Swarm Intelligence in Power System Planning

ABSTRACT

Power system planning is one of the essential tasks in the power system operation management, which requires in-depth knowledge of the system under consideration. It can be regarded as a nonlinear, discontinuous, constrained multi objective optimization problem. Although the traditional optimization tools can be used, the modern planning problem requires more advanced optimization tools. In this paper, a survey of state-of-the-art mathematical optimization methods that facilitates power system planning is provided, and the needs of introducing swarm intelligence approaches into power system planning are discussed.

Power system planning is one of the essential tasks in the power system operation management, which requires in-depth knowledge of the system under consideration. It can be regarded as a nonlinear, discontinuous, constrained multi objective optimization problem. Although the traditional optimization tools can be used, the modern planning problem requires more advanced optimization tools. In this paper, a survey of state-of-the-art mathematical optimization methods that facilitates power system planning is provided, and the needs of introducing swarm intelligence approaches into power system planning are discussed.

Cite this paper

K. Meng, Z. Y. Dong and Y. C. Qiao, "Swarm Intelligence in Power System Planning,"*International Journal of Clean Coal and Energy*, Vol. 2 No. 2B, 2013, pp. 1-7. doi: 10.4236/ijcce.2013.22B001.

K. Meng, Z. Y. Dong and Y. C. Qiao, "Swarm Intelligence in Power System Planning,"

References

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[1] F. F. Wu, Z. Yen, Y. H. Hou and Y. X. Ni, “Applications of AI Techniques to Generation Planning and Investment,” 2004 IEEE Power Engineering Society General Meeting, Vol. 1, 2004, pp. 936-940.

[2] G. Y. Yang, “Applying Advanced Methods to Power System Planning Studies,” Ph.D. thesis, the University of Queensland, Brisbane, Australia, Oct. 2008.

[3] A. Mazer, “Electric Power Planning for Regulated and Deregulated Markets,” IEEE Press, Wiley Inter-science, 2007.

[4] J. H. Zhao, Z. Y. Dong, P. Lindsay and K. P. Wong, “Flexible Transmission Expansion Planning with Uncertainties in an Electricity Market,” IEEE Transactions on Power Systems, Vol. 24, No. 1, 2009, pp. 479-488. doi.org/10.1109/TPWRS.2008.2008681

[5] E. Bonabeau, M. Dorigo and G. Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems,” 1st ed, London, U.K.: Oxford Univ., 1999.

[6] J. Kennedy, R. Eberhart and Y. Shi, “Swarm Intelligence,” 1st ed. San Mateo, CA: Morgan Kaufmann, 2001.

[7] A. Engelbrecht, “Fundamentals of Computational Swarm Intelligence” 1st ed. New York: Wiley, 2005.

[8] A. Engelbrecht, X. Li, M. Middendorf and L.M. Gambardella, “Editorial Special Issue: Swarm Intelligence,” IEEE Transactions on Evolutionary Computation, Vol. 13, No. 4, 2009, pp. 677-680. doi:10.1109/TEVC.2009.2022002

[9] D. Merkle and M. Middendorf, “Swarm Intelligence and Signal Processing,” IEEE Signal Processing Magazine, Vol. 25, No. 6, 2008, pp. 152-158. doi:10.1109/MSP.2008.929839

[10] M. G. Hinchey, R. Sterritt and C. Rouff, “Swarms and Swarm Intelligence,” Computers, Vol. 40, No. 4, 2007, pp. 111-113. doi:10.1109/MC.2007.144

[11] M. Dorigo and T. Stützle, “Ant Colony Optimization,” Cambridge, MA: MIT Press, Vol. 3172, 2004, pp. 1-12. doi:10.1007/b99492

[12] S. Goss, S. Aron, J. L. Deneubourg and J. M. Pasteels, “Self-Organized Shortcuts in the Argentine Ant,” Naturwissenschaften, Vol. 76, No. 12, 1989, pp. 579-581. doi:10.1007/BF00462870

[13] M. Dorigo, M. Birattari and T. Stützle, “Ant Colony Optimization: Artificial Ants as a Computational Intelligence Technique,” Computational Intelligence Magazine on IEEE, Vol. 1, No. 4, 2006, pp. 28-39. doi:10.1109/MCI.2006.329691

[14] T. Stützle and M. Dorigo, “ACO Algorithms for the Quadratic Assignment Problem,” in D. Corne, M. Dorigo, and F. Glover, (eds): New Ideas in Optimization, New York: McGraw-Hill, 1999.

