A novel hybrid particle swarm optimisation method applied to economic dispatch. (4th December 2009)

• Record Type: Journal Article
• Authors: Zhang, Tao; Cai, Jin-ding
• Is Part Of: International journal of bio-inspired computation. Volume 2:Number 1(2010)
• Page Start: 9
• Page End: 17
• Publication Date: 2009-12-04
• Subjects: economic dispatch -- particle swarm optimisation algorithm -- genetic algorithms -- GAs -- chaotic search -- valve-point effect -- globe optimisation -- dynamic inertial weight -- nonlinear optimisation -- economic load dispatch; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

Economic load dispatch is complex and non-linear problem, it is difficult to solve the problem using traditional optimisation method. PSO has been successfully applied to a wide range of applications, in solving continuous non-linear optimisation problems. This paper presents a novel hybrid PSO algorithm with dynamic inertial weight and chaotic search to solve the problem. The improved hybrid PSO enhanced the global search ability of the algorithm and improved its convergence speed. The hybrid PSO algorithm was successfully validated for two test systems. Numerical simulation results show that the modified hybrid PSO algorithm outperformed standard PSO algorithm and genetic algorithm on the same problem and can save considerable cost of economic load dispatch.