Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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High Impedance Fault Detection Using Neural Networks

신경회로망을 이용한 고저항 고장 검출

  • Han, J.G. (Dept. of Electrical Engineering, Pusan National University) ;
  • Lee, H.S. (Dept. of Electrical Engineering, Pusan National University) ;
  • Yun, J.Y. (Dept. of Electrical Engineering, Pusan National University) ;
  • Yang, K.H. (Dept. of Electrical Engineering, Pusan National University) ;
  • Park, J.H. (Dept. of Electrical Engineering, Pusan National University)
  • 한중길 (부산대학교 공과대학 전기공학과) ;
  • 이화석 (부산대학교 공과대학 전기공학과) ;
  • 윤재영 (부산대학교 공과대학 전기공학과) ;
  • 양광호 (부산대학교 공과대학 전기공학과) ;
  • 박준호 (부산대학교 공과대학 전기공학과)
  • Published : 1995.07.20
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Abstract

High impedance fault can not be easily detected by conventional method. But if it would not be detected and cleared quickly, it can result in fires, and electric shock. In this paper, ANN, which has learning capability, is used for high impedance fault detection. The potential of the neural network approach is demonstrated by simulation using KEPCO's measured data. Among ANN models used in this paper, CPN shows better result than BPN in respect of convergence and reliability.

Keywords