• DocumentCode
    2796192
  • Title

    New distributed protection algorithm based on ANN and adaptive fault area search

  • Author

    Xu, Yang ; Zhang, Qing-Jie ; Lu, Yu-Ping

  • Author_Institution
    Sch. of Electr. Eng., Southeast Univ., Nanjing
  • Volume
    7
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    3878
  • Lastpage
    3884
  • Abstract
    DG has great negative effects on conventional relay protection in distribution networks. Decentralized protection strategy is more profitable mechanism to contain shortages and to satisfied fault selectivity of power system. It is known that voltage measure is difficult in distributed system (DS). The paper proposed an innovative way to decide fault direction without voltage measurement and developed an intelligent adaptive fault location by isolating DS. This locating algorithm can greatly reduce protection information collection requirement because of artificial neural network (ANN) introduction. With ANN, it can classify relevant fault area more easily and fault clearance will be more quick and sensitive. Case studies have been shown to support algorithm advantages.
  • Keywords
    fault diagnosis; neural nets; power distribution faults; power distribution protection; power engineering computing; relay protection; ANN; adaptive fault area search; artificial neural network; decentralized protection strategy; distributed protection algorithm; distribution networks; power system fault selectivity; relay protection; Artificial intelligence; Artificial neural networks; Fault location; Intelligent networks; Power system faults; Power system measurements; Power system protection; Power system relaying; Protective relaying; Voltage measurement; ANN; DG; Distributed protection; Fault direction; Relevant fault area;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4621081
  • Filename
    4621081