The Technology on Fault Location of Distribution Network Based on Hierarchical Model and Intelligent Checking Algorithm
Wang Qiujie1, Jin Tao1, Tan Hong2, Li Zhenxing2
1. College of Electrical Engineering and Automation Fuzhou University Fuzhou 350116 China; 2. College of Electrical and New Energy China Three Gorges University Yichang 443000 China
Abstract：After a large number of distributed generators are connected to large distribution network, the fault location model based on single layer logic relation is extremely complex, and the location algorithm has low efficiency and poor stability. Therefore, a fault location method based on hierarchical model and intelligent checking algorithm is proposed. Its advantages are: ①The dimension of the switching function based on logical relation is greatly reduced and the structure is greatly simplified after two-port equivalence is implemented for each branch of the distribution network. ②Hierarchical location obviously reduces the computing dimension of location algorithm, and greatly improves the location efficiency. ③Feedback check mechanism, using the location absolute reliability of the exhaustion method to identify the fault area location results, effectively compensates for the instability of the intelligent algorithm in fault identification. The simulation results show that, comparing with the single layer model and the intelligent algorithm without checking mechanism, the hierarchical model and the intelligent algorithm have better fault tolerance and stability, which can greatly simplify the fault identification model and improve the fault location efficiency. In large distribution network with high penetration rate, the new method of fault location has obvious advantages.
王秋杰, 金涛, 谭洪, 李振兴. 基于分层模型和智能校验算法的配电网故障定位技术[J]. 电工技术学报, 2018, 33(22): 5327-5337.
Wang Qiujie, Jin Tao, Tan Hong, Li Zhenxing. The Technology on Fault Location of Distribution Network Based on Hierarchical Model and Intelligent Checking Algorithm. Transactions of China Electrotechnical Society, 2018, 33(22): 5327-5337.
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2018, Vol. 33 
