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Modified particle swarm optimization for nonconvex economic dispatch problems
- Source :
- International Journal of Electrical Power & Energy Systems. 69:304-312
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- This paper presents modified particle swarm optimization to solve economic dispatch problems with non-smooth/non-convex cost functions. Particle swarm optimization performs well for small dimensional and less complicated problems but fails to locate global minima for complex multi-minima functions. This paper proposes Gaussian random variables in velocity term which improves search efficiency and guarantees a high probability of obtaining the global optimum without considerably worsening the speed of convergence and the simplicity of the structure of particle swarm optimization. The efficacy of the proposed method has been demonstrated on four test problems and four different non-convex economic dispatch problems with valve-point effects, prohibited operating zones with transmission losses, multiple fuels with valve point effects and the large-scale Korean power system with valve-point effects and prohibited operating zones. The results of the proposed approach are compared with those obtained by other evolutionary methods reported in the literature. It is found that the proposed modified particle swarm optimization based approach is able to provide better solution.
- Subjects :
- Mathematical optimization
Engineering
business.industry
Economic dispatch
Energy Engineering and Power Technology
Particle swarm optimization
Maxima and minima
Electric power system
Convergence (routing)
Electrical and Electronic Engineering
Multi-swarm optimization
business
Metaheuristic
Random variable
Subjects
Details
- ISSN :
- 01420615
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- International Journal of Electrical Power & Energy Systems
- Accession number :
- edsair.doi...........fb2c709365b02f482631a975bfaa3ad5