Phase Selection and Location Method of Generator Stator Winding Ground Fault Based on BP Neural Network

The phase selection and fault location methods of generator stator winding single-phase grounding fault are greatly affected by the transition resistance. A new phase selection and generator stator ground fault location approach based on the BP neural network is proposed in this research from a data...

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Bibliographic Details
Published inEnergies (Basel) Vol. 16; no. 3; p. 1503
Main Authors Li, Qinwei, Jia, Wenchao
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.02.2023
Subjects
Algorithms
Artificial intelligence
Back propagation networks
BP neural network
Design and construction
Electric fault location
Electric generators
Error correction
Fault location
fault phase selection and location
Generators
Methods
Neural networks
stator ground fault
stator grounding protection
Stators
Winding
China
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Summary:The phase selection and fault location methods of generator stator winding single-phase grounding fault are greatly affected by the transition resistance. A new phase selection and generator stator ground fault location approach based on the BP neural network is proposed in this research from a data-driven angle. This method uses a neural network to calculate the probability of three-phase fault occurrence to identify the fault phase and directly calculate the fault location that takes the amplitude and phase angle characteristics of zero-sequence voltage as input. The simulation results show that the stator ground fault phase selection and location algorithm based on the neural network can achieve correct phase selection and small positioning error, which has verified the effectiveness of the method.
ISSN:1996-1073
1996-1073
DOI:10.3390/en16031503