• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid
Title Fault Type & Section Detection Method in a Distribution Network with Distributed Generations Based on the Separated Phase ANN-Model 484
Authors 강석준(Seok-Jun Kang) ; 이혜쩡(Hye-Jeong Lee) ; 최명찬(Myeong-Chan Choi) ; 김도균(Do-Kyun Kim) ; 현승호(Seung-Ho Hyun)
DOI https://doi.org/10.5370/KIEE.2023.72.4.484
Page pp.484-495
ISSN 1975-8359
Keywords Distribution Network; Distributed Generation; Fault Allocation; Fault Type Classification; Deep Learning; Artificial Neural Network
Abstract In recent years, the number of distributed generation (DG) in distribution network (DN) has increased. The increasing proportion of DG in DN brings benefits through improved network reliability and reduced transmission power losses. However the connection of DG makes network be more complicated, it changes the unidirectional flow of currents and power to bidirectional flow and thus protection based on over-current relay has limitations of protection coordination. These limitations may occur malfunction or misbehavior of protective devices so it requires new protection methods. This paper proposes a new method using artificial neural network (ANN) can adjust on DN with DG to allocate fault section and to classify fault type as part of solving limitations of protection coordination. This ANN model is separated to each phase and use magnitude and phasor of voltages and currents extracted from each generation sides. The new proposed method is applied to unbalanced distribution network model and verified to be useful in DN through computer simulations.