Multiobjective Real-Coded Genetic Algorithm for Economic/Environmental Dispatch Problem

Ragab A. El-SEHIEMY¹, Mostafa Abdelkhalik El-HOSSEINI²,
Aboul Ella HASSANIEN³
¹Electrical Engineering Department, Faculty of Engineering-Kafrelsheikh University
elsehiemy@eng.kfs.edu.eg
²Computers and Systems Engineering Department, Faculty of Engineering – Mansoura
melhosseini@eng.mans.edu.eg
³Cairo University, Faculty of Computers & Information
aboitcairo@fci-cu.edu.eg

Abstract: This paper outlines the optimization problem of nonlinear constrained multi-objective economic/environmental dispatch (EED) problems of thermal generators in power systems and presents novel improved real-coded genetic optimization (MO-RCGA) algorithm for solving EED problems. The considered problem minimizes environmental emission and non-smooth fuel cost simultaneously while fulfilling the system operating constraints. The proposed MO-RCGA technique evolves a multi-objective version of GA by proposing redefinition of global best and local best individuals in multi-objective optimization domain. The performance of the proposed MO-RCGA enhanced with biased Initialization, dynamic parameter setting, and elitism is carried out. The validity and effectiveness of the proposed MO-RCGA is verified by means of several optimization runs accomplished at different population sizes on standard IEEE 30-bus test system. Simulation results demonstrated the capabilities of the proposed MO-RCGA algorithm to obtain feasible set of effective well-distributed solutions.

Keywords: Multiobjective real-coded genetic algorithm, economic environmental dispatch (EED), security.

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CITE THIS PAPER AS:
Ragab A. EL-SEHIEMY, Mostafa Abdelkhalik EL-HOSSEINI, Aboul Ella HASSANIEN, Multiobjective Real-Coded Genetic Algorithm for Economic/Environmental Dispatch Problem, Studies in Informatics and Control, ISSN 1220-1766, vol. 22 (2), pp. 113-122, 2013. https://doi.org/10.24846/v22i2y201301