Distribution System Restoration Based on Hybrid Particle Swarm

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Abstract:

By the heuristic algorithm and particle swarm optimization algorithm combining hybrid particle swarm algorithm proposed combination of heuristic search and stochastic optimization,stochastic optimization process using a spanning tree and the loop matrix operations combined to ensure the system topology constraints to improve the efficiency of solution. The analysis shows that the proposed method calculation speed,easy to converge to the global optimal solution. It can effectively solve the problem of distribution network fault recovery.

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Periodical:

Advanced Materials Research (Volumes 732-733)

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662-668

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Hsiao-Dong Chiang, Z. J. QUAN. Approach for Identification and Computation of Static Voltage Stability Critical Point. IEEE Transactions on Power Systems . (1995)

Google Scholar

[2] Z.Q. LU, X.Y. Dong. Distribution System Restoration Based on Improved Binary Particle Swarm Optimization. Automation of Electric Power System, Vol. 30(2006), pp.39-42

Google Scholar

[3] W.C. Wu, B.M. Zhang. A candidate restoring tree cutting based algorithm for real-time distribution system restoration. Automation of Electric Power System, Vol.32 (2003), pp.50-54

Google Scholar

[4] J.Q.CHEN, Y.F.TANG. Reliability Design Optimization of Composite Structures Based on PSO together with FEA

Google Scholar

[5] K. Liu and HD. Chiang, "Electric distribution system load capability: Problem formulation, solution algorithm, and numerical results," IEEE Trans. Power Del., Vol. 15, (2000) pp.436-442

DOI: 10.1109/61.847286

Google Scholar

[6] J.K LIN, X.D. WANG. Distribution Network Reconfiguration Based on Feasible Solution Search and Adaptive Immune Algorithm. Journal of Tianjin University.Vol.12 (2008) pp.76-81

Google Scholar