Reconfiguration of the Shipboard Power System Based on Particle Swarm Optimization with Non-Clique Topology

Abstract:

The modern shipboard power system integrates heavy loads and has less fault tolerance than the terrestrial power system. Therefore, a fast and high-performance reconfiguration is needed when a fault occurs. This paper proposes a method to achieve a rapid and optimal reconfiguration for shipboard power system. This method at first employs graph theory to generate the topology of particles, which can construct a non-Clique topology. Then, the particle swarm optimization algorithm with the non-Clique topology is used to improve the restoration scheme while considering constraints. The proposed Particle Swarm Optimization algorithm enables to find the optimal combination of loads that can be supplied after the occurrence of the fault.

• Periodical: Advanced Materials Research (Volumes 860-863)
• Pages: 2530-2533
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.860-863.2530
• Online since: December 2013
• Authors: Yang Chen, Yan Cheng Liu, Chuan Wang
• Keywords: Non-Clique Topology, Particle Swarm Optimization (PSO), Reconfiguration, Shipboard Power Systems (SPS)

References

[1] Ahuja A, Das S, Pahwa A. An AIS-ACO hybrid approach for multi-objective distribution system reconfiguration[J]. Power Systems, IEEE Transactions on, 2007, 22(3): 1101-1111.

DOI: 10.1109/tpwrs.2007.901286

[2] Gomes F V, Carneiro Jr S, Pereira J L R, et al. A new heuristic reconfiguration algorithm for large distribution systems[J]. Power Systems, IEEE Transactions on, 2005, 20(3): 1373-1378.

DOI: 10.1109/tpwrs.2005.851937

[3] Butler K L, Sarma N D R. General reconfiguration methodology for AC radial shipboard power systems[C]/Power Engineering Society Winter Meeting, 2000. IEEE. IEEE, 2000, 2: 1226-1230.

DOI: 10.1109/pesw.2000.850121

[4] YANG Xiuxia, ZHANG Xiaofeng, ZHANG Yi. The Study of Network Recconfiguration of The Shipboard Power System Based on Heuristic Genetic Algrithm(In Chinese) [J]. Proceedings of the CSEE, 2003，23(10)：42-46.

[5] W. P. Luan, M. R. Irving, and J. S. Daniel. Genetic Algorithm for Supply Restoration and Optimal Load Shedding in Power System Distribution Networks[J]. IEEE Proceedings of Generation, Transmission and Distribution, 2002, 149(2): 145-151.

DOI: 10.1049/ip-gtd:20020095

[6] K. Huang, D. A. Cartes, S. K. Srivastava. A Multiagent-Based Algorithm for Ring-Structured Shipboard Power System Reconfiguration[J]. IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews. 2007, 37(5): 1016-1021.

DOI: 10.1109/tsmcc.2007.900643

[7] Mitra P, Venayagamoorthy G K. Real-time implementation of an intelligent algorithm for electric ship power system reconfiguration[C]/Electric Ship Technologies Symposium, 2009. ESTS 2009. IEEE. IEEE, 2009: 219-226.

DOI: 10.1109/ests.2009.4906519