KIEE International Transactions on Power Engineering

대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

Bus Reconfiguration Strategy Based on Local Minimum Tree Search for the Event Processing of Automated Distribution Substations

  • Ko Yun-Seok (Dept. of Electronics and Information Communication Engineering, Namseoul University)
  • 발행 : 2005.06.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper proposes an expert system that can enhance the accuracy of real-time bus reconfiguration strategy by adopting the local minimum tree search method and that can minimize the spreading effect of the fault by considering the operating condition when a main transformer fault occurs in an automated substation. The local minimum tree search method is used to expand the best-first search method. This method has the advantage that it can improve the solution performance within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. The second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules from the obtained switching candidate set. Also, this paper proposes generalized distribution substation modeling using graph theory, and a substation database based on the study results is designed.

키워드

참고문헌

  1. C.S. Chang, T.S.Chung, 'An Expert System for On- Line Security-Economic Load Allocation on Distribution Systems', IEEE Trans. on Power Delivery, Vol. 5, No. 1, pp. 467- 469, January 1990 https://doi.org/10.1109/61.107314
  2. Aoki, K., H. Kuwabara, T. Satoh, and M. Kanezashi, 'An Efficient Algorithm for Load Balancing of Transformers and Feeders by Switch Operation in Large Scale Distribution Systems', IEEE Trans. on Power Delivery, Vol. 3, No. 4, pp. 1865-1872, October 1988 https://doi.org/10.1109/61.193994
  3. Taylor T. and D., Lubkeman, 'Implementation of Heuristic Search Strategies for Distribution Feeder Reconfiguration', IEEE Trans. on Power Delivery, Vol. 5, No. 2, pp. 239-246, January 1990 https://doi.org/10.1109/61.107279
  4. Mori S., I.Hata, T.Usui and K. Morita, 'Expert System Supporting Substation Service Restoration', ESAP IV, pp. 131-136, January 1993
  5. Bernard J. P. and D. Durocher, 'An Expert System for Fault Diagnosis Integrated in Existing SCADA Systems', IEEE Trans. on Power Systems, Vol. 9, No. 1, pp. 548-554, February 1994 https://doi.org/10.1109/59.317567
  6. Power System Restoration Working Group, 'Special Consideration in Power System Restoration: The Second Working Group Report', IEEE Trans. on Power Systems, Vol. 9, No. 1, February 1994 https://doi.org/10.1109/59.331461
  7. Yang, Hong-Tzer, Wen-Yeay Chang, Ching-Lien Huang, 'On-Line Fault Diagnosis of Power Substation Using Connectionist Expert System,' IEEE Trans on Power Systems', Vol. 10, No. 1, February 1995
  8. Kim, H., Y. Ko, and K. H. Jung, 'Algorithm of Transferring the Load of the Faulted Substation Transformer using the Best-First Search Method', IEEE Trans. on PWRD, Vol. 7 No. 3, pp. 1434-1442, July 1992
  9. Luger, G.F. and Stubblefield, W.A. ARTIFICIAL INTELLIGENCE AND THE DESIGN OF EXPERT SYSTEM, the Beniman/Cummings Publishing Company, Inc
  10. Patterson, Dan W, INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS, Prentice- Hall International Inc