Abstract
A comparative study of newly developed Pareto-based Multi-Objective Evolutionary Algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. Specifically, Niched Pareto Genetic Algorithm (NPGA), Nondominated Sorting Genetic Algorithm (NSGA), and Strength Pareto Evolutionary Algorithm (SPEA) have been developed and successfully applied to Environmental/Economic electric power Dispatch (EED) problem. These multiobjective evolutionary algorithms have been individually examined and applied to the standard IEEE 30-bus test system. A feasibility check procedure has been developed and superimposed on MOEA to restrict the search to the feasible region of the problem space. The results of MOEA have been compared to those reported in the literature. The comparison shows the superiority of MOEA to the traditional multiobjective optimization techniques and confirms their potential to handle power system multiobjective optimization problems.
| Original language | English |
|---|---|
| Title of host publication | 2003 IEEE Power Engineering Society General Meeting, Conference Proceedings |
| Pages | 920-925 |
| Number of pages | 6 |
| State | Published - 2003 |
Publication series
| Name | 2003 IEEE Power Engineering Society General Meeting, Conference Proceedings |
|---|---|
| Volume | 2 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- Economic power dispatch
- Emission reduction
- Environmental impact
- Evolutionary algorithms
- Multiobjective optimization
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- General Engineering
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