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