An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems
Konkuk University · Baylor University
Indexed incrossref
Abstract
This paper presents an efficient approach for solving economic dispatch (ED) problems with nonconvex cost functions using an improved particle swarm optimization (IPSO). Although the particle swarm optimization (PSO) approaches have several advantages suitable to heavily constrained nonconvex optimization problems, they still can have the drawbacks such as local optimal trapping due to premature convergence (i.e., exploration problem), insufficient capability to find nearby extreme points (i.e., exploitation problem), and lack of efficient mechanism to treat the constraints (i.e., constraint handling problem). This paper proposes an improved PSO framework employing chaotic sequences combined with the…
Citation impact
621
total citations
- FWCI
- 22.58
- Percentile
- 100%
- References
- 32
Citations per year
Authors
4Topics & keywords
Topics
Keywords
- Mathematical optimization
- Economic dispatch
- Particle swarm optimization
- Premature convergence
- Convergence (economics)
- Constraint (computer-aided design)
- Electric power system
- Optimization problem
No related works found for this paper.