Application and Comparison of PSO, its Variants and HDE Techniques to Emission/Economic Dispatch

The conventional particle swarm optimization (PSO) algorithm known for its global searching capabilities has been successfully applied to emission/economic dispatch (EED) problems. In this paper, the applicability of PSO and its four variants, namely, self-adaptive PSO, dispersed PSO, chaotic PSO and new PSO to emission/economic dispatch problems has been presented. Furthermore, the employability of hybrid differential evolution (HDE) technique to EED problems is also proved here. Two numerical examples are tested—one having 9 units, and limits on SO2 and NOx emissions and the other having 6 units with NOx emission and B-loss co-efficients. Results obtained are compared with those reported in literature. The comparison of the results shows that the conventional PSO, its variants and HDE algorithm converge to optimal or near optimal solutions in the two examples tested in this paper. But the convergence time in HDE is far greater when compared with PSO and its variants.

[1]  C. S. Chang,et al.  Security-constrained multiobjective generation dispatch using bicriterion global optimisation , 1995 .

[2]  Ying Tan,et al.  Dispersed particle swarm optimization , 2008, Inf. Process. Lett..

[3]  Rui Wang,et al.  A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problem , 2010, ICSI.

[4]  D. P. Kothari,et al.  Stochastic economic emission load dispatch , 1993 .

[5]  Rainer Storn,et al.  Minimizing the real functions of the ICEC'96 contest by differential evolution , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[6]  Ying Wang,et al.  Environmental/economic dispatch problem of power system by using an enhanced multi-objective differential evolution algorithm , 2011 .

[7]  Bijay Ketan Panigrahi,et al.  Multiobjective bacteria foraging algorithm for electrical load dispatch problem , 2011 .

[8]  J. Yuryevich,et al.  Evolutionary-programming-based algorithm for environmentally-constrained economic dispatch , 1998 .

[9]  A. Selvakumar,et al.  A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems , 2007, IEEE Transactions on Power Systems.

[10]  Kao-Shing Hwang,et al.  CO-EVOLUTIONARY HYBRID DIFFERENTIAL EVOLUTION FOR MIXED-INTEGER OPTIMIZATION PROBLEMS , 2001 .

[11]  J. W. Lamont,et al.  Emission dispatch models and algorithms for the 1990s , 1995 .

[12]  Jiang Chuanwen,et al.  A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation , 2005, Math. Comput. Simul..

[13]  P. K. Chattopadhyay,et al.  Solving economic emission load dispatch problems using hybrid differential evolution , 2011, Appl. Soft Comput..

[14]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[15]  K. S. Swarup,et al.  Environmental/economic dispatch using multi-objective harmony search algorithm , 2011 .

[16]  Rahmat-Allah Hooshmand,et al.  Emission, reserve and economic load dispatch problem with non-smooth and non-convex cost functions using the hybrid bacterial foraging-Nelder–Mead algorithm , 2012 .

[17]  Dun-Wei Gong,et al.  A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch , 2012, Inf. Sci..

[18]  S. Baskar,et al.  Application of modified NSGA-II algorithm to Combined Economic and Emission Dispatch problem , 2011 .

[19]  Xuehu Yan,et al.  An Improved Algorithm for Iris Location , 2007 .

[20]  Chunming Yang,et al.  A new particle swarm optimization technique , 2005, 18th International Conference on Systems Engineering (ICSEng'05).

[21]  Narayana Prasad Padhy,et al.  Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints , 2003 .

[22]  P. K. Chattopadhyay,et al.  Hybrid differential evolution with biogeography-based optimization algorithm for solution of economic emission load dispatch problems , 2011, Expert Syst. Appl..

[23]  Jianzhong Zhou,et al.  A Self-Adaptive Particle Swarm Optimization Algorithm with Individual Coefficients Adjustment , 2007 .

[24]  Ioan Cristian Trelea,et al.  The particle swarm optimization algorithm: convergence analysis and parameter selection , 2003, Inf. Process. Lett..