LAPSE:2018.0506
Published Article
LAPSE:2018.0506
Fault Location Method for DC Distribution Systems Based on Parameter Identification
Yan Xu, Jingyan Liu, Weijia Jin, Yuan Fu, Hui Yang
September 21, 2018
When a short circuit fault occurs on the DC side line, the fault current reaches the peak within a few milliseconds, and the voltage drops significantly. This phenomenon can cause overcurrent flowing through the DC line, semiconductor devices, and AC side, which is a major threat to the operation of the entire system. To solve this problem, this paper proposes a fault location scheme based on parameter identification. Firstly, the entire DC distribution system is regarded as a graph. The intersections of the distribution system lines are regarded as vertices. The current flow of each line is regarded as a directed edge. The network topology matrix is constructed and a fault type recognition algorithm is proposed based on graph theory. Secondly, the mathematical model of the pole-to-pole short-circuit fault and pole-to-ground short-circuit fault are analyzed with double-ended electrical quantities. Transform the fault location problem into a parameter identification problem, four parameters to be identified are extracted, and the fitness function is constructed separately for two kinds of fault cases. Thirdly, a genetic algorithm (GA) is adopted to identify the value of parameters. Considering the fault types, transition resistance and fault location, the Matlab/Simulink simulation platform is used to simulate 18 fault conditions. The simulation results show that the positioning error of the fault location method is less than 1%, which is not affected by the transition resistance and has strong robustness.
Keywords
DC distribution system, fault location, fault type identification, parameter identification
Suggested Citation
Xu Y, Liu J, Jin W, Fu Y, Yang H. Fault Location Method for DC Distribution Systems Based on Parameter Identification. (2018). LAPSE:2018.0506
Author Affiliations
Xu Y: State Key Laboratory of New Energy and Electric Power Systems, North China Electric Power University, Baoding 071003, Hebei, China
Liu J: State Key Laboratory of New Energy and Electric Power Systems, North China Electric Power University, Baoding 071003, Hebei, China
Jin W: Hebei Province Baoding Power Supply Company, Baoding 071000, Hebei, China
Fu Y: State Key Laboratory of New Energy and Electric Power Systems, North China Electric Power University, Baoding 071003, Hebei, China
Yang H: State Key Laboratory of New Energy and Electric Power Systems, North China Electric Power University, Baoding 071003, Hebei, China
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Journal Name
Energies
Volume
11
Issue
8
Article Number
E1983
Year
2018
Publication Date
2018-07-31
Published Version
ISSN
1996-1073
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Original Submission
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PII: en11081983, Publication Type: Journal Article
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LAPSE:2018.0506
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doi:10.3390/en11081983
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Sep 21, 2018
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Sep 21, 2018
 
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Calvin Tsay
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