A Novel Multiobjective Genetic Algorithm Based Technique for Economic Emission Load Dispatch Optimization Problem
Mousa, A., El-Desoky, I. (2008). A Novel Multiobjective Genetic Algorithm Based Technique for Economic Emission Load Dispatch Optimization Problem. EKB Journal Management System, 6(6th International Conference on Electrical Engineering ICEENG 2008), 1-20. doi: 10.21608/iceeng.2008.34524
A. A. Mousa; I. M. El-Desoky. "A Novel Multiobjective Genetic Algorithm Based Technique for Economic Emission Load Dispatch Optimization Problem". EKB Journal Management System, 6, 6th International Conference on Electrical Engineering ICEENG 2008, 2008, 1-20. doi: 10.21608/iceeng.2008.34524
Mousa, A., El-Desoky, I. (2008). 'A Novel Multiobjective Genetic Algorithm Based Technique for Economic Emission Load Dispatch Optimization Problem', EKB Journal Management System, 6(6th International Conference on Electrical Engineering ICEENG 2008), pp. 1-20. doi: 10.21608/iceeng.2008.34524
Mousa, A., El-Desoky, I. A Novel Multiobjective Genetic Algorithm Based Technique for Economic Emission Load Dispatch Optimization Problem. EKB Journal Management System, 2008; 6(6th International Conference on Electrical Engineering ICEENG 2008): 1-20. doi: 10.21608/iceeng.2008.34524

A Novel Multiobjective Genetic Algorithm Based Technique for Economic Emission Load Dispatch Optimization Problem

The International Conference on Electrical Engineering
Article 153, Volume 6, 6th International Conference on Electrical Engineering ICEENG 2008, May 2008, Page 1-20  XML PDF (173.03 K)
Document Type: Original Article
DOI: 10.21608/iceeng.2008.34524
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Authors
A. A. Mousa; I. M. El-Desoky
Department of basic engineering science, Faculty of Engineering, Shebin El-Kom, Menoufia University, Egypt.
Abstract
Abstract:
In this paper, a novel multiobjective genetic algorithm approach for economic
emission load dispatch (EELD) optimization problem is presented. The EELD problem
is formulated as a nonlinear constrained multiobjective optimization problem with both
equality and inequality constraints. A new multiobjective genetic algorithm based
approach employs the concept of co-evolution and repair algorithm for handling
nonlinear constraints. The algorithm maintains a finite-sized archive of non-dominated
solutions which gets iteratively updated in the presence of new solutions based on the
concept of e -dominance. The use of e -dominance also makes the algorithms practical
by allowing a decision maker to control the resolution of the Pareto set approximation.
TOPSIS method is employed to extract the best compromise solution from a finite
set of alternatives based upon simultaneous minimization of distance from an ideal point
(IP) and maximization of distance from a nadir point (NP). Several optimization runs of
the proposed approach are carried out on the standard IEEE 30-bus 6-genrator test
system. Simulation results with the proposed approach have been compared to those
reported in the literature. The comparison demonstrates the superiority of the proposed
approach and confirms its potential to solve the multiobjective EELD problem.
Keywords
Economic emission load dispatch; Evolutionary algorithms; TOPSIS
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