[15] M. Dorigo, V. Maniezzo and A. Colorni, “Ant System: Optimization by a Colony of Cooperating Agents,” IEEE Trans. Syst., Man, Cybern. Part-B, Vol. 26, No. 1, 1996, pp. 29-41.

[16] M. Birattari, P. Pellegrini and M. Dorigo, “On the Invariance of Ant Colony Optimization,” IEEE Transactions on Evolutionary Computation, Vol. 11, No. 6, 2007, pp. 732-742. doi:10.1109/TEVC.2007.892762

[17] M. Dorigo and L. M. Gambardella, “Ant Colony Sstem: A Cooperative learning approach to the traveling salesman problem,” IEEE Transactions on Evolutionary Computation, Vol. 1, No. 1, 1997, pp. 53-66. doi:10.1109/4235.585892

[18] M. Zlochin, M. Birattari, N. Meuleau and M. Dorigo, “Model-based Search for Combinatorial Optimization: A Critical Survey,” Annals of Operations Research, Vol. 131, No. 1-4, 2004, pp. 373-395. doi:10.1023/B:ANOR.0000039526.52305.af

[19] J. Kennedy and R. Eberhart, “Particle Swarm Otimization,” IEEE Int. Conf. Neural Network, Perth, Australia, 1995, pp. 1942-1948.

[20] J. Kennedy, “The Particle Swarm: Social Adaptation of Knowledge,” IEEE Int. Conf. Evol. Comput., 1997, pp. 303-308.

[21] J. Kennedy, “Small Worlds and Megaminds: Effects of NCZGDbourhood Topology on Particle Swarm Performance,” Proc. IEEE Congr. Evol. Comput., Vol. 3, 1999, pp. 1931-1938.

[22] Y. Shi and R. Eberhart, “Parameter Selection in Particle Swarm Optimization,” Lecture Notes in Computer Science, Vol. 1447, 1998, pp. 591-600. doi:10.1007/BFb0040810

[23] Y. del Valle, G. K. Venayagamoorthy, S. Mohagheghi, J. C. Hernandez and R. G. Harley, “Particle Swarm Optimization: Basic Concepts, Variants and Applications in power Systems,” IEEE Transactions on Evolutionary Computation, Vol. 12, No. 2, 2008, pp. 171-195. doi:10.1109/TEVC.2007.896686

[24] Z. Y. Dong, K. P. Wong, X. Zhou and C. Ziser, “New Issues on Reliable and Efficient Operation of the National Electricity Market of Australia”, Proc DRPT, 2008, Nanjing, China, Apr 2008.

[25] P. Masse and R. Gilbrat, “Application of Linear Programming to Investments in the Electric Power Industry,” Management Science, Vol. 3, No. 2, 1957, pp. 149-166. doi:10.1287/mnsc.3.2.149

[26] W. Rutz, M. Becker, F. E. Wicks and S. Yerazunis, “Sequential Objective Linear Programming for Generation Planning,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-98, No. 6, 1979, pp. 2015-2021. doi:10.1109/TPAS.1979.319394

[27] J. K. Delson and S. M. Shahidehpour, “Linear Programming Applications to Power System Economics, Planning and Operations,” IEEE Transactions on Power Systems, Vol. 7, No. 3, 1992, pp. 1155-1163. doi:10.1109/59.207329

[28] A. Ramos, I. J. Perez-Arriaga and J. Bogas, “A Nonlinear Programming Approach to Optimal Static Generation expansion Planning,” IEEE Transactions on Power Systems, Vol. 4, No. 3, 1989, pp. 1140-1146. doi:10.1109/59.32610

[29] R. T. Jenkins and D. S. Joy, “Wien Automatic System Planning Package (WASP) - An Electric Utility Optimal Generation Expansion Planning Computer Code,” Oak Ridge National Laboratory, Oak Ridge, TN, ORNL 4945, 1974.

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