JOURNAL ARTICLE

Application of Multi Objective Evolutionary Programming to Combined Economic Emission Dispatch Problem

D.N. JeyakumarP. VenkateshKwang Y. Lee

Year: 2007 Journal:   IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks Pages: 1162-1167   Publisher: Institute of Electrical and Electronics Engineers

Abstract

This paper describes a new multi-objective evolutionary programming (MOEP) method to solve the combined economic emission dispatch (CEED) problem. CEED is a multi-objective optimization problem by considering the fuel cost and emission as the objectives. It is converted into single objective optimization problem using weighted sum method. Hence the MOEP is proposed by employing the non-dominated solution ranking as selection mechanism for the bi-objective CEED problem. The developed algorithm is tested for a three-unit and a six-unit system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective CEED problem in a single run.

Keywords:
Mathematical optimization Economic dispatch Computer science Ranking (information retrieval) Pareto principle Multi-objective optimization Evolutionary algorithm Selection (genetic algorithm) Evolutionary programming Optimization problem Artificial intelligence Mathematics Electric power system

Metrics

30
Cited By
4.13
FWCI (Field Weighted Citation Impact)
22
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Electric Power System Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Efficiency and Management
Physical Sciences →  Energy →  Renewable Energy, Sustainability and the Environment
Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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