Ragab A. El-SEHIEMY1, Mostafa Abdelkhalik El-HOSSEINI2,
Aboul Ella HASSANIEN3
1 Electrical Engineering Department, Faculty of Engineering-Kafrelsheikh University
2 Computers and Systems Engineering Department, Faculty of Engineering – Mansoura
3 Cairo University, Faculty of Computers & Information
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.
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.