Research ArticleOpen AccessGoogle Scholar indexed
Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm
Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
- 1 Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
- 2 Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
- 3 Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
- 4 Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
- 5 Center for Electric Power and Energy, Technical University of Denmark, Copenhagen, Denmark
Energy and Power Engineering·Volume 05 (2013)·Pages 975–979·Published 30 June 2013·DOI10.4236/epe.2013.54B187
Copy link · social · email
Abstract
This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.
KeywordsDistribution Network Expansion PlanningTwo-phaseMulti-objective PSO
- A. Barin, L. F. Pozzatti, L. N. Canha, et al., “Multi-objective Analysis of Impacts of Distributed Generation Placement on the Operational Characteristics of Networks for Distribution System Planning,” International Journal of Electrical Power & Energy Systems, Vol. 32, 2010, pp. 1157-1164. doi:10.1016/j.ijepes.2010.06.015
- Z. Kai, A. P. Agalgaonkar, K. M. Muttaqi and S. Perera, “Multi-objective Optimization for Distribution System Planning with Renewable Energy Resources,” in Proc. 2010 IEEE International Energy Conference, pp. 670-675.
- A. H. Mantway and M. M. Al-Muhaini, “Multi-objective BPSO Algorithm for Distribution System Expansion Planning Including Distributed Generation,” in Proc. 2008 IEEE International Transmission & Distribution, pp. 134-141.
- R. Rosado and D. Navarro, “Possibilistic Model Based on Fuzzy Sets for the Multiobjective Optimal Planning of Electric Power Distribution Networks,” IEEE Trans. Power Systems, Vol. 19, 2004, pp. 1801-1810. doi:10.1109/TPWRS.2004.835678
- A. Soroudi and M. Ehsan, “A Distribution Network Expansion Planning Model Considering Distributed Generation Options and Techo-Economical Issues,” International Journal of Energy, Vol. 35, 2010, pp. 3364-3374.
- E. G. Carrano, F. G. Guimaraes, R. H. C. Takahashi, et al., “Electric Distribution Network Expansion Under Load-Evolution Uncertainty Using an Immune System Inspired Algorithm,” IEEE Trans. Power Systems, Vol. 22, 2007, pp. 851-861.
- T. S. Chung, K. K. Lee, G. J. Chen, J. D. Xie and G. Q. Tang, “Multi-Objective Transmission Network Planning by a Hybrid GA Approach with Fuzzy Decision Analysis,” International Journal of Electrical Power & Energy Systems, Vol. 25, 2003, pp. 187-192.
- R. Poli, J. Kennedy and T. Blackwell, Particle swarm optimization an overview, Vol. I. MIT: Wiley, 2010, p. 2.
- A. M. R. Sierra and C. A. Coello, “Multi-objective Particle Swarm Optimizers: A Survey of the State-of-the-art,” International Journal of Computational Intelligence Research, Vol. 3, 2006, pp. 287-308.
- S. Mostaghim and J. Teich, “Strategies for finding good local guides in multi-objective particle swarm optimization (MOP-SO),” in Proc. 2003 IEEE Swarm Intelligence Symposium, pp. 26-33.
- M. S. Lechuga, and C. A. Coello, “Handling Multiple Objectives with Particle Swarm Optimization,” IEEE Trans. Evolutionary Computation, Vol. 3, 2006, pp. 256-279.
- N. C. Sahoo, S. Ganguly and D. Das, “Fuzzy-Pareto-dominance Driven Possibilistic Model Based Planning of Electrical Distribution Systems Using Multi-objective Particle Swarm Optimization,” Expert Systems with Applications, Vol. 39, 2012, pp. 881-893. doi:10.1016/j.eswa.2011.07.086