Cosine similarity cluster analysis model based effective power systems fault identification

@article{Sing2017CosineSC,
  title={Cosine similarity cluster analysis model based effective power systems fault identification},
  author={Tan Yong Sing and Syahrel Emran Bin Siraj and R. Raguraman and P. N. Marimuthu and K. Nithiyananthan},
  journal={International Journal of Advanced and Applied Sciences},
  year={2017},
  volume={4},
  pages={123-130}
}
  • Tan Yong Sing, Syahrel Emran Bin Siraj, +2 authors K. Nithiyananthan
  • Published 2017
  • Computer Science
  • International Journal of Advanced and Applied Sciences
  • Article history: Received 20 October 2016 Received in revised form 2 December 2016 Accepted 5 December 2016 The main objective of this paper is to develop a novel technique using Cluster Analysis with Cosine Similarity model to detect power system transmission lines fault and the types of fault that had occurred in power system. A test case of IEEE30 bus power system and different types of fault are simulated using PowerWorld v.18 software. Statistical Package for the Social Science (SPSS… CONTINUE READING

    Figures and Topics from this paper.

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 16 REFERENCES
    Fuzzy-neuro approach to fault classification for transmission line protection
    • 192
    Fuzzy-logic-based fault classification scheme for digital distance protection
    • 206
    Neural network approach to fault classification for high speed protective relaying
    • 283
    A fuzzy-set approach to fault-type identification in digital relaying
    • 114
    Data clustering: a review
    • 12,810
    • PDF
    Applications of Data Mining Theory in Electrical Engineering
    • 7
    • PDF