Abstract
A new multiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed in this paper. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposed MOPSO technique has been implemented to solve the EED problem with competing and non-commensurable cost and emission objectives. Several optimization runs of the proposed approach have been carried out on a standard test system. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run. The comparison with the different reported techniques demonstrates the superiority of the proposed MOPSO in terms of the diversity of the Pareto-optimal solutions obtained. In addition, a quality measure to Pareto-optimal solutions has been implemented where the results confirm the potential of the proposed MOPSO technique to solve the multiobjective EED problem and produce high quality nondominated solutions.
| Original language | English |
|---|---|
| Pages (from-to) | 1105-1113 |
| Number of pages | 9 |
| Journal | Electric Power Systems Research |
| Volume | 79 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2009 |
Bibliographical note
Funding Information:The author acknowledges the support of King Fahd University of Petroleum & Minerals via funded Project # SAB/2007-01.
Keywords
- Environmental/economic dispatch
- Multiobjective optimization
- Nondominated solutions
- Pareto-optimal front
- Particle swarm optimization
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
