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

Citation:
Ragab A. El-Sehiemy, Mostafa Abdelkhalik El-hosseini, and A. E. Hassanien, " Multiobjective Real-Coded Genetic Algorithm for Economic/Environmental Dispatch Problem, ", Studies in Informatics and Control, , vol. 22, issue 2, pp. 113-122, 2013.

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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.

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