Topology identification in distribution network based on power injection measurements

Erroneous remote signal in distribution supervisory control and data acquisition (DSCADA) decreases reliability of distribution network topology which is identified based on remote signaling data of DSCADA. A new method of topology identification is proposed to solve this problem, which adopts multi-sampling of power injections by micro synchronous phasor measurement unit (μPMU) to construct the variance model of the branch voltage deviation. 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 example shows that the algorithm has good reliability and practicability for the topology identification in distribution network.