Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

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...

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Bibliographic Details
Published in:IEEE access 2022, Vol.10, p.72785-72793
Main Authors: Zhang, Lizong, Zhang, Fengming, Li, Xiaolei, Wang, Chunlei, Chen, Taotao, Wang, Qingqing, Hu, Huilin
Format: Article
Language:English
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Summary: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 multi-user 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 multi-user 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, multi-user data fusion is carried out, and a PMU based multi-user 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 multi-user 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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3052993