Environmental/economic dispatch using multi-objective harmony search algorithm

This paper presents a new multi-objective harmony search (MOHS) algorithm for environmental/economic dispatch (EED) problem. The EED problem is formulated as a non linear and constrained optimization problem with competing and non-commensurable objectives. The two competing objectives, fuel cost and emission, were optimized simultaneously using the proposed MOHS algorithm. The MOHS algorithm uses a non dominated sorting and ranking procedure with dynamic crowding distance to develop and maintain a well distributed Pareto-optimal set. The proposed algorithm has been tested on the standard IEEE 30 bus and 118 bus systems. Simulation results are compared with the fast non dominated sorting genetic algorithm (NSGA-II) method. The results clearly show that the proposed method is able to produce a well distributed Pareto-optimal solutions than the NSGA-II method.

[1]  T. Yalcinoz,et al.  A multiobjective optimization method to environmental economic dispatch , 2007 .

[2]  M. A. Abido.  Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003 .

[3]  A. A. El-Keib,et al.  Economic dispatch in view of the Clean Air Act of 1990 , 1994 .

[4]  Yaonan Wang,et al.  Environmental/economic power dispatch problem using multi-objective differential evolution algorithm , 2010 .

[5]  M. A. Abido,et al.  Multiobjective particle swarm optimization for environmental/economic dispatch problem , 2009 .

[6]  M. Mahdavi,et al.  ARTICLE IN PRESS Available online at www.sciencedirect.com , 2007 .

[7]  G. P. Granelli,et al.  Emission constrained dynamic dispatch , 1992 .

[8]  S. A. Al-Baiyat,et al.  Economic load dispatch multiobjective optimization procedures using linear programming techniques , 1995 .

[9]  Ferial El-Hawary,et al.  A summary of environmental/economic dispatch algorithms , 1994 .

[10]  Lingfeng Wang,et al.  Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm , 2007 .

[11]  Mohammad Ali Abido,et al.  Multiobjective evolutionary algorithms for electric power dispatch problem , 2006, IEEE Transactions on Evolutionary Computation.

[12]  D. P. Kothari,et al.  Multiobjective optimal thermal power dispatch , 1994 .

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

[14]  Leandro dos Santos Coelho,et al.  An improved harmony search algorithm for power economic load dispatch , 2009 .

[15]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[16]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[17]  Yong Zhang,et al.  Environmental/economic power dispatch using a hybrid multi-objective optimization algorithm , 2010 .

[18]  P. K. Chattopadhyay,et al.  Application of Biogeography-based Optimization for Solving Multi-objective Economic Emission Load Dispatch Problems , 2010 .

[19]  Jun Wu,et al.  Dynamic Crowding Distance?A New Diversity Maintenance Strategy for MOEAs , 2008, 2008 Fourth International Conference on Natural Computation.

[20]  K. S. Swarup,et al.  Solving multi-objective optimal power flow using differential evolution , 2008 .

[21]  M. Fesanghary,et al.  A novel meta-heuristic optimization methodology for solving various types of economic dispatch problem , 2009 .

[22]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..