景在样本空间内均匀分布,简化了BN的训练过程并提高了拓扑识别的泛化能力。通过仿真算例验证方法的有效性,结果表明,所提方法具有与实时估计匹配法相当的识别精度和更高的时效性,且识别时间不随配电网可行拓扑数量的增加而线性增长,适用性佳;即使在μPMU部分失效或负荷、光伏等数据缺失时仍能保证较高识别率,具有较强的鲁棒性。Based on the micro phasor measurement unit(μPMU),this paper proposes a new identification method of distribution network topology.The nonlinear relationship among distribution network topology,photovoltaic(PV),load andμPMU measured voltage is fitted by Bayesian network(BN).The interval of continuous nodes is measured by introducing the grid division of maximal information coefficient(MIC).MIC solves the problem that traditional BN needs to specify the interval number manually when processing continuous data,and is difficult to be applied to cases with lots of continuous variables.The photovoltaic-load data generated by the Latin hypercube sampling(LHS)can realize the uniform distribution of the scene in the sample space.The training process of BN is simplified and the generalization ability of topology identification is improved.The effectiveness of the method is verified by a simulation example.The simulation results show that the proposed method has the same identification accuracy and higher timeliness compared with the real-time estimation matching method.The identification time does not increase linearly with the increasing of the number of feasible topologies.The proposed method has good applicability.Even in the case of partial failure of theμPMU or lack of key data,such as load and PV data,the proposed method can ensure high identification effect,and thus has strong robustness.

关 键 词：贝叶斯网络 互信息 拉丁超立方抽样 配电网 微型同步相量测量装置 拓扑识别 节点电压信息 

分 类 号：TM73[电气工程—电力系统及自动化]