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Classifier System and Co-evolutionary Hybrid Approach to Restoration Service of Electric Power Distribution Networks

  • Filipiak, Sylwester (Dept. of Electrical Engineering, Automatics and Computer Science University of Technology Kielce)
  • Received : 2011.03.14
  • Accepted : 2011.10.19
  • Published : 2012.05.01

Abstract

The method proposed by the author is intended for assistance in decision-making (concerning changes of connections) by operators of complex distribution systems during states of malfunction (particularly in the events of malfunctions, for which the consequences encompass extended parts of the network), through designation of connection action scenarios (creating substitute configurations). It is the use by the classifying system working with the co-evolution algorithm that enables the effective creation of substitute scenarios for the Medium Voltage electric power distribution network. The author also completed works concerning the possibility of using cooperation of the evolutionary algorithm and the co-evolutionary algorithm with local search algorithms. The method drawn up may be used in current systems managing the work of distribution networks to assist network operators in taking decisions concerning connection actions in supervised electric power systems.

Keywords

References

  1. Stepien J. Madej Z.: "Evaluation of structural redundancy efects in medium voltage cable networks". Rynek Energii No 4(83), 2009, pp. 55-62.
  2. Stepien J.: "Changes in demand structure of energy carriers with the use of waste heat and renewable energy". Rynek Energii Issue: 5 p. 58-62 Published: OCT 2008.
  3. Stepien J.: "Evaluation of structural redundancy effects in medium voltage cable networks". Przeglad Elektrotechniczny Volume: 84 Issue: 4 p. 128-131 Published: 2008.
  4. D. Rho, K. Kook, Y. Wang, "Optimal Algorithms for Voltage Management in Distribution Systems Interconnected with New Dispersed Sources", Journal of Electrical Engineering & Technology Vol. 6, No. 2, 2011, pp. 192-201. https://doi.org/10.5370/JEET.2011.6.2.192
  5. S. Jang, J. Roh, W. Kim, T. Sherpa, .J. Kim, J. Park, "A Novel Binary Ant Colony Optimization: Application to the Unit Commitment Problem of Power Systems", Journal of Electrical Engineering & Technology Vol. 6, No. 2, 2011, pp. 174-181. https://doi.org/10.5370/JEET.2011.6.2.174
  6. S. Toune, H. Fudo, T. Genji, Y. Fukuyama, "Comparative study of modern heuristic algorithms to service restoration in distribution systems," IEEE Trans. Power Delivery, vol. 17, Jan. 2002, pp. 173-181. https://doi.org/10.1109/61.974205
  7. S. Khushalani, J.M. Solanki, N.N. Schulz, "Optimized Restoration of Unbalanced Distribution Systems," IEEE Transactions on Power Systems, no. 22, Issue 2. 2007, p. 624-630. https://doi.org/10.1109/TPWRS.2007.894866
  8. Y. Kumar, B. Das, J. Sharma, "Multiobjective, Multiconstraint Service Restoration of Electric Power Distribution System With Priority Customers," IEEE Transactions on Power Delivery, no. 23, Issue 1, 2008, p. 261-270. https://doi.org/10.1109/TPWRD.2007.905412
  9. Goldberg D. E. Genetic Algorithms and Their Applications. WNT, Warszawa 2003.
  10. Filipiak S.: Multiobjective optimisation of electric power distribution networks post-fault configuration. Rynek Energii No 3(88), 2010, p. 164-169.
  11. Stepien J.: "Forecast of heat demands in the low urbanized areas", Rynek Energii, Issue: 6 p. 7-12 Published: DEC 2007