Journal
ELECTRIC POWER SYSTEMS RESEARCH
Volume 223, Issue -, Pages -Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2023.109689
Keywords
Characteristics; Fault type identification; Fourier transform; Neural network; Wavelet transform
Categories
Ask authors/readers for more resources
Different types of faults have different levels of threat to the distribution network. Accurate identification of fault types is crucial for maintenance and prevention of hazards in the distribution network.
Different types of faults pose different degrees of threat to the distribution network. Accurate identification of fault types is essential for distribution network maintenance and hazard prevention. The simulation of a typical single-phase arc grounding fault in a distribution network is carried out based on a 10 kV test platform, and the zero-sequence current of cable fault, tree touch, line break, and insulator flashover is obtained. The BP neural network is established and trained to recognize the feature data, which is extracted by Fourier transform and wavelet transform. The identification results prove the effectiveness of the proposed method for single-phase arc grounding fault type identification in distribution networks.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available