Actas de congresos
Multiobjective Tabu Search For Service Restoration In Electric Distribution Networks
Registro en:
9781424418749
2005 Ieee Russia Power Tech, Powertech. , v. , n. , p. - , 2005.
10.1109/PTC.2005.4524552
2-s2.0-51549083633
Autor
Garcia V.J.
Franca P.M.
Institución
Resumen
Contingency situations may cause emergency states in distribution systems; these states are defined as the interruption of power supply. The importance of the maintenance of the quality limits in relation frequency and duration of interruption means that such situations should be avoided whenever possible. The service restoration problem is designed to minimize the number of consumers affected by a fault, by transferring them to distribution support feeders, thus restoring power, but without violating electrical and operational conditions, such as radial network configuration, and equipment and voltage drop limits. This paper outlines a new method for the restoration of service which uses a multiobjective version of the well-known Tabu Search metaheuristic. Two criteria are considered: the minimization of the load not restored and of the number of switching operations involved. The flexibility and effectiveness of the proposed method are proved in a practical test system.
Curcic, S., Ozveren, C., Crowe, L., Lo, P., Electric power distribution network restoration: A survey of papers and a review of the restoration problem (1996) Electric Power Systems Research, 35, pp. 73-86 Morelato, A., Monticelli, A., Heuristic search approach to distribution system restoration (1989) IEEE Transactions on Power Delivery, 4 (4), pp. 2235-2241. , October Liu, C., Lee, S., Venkata, S., An expert sytem operational aid for restoration and loss reduction of distribution systems (1988) IEEE Transactions on Power Delivery, 3 (2), pp. 619-626 Shirmohammadi, D., Service restoration in distribution networks via network reconfiguration (1992) IEEE Transactions on Power Delivery, 7 (2), pp. 952-958. , April Lee, S.-J., Lim, S.-I., Ahn, B.-S., Service restoration of primary distribution systems based on fuzzy evaluation of multicriteria (1998) IEEE Transactions on Power Systems, 13 (3), pp. 1156-1163. , August Miu, K., Chiand, H.-D., Yuan, B., Darling, G., Fast service restoration for large-scale distribution systems with priority customers and constraints (1998) IEEE Transactions on Power Delivery, 13 (3), pp. 789-795 Matos, M., Melo, P., Multiobjective reconfiguration for loss reduction and service restoration using simulated annealing (1999) Proceedings of IEEE Budapest Power Tech'99, , IEEE Service Center Augugliaro, A., Dusonchet, L., Sanseverino, E.R., Evolving non-dominated solutions in multiobjective service restoration for automated distribution networks (2001) Electric Power Systems Research, 59, pp. 185-195 Ciric, R., Popovic, D., Multi-objective distribution network restoration using heuristic approach and mix interger programming method (2000) Electrical Power and Energy Systems, 22, pp. 497-505 Steuer, R., (1986) Multiple Criteria Optimization: Theory, Computation and Application, , New York: Wiley Glover, F., Tabu Search - Part I (1989) ORSA Journal on Computing, 1, pp. 190-206 Glover, F., Laguna, M., (1997) Tabu Search, , Kluwer Academic Publishers Ahuja, R., Magnanti, T., Orlin, J., (1993) Network Flows: Theory, Algorithms and Applications, , Prentice Hall, Englewood Cliffs Baran, M., Wu, F., Network reconfiguration in distribution systems for loss reduction and load balancing (1989) IEEE Transactions on Power Delivery, 4 (2), pp. 1401-1407. , April Hsu, Y., Kuo, H., A heuristic based fuzzy reasoning approach for distribution system service restoration (1994) IEEE Transactions on Power Delivery, 9 (2), pp. 948-953 Aoki, K., Nara, K., Itoh, M., Satoh, T., Kuwabara, H., A new algorithm for service restoration in distribution systems (1989) IEEE Transactions on Power Delivery, 4 (3), pp. 1832-1839 Lewis, H., Papadimitriou, C., (1981) Elements of the Theory of Computation, , Prentice-Hall International Morse, J.N., Reducing the size of the nondominated set: Pruning by clustering (1980) Computers and Operations Research, 7 (1-2), pp. 55-66