Faculty of Electrical Engineering, Babol University of Technology, Babol, Iran
Abstract
Economic dispatch at minimum production cost is one of the most important subjects in the power system operation, which is a complicated nonlinear constrained optimization problem. To solve the dynamic economic dispatch problem, it is assumed that a thermal unit commitment has been previously determined. Since dynamic economic load dispatch was introduced, several methods have been used to solve this problem. However, all of those methods may not be able to provide an optimal solution and usually getting stuck at a local optimal. In this paper, an Improved Particle Swarm Optimizer (IPSO) has been proposed to solve dynamic economic load dispatch problem. This algorithm is applied to a complex dynamic economic dispatch problem for 6-unit power systems with a 24-h load demand at each 1-h time intervals. Comparing IPSO results with other methods' results that reported in literature shows the ability of IPSO to reach better solutions.
Khosravi, A., Gholamian, A., & Yazdani Asrami, M. (2015). Improved Particle Swarm Optimization Algorithm for Solving Dynamic Economic Load Dispatch. Journal of Soft Computing and Information Technology, 4(3), 76-82.
MLA
AliReza Khosravi; Asghar Gholamian; Mohammad Yazdani Asrami. "Improved Particle Swarm Optimization Algorithm for Solving Dynamic Economic Load Dispatch". Journal of Soft Computing and Information Technology, 4, 3, 2015, 76-82.
HARVARD
Khosravi, A., Gholamian, A., Yazdani Asrami, M. (2015). 'Improved Particle Swarm Optimization Algorithm for Solving Dynamic Economic Load Dispatch', Journal of Soft Computing and Information Technology, 4(3), pp. 76-82.
VANCOUVER
Khosravi, A., Gholamian, A., Yazdani Asrami, M. Improved Particle Swarm Optimization Algorithm for Solving Dynamic Economic Load Dispatch. Journal of Soft Computing and Information Technology, 2015; 4(3): 76-82.
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