• DocumentCode
    535593
  • Title

    A new hybrid intelligent based approach to islanding detection in distributed generation

  • Author

    Ghazi, R. ; Lotfi, N.

  • Author_Institution
    Ferdowsi Univ. of Mashhad, Mashhad, Iran
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 3 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a new hybrid intelligent based approach for detecting islanding in distributed generation (DG). In this proposed method the passive and active techniques are combined to get a better reliability. So this hybrid method can secure the detection of islanding for different network topology and various operating conditions of synchronous machine based DG. Hence a better reliability is provided. This approach utilizes the artificial neural network (ANN) as a machine learning technology for processing and analyzing the large data sets provided from network simulations using PSCAD/EMTD software. The technique is tested on two typical distribution networks. The results obtained from one case study are compared with results of one of references to show the validity of the proposed method. The results of both studied cases indicate that the developed method can successfully detect islanding situations.
  • Keywords
    CAD; distributed power generation; learning (artificial intelligence); network topology; neural nets; power distribution reliability; power engineering computing; PSCAD-EMTD software; active techniques; artificial neural network; distributed generation; hybrid intelligent based approach; islanding detection; machine learning technology; network topology; passive techniques; Accuracy; Artificial intelligence; Artificial neural networks; Distributed power generation; Loading; Reactive power; Sensitivity; Artificial Neural Network (ANN); Distributed Generation (DG); Islanding Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Universities Power Engineering Conference (UPEC), 2010 45th International
  • Conference_Location
    Cardiff, Wales
  • Print_ISBN
    978-1-4244-7667-1
  • Type

    conf

  • Filename
    5649170