INDEXED IN 

ISSN 2456-0235

ISSN 2456-0235

International Journal of Modern Science and Technology

​​​​​​​​International Journal of Modern Science and Technology, Vol. 2, No. 3, 2017, Pages 117-121. 


Minimum Spanning Tree based Power Restoration in Distribution Network

T. D. Sudhakar
Department of Electrical and Electronics Engineering, St Joseph’s College of Engineering, Chennai – 600 119. India.

*Corresponding author’s e-mail: t_d_sudhakar@yahoo.co.in

Abstract
The present paper deals with the restoration of the distribution following a partial blackout. The main issue during a restoration is to achieve the minimum deficit of power supply; a proper switching of power lines is required. Since time is a limiting factor and the decision making is a highly combinatorial problem, a graph theory based system is proposed in order to solve it. The restoration process can be decomposed into two main stages. The first one, power flow path identification, consists of switching status of all the K switches in order to energise a network. The second stage, load flow analysis, aims to supply the consumers effectively by satisfying the major constraints. The proposed methodology is tested on a 33 bus distribution network is tested to demonstrate the effectiveness of this study. The results obtained are comparable to the results available in the literature.

​​Keywords: Minimum Spanning Tree; Distribution network; Restoration; Switching; Graph theory.

References

  1. Sudhakar TD, Srinivas KN. A Graph Theory–Based Distribution Feeder Reconfiguration for Service Restoration. International Journal of Power and Energy Systems. 2010;30(3):161–168.
  2. Adibi MM, Kafka RJ. Power System Restoration Issues. IEEE Computer Applications in Power. 1991;4(2):19–24.
  3. Morelato AL Monticelli A. Heuristic Search Approach to Distribution System Restoration. IEEE Transactions on Power Delivery. 1989;4(4):2235–2241.
  4. Hotta K, Nomura H, Takemoto H, Suzuki K. Nakamura S, Fukui S. The Implementation of a Real–Time Expert System for a Restoration Guide in a Dispatching Center. IEEE Transactions on Power Systems. 1990;5(3):1032–1038.
  5. Matsumoto K, Sakaguchi T, Kafka RJ, Adibi MM. Knowledge–Based Systems as Operational Aids in Power System Restoration. Proceedings of the IEEE, 1992;80(5):689–697.
  6. Hoyong K, Yunseok K, Kyung–Hee J. Artificial Neural–Network based Feeder Reconfiguration for Loss Reduction in Distribution Systems. IEEE Transactions on Power Systems. 1993;8(3):1356–1366.
  7. Han Ching K, Yuan Yih H. Distribution System Load Estimation and Service Restoration using a Fuzzy Set Approach. IEEE Transactions on Power Delivery. 1993;8(4):1950–1957.
  8. Gregory L, Shmuel Mazal T, David E. Genetic algorithm for optimal sectionalizing in radial distribution systems with alternative supply. Electric Power Systems Research. 1995;35:149–155.
  9. Rahman S. Artificial intelligence in electric power systems – a survey of the Japanese industry. IEEE Transactions on Power System. 1993;8(3):1211–1218.
  10. Fountas NA, Hatziargyriou ND, Valavanisl KP. Hierarchical Time Extended Petri Nets as a Generic Tool for Power System Restoration. IEEE Transactions on Power Systems. 1997;12 (2):837–843. 
  11. Toune S, Fudo H, Genji T, Fukuyama Y, Nakanishi Y. A reactive tabu search for service restoration in electric power distribution systems. Proceedings of IEEE International Conference on Evolutionary Computation. 1998;763–768.
  12. Nagata T, Sasaki H. A Multi–Agent Approach to Power System Restoration. IEEE transactions on power systems. 2002;17(2):457–462.
  13. Mohanty I, Kalita J, Das S, Pahwa A, Buehler E. Ant algorithms for the optimal restoration of distribution feeders during cold load pickup.  Proceedings of the Swarm Intelligence Symposium. IEEE, 2003;132–137.
  14. Si–Qing S, Yun C, Yu Y. Distribution Network Reconfiguration Based on Particle Swarm Optimization and Chaos Searching. Asia–Pacific Power and Energy Engineering Conference. 2009;1–4.
  15. Ying–Tung H, Ching–Yang C. Enhancement of Restoration Service in Distribution Systems Using a Combination Fuzzy–GA Method. IEEE Transactions On Power Systems. 2000;15(4):1394–1400.
  16. Lin Ming J, Shu Park C. An electrical method for finding suboptimal routes, ISCAS’89 IEEE, 1989;935–938.
  17. Hiroyuki Mork and Senji Tsuzuki, A fast method for topological observability analysis using minimum spanning tree technique. IEEE Transaction on Power System. 1991;6(2):491–500.
  18. Shun Lin S, Charles HB, Chi Yuan L. A space efficient short finding algorithms. IEEE Transactions on Computer Aided Design of Integrated Circuit and Systems. 1994;13(8):1065–1068.
  19. Cavellucci and Lyra, Minimization of energy losses in electric power distribution system by intelligent search strategies, International Transaction in Operational Research. 1997;4(1):23–33.
  20. Michel B. A note on the complexity of Dijkstra’s algorithm for graphs with weighted vertices, IEEE Transactions on computers. 1998;41(2): 263.
  21. Ali S, Ahmad MO, Swamy MN. Scheduling of DSP data flow graphs onto multiprocessor for maximum throughput, IEEE 1999, 1999;386–389.
  22. Partricia AV, Christiano LF, Fernanado JVZ. On line approach for loss reduction in electric power distribution networks using learner classifier systems. Springer, 2002; 181–196.
  23. Kaigui X, Jiaqi Z, Billinton R. Reliability evaluation algorithm for complex medium voltage electrical distribution networks based on the shortest path. IEE Proceeding on Generation. Transmission and Distribution. 2003;150(6):686 – 690.
  24. TianTian C, Qian A. Research of PMU optimal placement in power systems. International Conference on System Theory and Scientific Computation, 2005;38–43.
  25. Yixin Y, Jianzhong W. Loads Combination Method Based Core Schema Genetic Shortest–path Algorithm For Distribution Network Reconfiguration, 2002;1729–1733.
  26. Sudhakar TD, Srinivas KN. Restoration of Power Distribution Network–A Bibliographical Survey. European Transactions on Electrical Power. 2011; 21(1):635–655.
  27. Sudhakar TD, Mohanaram S. Power System Restoration using Reverse Delete Algorithm Implemented in FPGA. Second IET International Conference on Sustainable Energy and Intelligent System. 2011;373–378.
  28. Sudhakar TD, Srinivas KN. Power System Reconfiguration based on Kruskal’s Algorithm. IEEE conference ICEES 2011, 2011;1:234–240
  29. Sudhakar TD, Srinivas KN. Prim’s Algorithm for Loss Minimization and Service Restoration in Distribution Networks. International Journal of Electrical and Computer Engineering. 2010;2(1):43–62.