Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

Abstract

Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties to the topology identification of distribution network. The existing distribution network topology identification methods lack of multi period measurement data, and the utilization rate of multiuser data is low, which leads to the low accuracy of distribution network topology identification. To solve this problem, a distribution network topology identification method based on multiuser fusion data is proposed. Firstly, the existing distribution network measurement system is analyzed, and the data and characteristics that can be collected in the actual project are obtained. Then, according to the characteristics of different data sampling frequency and accuracy, multiuser data fusion is carried out, and a PMU based multiuser data time scale alignment method and a pseudo measurement generation method based on linear extrapolation are proposed. Finally, an optimization model of distribution network topology identification based on multiuser and multi period fusion data is proposed. By minimizing the error between the measured value and the estimated value in several time periods, the model realizes the identification of distribution network topology. Simulation results show that the method is correct and effective. INDEX TERMS Distribution network,nonsynchronous measurement, multi-prosumer data, topology identification, prosumer gourp.

A Novel Topology Identification Algorithm Fusing Multi-Source Measurement Data in Distribution Network

“…Measurement positions[11] Multi user fusion data Figures 2 represents the original data and multi-source fusion data for the injected active power of node 2 measured by μPMU, SCADA and AMI respectively.…”