Contingency Ranking and Screening of an IEEE Bus-6 Case System with Distributed Generation

  • Authors

    • John Christopher T. Adina
    • John Mark L. Gonzales
    • Jonathan John C.
    • Julius Patrick L. Fontanilla
    • Michael C. Pacis
    • Esperanza E. Chua
    https://doi.org/10.14419/ijet.v7i3.7.19049
  • Power System, System Security, Contingency Analysis, NRLF, IEEE 6-Bus

  • Abstract

    Power System is a large system that is very sensitive to damage and failure especially in line and power outages, to assess the system security, contingency analysis allows systems to be operated. Many problems that occur on a power system cause serious trouble if not accounted and must be solved quickly. The objective is to create a program on how to have a quicker response on every contingencies. To solve this problem, the researchers had developed an algorithm for ranking and screening the contingencies for every line and power outages of an IEEE 6-Bus case system. Newton Raphson Load Flow (NRLF) was used to determine the line contingencies in the system and Performance Index (PI) ranked the contingencies based on their severity. The researchers were able to make a contingency analysis with a time of at least 10 minutes for computation.

     

  • References

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      [2] A. J. Wood, B. F. Wollenberg, “Power Generation, Operation, and Control†Chapter 11..

      [3] B. Krishnakumar, S. K. Soundarajan, R. Gnanadass, “Fuzzy Based Contingency Assessment Using Performance Indices with Masking Effect. 2012 IEEE Students’ Conference on Electrical, Electronics and Computer Science

      [4] Mohammad Khazaei, Shahram Jadid, Contingency Ranking Using Neural Networks by Radial Basis Function Method, 2008 IEEE.

      [5] S. Sidhu, L. Cui, “Contingency Screening for Steady-State Security Analysis By Using FFT and Artificial Neural Networks. IEEE transactions on power systems, vol. 15, no.1 February 2000

      [6] Power Generation, Operation, and Control 3rd edition by Allen J. Wood, Bruce F. Wollenberg & Gerald B. Shelbe page 328

      [7] K. Shanti Swarup, G. Sudhakar, Neural network approach to contingency screening and ranking in power systems, May 2006

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  • How to Cite

    Christopher T. Adina, J., Mark L. Gonzales, J., John C., J., Patrick L. Fontanilla, J., C. Pacis, M., & E. Chua, E. (2018). Contingency Ranking and Screening of an IEEE Bus-6 Case System with Distributed Generation. International Journal of Engineering & Technology, 7(3.7), 554-557. https://doi.org/10.14419/ijet.v7i3.7.19049

    Received date: 2018-09-05

    Accepted date: 2018-09-05