基于节点注入功率的配电网运行拓扑辨识

配电网安全监控和数据采集系统(DSCADA)采集的遥信数据存在抖动和误动情况,导致基于遥信数据的配电网拓扑信息可靠性不高。通过微型同步相量量测单元(μPMU)多次采样的节点注入功率,构建基于节点注入功率量测的支路电压偏差的方差模型。采用Kruskal算法得到以支路电压偏差的方差为线路权重的最小生成树,实现对配电网拓扑运行结构的辨识。在此基础上,对比分析节点注入功率量测的采样次数以及网络复杂程度对拓扑辨识误差的影响。IEEE 33和IEEE 123节点系统仿真结果表明,该配电网运行拓扑辨识算法具有较好的可靠性和实用性。

Topology Identification of Distribution Network Based on Nodal Power Injection

Erroneous remote signal in distribution supervisory control and data acquisition ( DSCADA ) decreases the reliability of distribution network topology of remote signaling data. With adopting multi-sampling of power injections by micro synchronous phasor measurement unit (μPMU ) , this paper constructs the variance model of the branch voltage deviation based on the measurement of nodal power injection. The Kruskal algorithm is used to obtain the minimum spanning tree with the variance of the branch voltage deviation as the line weight to achieve the identification of operation topology structure of distribution network, and then the influence of the sampling times of the power injection data and the complexity of the distribution network on the identification errors is analyzed. The simulation results of IEEE 33 and IEEE 123 node system show that the algorithm has good reliability and practicability for the topology identification in distribution network.