• DocumentCode
    2079483
  • Title

    A co-operative hybrid algorithm for fault diagnosis in power transmission

  • Author

    Rayudu, Ramesh K. ; Samarasinghe, Sandhya ; Maharaj, Ajay

  • Author_Institution
    Transpower AI Res. Lab., Lincoln Univ., Canterbury, New Zealand
  • Volume
    3
  • fYear
    2000
  • fDate
    23-27 Jan 2000
  • Firstpage
    1939
  • Abstract
    This paper presents our co-operative hybrid algorithm for fault diagnosis in power transmission networks. When a fault occurs in a transmission network, it must be identified and eliminated as soon as possible. Since control centers are flooded with hundreds of alarm messages during a fault, fault diagnosis, which involves the analysis of alarm messages, is a time consuming task. Towards the development of a fault diagnostician, model-based, heuristic, and neural networks are applied to the domain and the results are presented in this paper. The algorithm is a hierarchical model which combines several reasoning methods such as heuristic, temporal and model-based diagnosis and incorporates a network of neural networks at one of the levels of the hierarchy. The working of this co-operative algorithm is discussed and its results are analysed
  • Keywords
    fault diagnosis; neural nets; power system analysis computing; power transmission faults; alarm messages; co-operative hybrid algorithm; control centers; fault diagnosis; hierarchical model; intelligent fault diagnosis; intelligent system; model-based diagnosis; model-based heuristic; neural networks; power transmission networks; reasoning methods; temporal-based diagnosis; Electrical fault detection; Fault diagnosis; Hybrid intelligent systems; Intelligent networks; Neural networks; Power system faults; Power system modeling; Power system protection; Power system relaying; Power transmission;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Winter Meeting, 2000. IEEE
  • Print_ISBN
    0-7803-5935-6
  • Type

    conf

  • DOI
    10.1109/PESW.2000.847650
  • Filename
    847650