Hybrid Differential Evolution and Gravitational Search Algorithm for Nonconvex Economic Dispatch

The hybrid differential evolution and gravitational search algorithm (DEGSA) to solve economic dispatch (ED) problems with non-convex cost functions is presented in this paper with various generator constraints in power systems. The proposed DEGSA method is an improved differential evolution method based on the gravitational search algorithm scheme. The DEGSA method has the flexible adjustment of the parameters to get a better optimal solution. Moreover, an effective constraint handling framework in the method is employed for properly handling equality and inequality constraints of the problems. The proposed DEGSA has been tested on three systems with 13, 15, 40 units and the obtained results from the DEGSA algorithm have been compared to those from other methods in the literature. The result comparison has indicated that the proposed DEGSA method is more effective than many other methods for obtaining better optimal solution for the test systems. Therefore, the proposed DEGSA is a very favorable method for solving the non-convex ED problems.

[1]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[2]  Zwe-Lee Gaing,et al.  Particle swarm optimization to solving the economic dispatch considering the generator constraints , 2003 .

[3]  L. Coelho,et al.  Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect , 2006, IEEE Transactions on Power Systems.

[4]  P. K. Chattopadhyay,et al.  Evolutionary programming techniques for economic load dispatch , 2003, IEEE Trans. Evol. Comput..

[5]  S. Khamsawang,et al.  Solving the economic dispatch problem with tabu search algorithm , 2002, 2002 IEEE International Conference on Industrial Technology, 2002. IEEE ICIT '02..

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

[7]  Whei-Min Lin,et al.  An Improved Tabu Search for Economic Dispatch with Multiple Minima , 2002, IEEE Power Engineering Review.

[8]  Hong-Tzer Yang,et al.  Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions , 1996 .

[9]  Leandro dos Santos Coelho,et al.  Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems , 2009, Math. Comput. Simul..

[10]  Chih-Wen Liu,et al.  Non-smooth/non-convex economic dispatch by a novel hybrid differential evolution algorithm , 2007 .

[11]  Fuli Wang,et al.  Hybrid genetic algorithm for economic dispatch with valve-point effect , 2008 .

[12]  Y. W. Wong,et al.  Genetic and genetic/simulated-annealing approaches to economic dispatch , 1994 .

[13]  Hossein Shayeghi,et al.  Iteration particle swarm optimization procedure for economic load dispatch with generator constraints , 2011, Expert Syst. Appl..

[14]  H. Iba,et al.  Differential evolution for economic load dispatch problems , 2008 .

[15]  Vo Ngoc Dieu,et al.  A hybrid differential evolution and harmony search for nonconvex economic dispatch problems , 2013, 2013 IEEE 7th International Power Engineering and Optimization Conference (PEOCO).

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

[17]  Taher Niknam,et al.  A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem , 2010 .

[18]  Wen-Chih Peng,et al.  Particle Swarm Optimization With Recombination and Dynamic Linkage Discovery , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[19]  Kit Po Wong,et al.  Solving power system optimization problems using simulated annealing , 1995 .

[20]  A. Ebenezer Jeyakumar,et al.  Hybrid PSO–SQP for economic dispatch with valve-point effect , 2004 .

[21]  M. Pandit,et al.  Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch , 2008, IEEE Transactions on Power Systems.

[22]  Sishaj P. Simon,et al.  Artificial Bee Colony Algorithm for Economic Load Dispatch Problem with Non-smooth Cost Functions , 2010 .

[23]  Hossein Nezamabadi-pour,et al.  Filter modeling using gravitational search algorithm , 2011, Eng. Appl. Artif. Intell..

[24]  C.H. Chen,et al.  Particle Swarm Optimization for Economic Power Dispatch with Valve-Point Effects , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.