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Immune algorithm for solving the smooth economic dispatch problem
Keywords:
Artificial immune systems, economic dispatch problem, metaheuristicsAbstract
In this paper, an algorithm inspired on the T- Cell model of the immune system is presented, it is used to solve Economic Dispatch Problems with smooth objective function. The proposed approach is called IA EDP S, which stands for Immune Algorithm for Economic Dispatch Prob- lem for smooth objective function, and it uses as differentiation process a redistribution power op- erator. The proposed approach is validated using five problems taken from the specialized litera- ture. Our results are compared with respect to those obtained by several other approaches.
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References
[1] N. Amjady and H. Sharifzadeh. Solution of non-convex economic dispatch problem considering valve loading effect by a new modified differential evolution algorithm. International Journal of Electrical Power and Energy Systems, 32(8):893–903, 2010.
[2] V.S. Aragon, S.C. Esquivel, and C.A. Coello Coello. An immune algorithm with power redistribution for solving economic dispatch problems. Information Sciences, 295(0):609– 632, 2015.
[3] A. Bhattacharya and P.K. Chattopadhyay. Biogeography-based optimization for different economic load dispatch problems. IEEE Transactions on Power Systems, 25(2):1064–1077, 2010.
[4] Leticia Cecilia Cagnina, Susana Cecilia Esquivel, and Carlos A. Coello Coello. A fast particle swarm algorithm for solving smooth and non-smooth economic dispatch problems. Engineering Optimization, 43(5):485–505, 2011.
[5] Cheng-Chien Kuo. A novel coding scheme for practical economic dispatch by modified particle swarm approach. IEEE Transactions on Power Systems, 23(4):1825–1835, 2008.
[6] Leandro Nunes de Castro and Jonathan Timmis. Artificial Immune Systems: A New Computational Intelligence Approach. Springer-Verlag, New York, 2002.
[7] V.R. Pandi, K.B. Panigrahi, M.K. Mallick, A. Abraham, and S. Das. Improved harmony search for economic power dispatch. In Hybrid Intelligent Systems, 2009. HIS’09. Ninth International Conference on, volume 3, pages 403–408, 2009.
[8] J.-B. Park, Y.-W. Jeong, J.-R. Shin, and K.Y. Lee. An improved particle swarm optimization for nonconvex economic dispatch problems. IEEE Transactions on Power Systems, 25(1):156–166, 2010.
[9] Jong-Bae Park, Ki-Song Lee, Joong-Rin Shin, and K.Y. Lee. A particle swarm optimization for economic dispatch with nonsmooth cost functions. Power Systems, IEEE Transactions on, 20(1):34–42, 2005.
[10] Y. M. Park, J. R. Won, and J. B. Park. A new approach to economic load dispatch based on improved evolutionary programming. Eng. Intell. Syst. Elect. Eng. Commun., 6(2):103–110, June 1998.
[11] P. Sriyanyong, Y.H. Song, and P.J. Turner. Particle swarm optimisation for operational planning: Unit commitment and economic dispatch. In KeshavP. Dahal, KayChen Tan, and PeterI. Cowling, editors, Evolutionary Scheduling, volume 49 of Studies in Computational Intelligence, pages 313–347. Springer Berlin Heidelberg, 2007.
[12] S. Siva Subramani and P. Raja Rajeswari. A modified particle swarm optimization for economic dispatch problems with non-smooth cost functions. International Journal of Soft Computing, 3(4):326–332, 2008.
[13] J.G. Vlachogiannis and K.Y. Lee. Economic load dispatch a comparative study on heuristic optimization techniques with an improved coordinated aggregation-based pso. IEEE Transactions on Power Systems, 24(2):991–1001, 2009.
[14] Ling Wang and Ling po Li. An effective differential harmony search algorithm for the solving non-convex economic load dispatch problems. International Journal of Electrical Power & Energy Systems, 44(1):832 – 843, 2013.
[2] V.S. Aragon, S.C. Esquivel, and C.A. Coello Coello. An immune algorithm with power redistribution for solving economic dispatch problems. Information Sciences, 295(0):609– 632, 2015.
[3] A. Bhattacharya and P.K. Chattopadhyay. Biogeography-based optimization for different economic load dispatch problems. IEEE Transactions on Power Systems, 25(2):1064–1077, 2010.
[4] Leticia Cecilia Cagnina, Susana Cecilia Esquivel, and Carlos A. Coello Coello. A fast particle swarm algorithm for solving smooth and non-smooth economic dispatch problems. Engineering Optimization, 43(5):485–505, 2011.
[5] Cheng-Chien Kuo. A novel coding scheme for practical economic dispatch by modified particle swarm approach. IEEE Transactions on Power Systems, 23(4):1825–1835, 2008.
[6] Leandro Nunes de Castro and Jonathan Timmis. Artificial Immune Systems: A New Computational Intelligence Approach. Springer-Verlag, New York, 2002.
[7] V.R. Pandi, K.B. Panigrahi, M.K. Mallick, A. Abraham, and S. Das. Improved harmony search for economic power dispatch. In Hybrid Intelligent Systems, 2009. HIS’09. Ninth International Conference on, volume 3, pages 403–408, 2009.
[8] J.-B. Park, Y.-W. Jeong, J.-R. Shin, and K.Y. Lee. An improved particle swarm optimization for nonconvex economic dispatch problems. IEEE Transactions on Power Systems, 25(1):156–166, 2010.
[9] Jong-Bae Park, Ki-Song Lee, Joong-Rin Shin, and K.Y. Lee. A particle swarm optimization for economic dispatch with nonsmooth cost functions. Power Systems, IEEE Transactions on, 20(1):34–42, 2005.
[10] Y. M. Park, J. R. Won, and J. B. Park. A new approach to economic load dispatch based on improved evolutionary programming. Eng. Intell. Syst. Elect. Eng. Commun., 6(2):103–110, June 1998.
[11] P. Sriyanyong, Y.H. Song, and P.J. Turner. Particle swarm optimisation for operational planning: Unit commitment and economic dispatch. In KeshavP. Dahal, KayChen Tan, and PeterI. Cowling, editors, Evolutionary Scheduling, volume 49 of Studies in Computational Intelligence, pages 313–347. Springer Berlin Heidelberg, 2007.
[12] S. Siva Subramani and P. Raja Rajeswari. A modified particle swarm optimization for economic dispatch problems with non-smooth cost functions. International Journal of Soft Computing, 3(4):326–332, 2008.
[13] J.G. Vlachogiannis and K.Y. Lee. Economic load dispatch a comparative study on heuristic optimization techniques with an improved coordinated aggregation-based pso. IEEE Transactions on Power Systems, 24(2):991–1001, 2009.
[14] Ling Wang and Ling po Li. An effective differential harmony search algorithm for the solving non-convex economic load dispatch problems. International Journal of Electrical Power & Energy Systems, 44(1):832 – 843, 2013.
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Published
2015-11-01
How to Cite
Aragón, V. S., & Esquivel, S. C. (2015). Immune algorithm for solving the smooth economic dispatch problem. Journal of Computer Science and Technology, 15(02), p. 137–142. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/542
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