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

Author

Listed:
  • Qinwei Li

    (Department of Electrical Engineering, North China Electric Power University, No. 619 Yonghua Road, Baoding 071003, China)

  • Wenchao Jia

    (Department of Electrical Engineering, North China Electric Power University, No. 619 Yonghua Road, Baoding 071003, China)

Abstract

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.

Suggested Citation

  • Qinwei Li & Wenchao Jia, 2023. "Phase Selection and Location Method of Generator Stator Winding Ground Fault Based on BP Neural Network," Energies, MDPI, vol. 16(3), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1503-:d:1056268
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