Model Predictive Control of Two-Area Load Frequency Control Based Imperialist Competitive Algorithm
Author(s) -
Mahmoud Elsisi,
Magdy A.S. Aboelela,
Mohamed A. Soliman,
W. Mansour
Publication year - 2015
Publication title -
telkomnika indonesian journal of electrical engineering
Language(s) - English
Resource type - Journals
eISSN - 2460-7673
pISSN - 2302-4046
DOI - 10.11591/tijee.v16i1.1590
Subject(s) - model predictive control , control theory (sociology) , imperialist competitive algorithm , controller (irrigation) , computer science , range (aeronautics) , frequency domain , algorithm , optimization problem , control (management) , engineering , artificial intelligence , multi swarm optimization , aerospace engineering , biology , agronomy , computer vision
Imperialist Competitive Algorithm (ICA) has recently been explored to develop a novel algorithm for distributed optimization and control. This paper proposes a Model Predictive Control (MPC) of Load Frequency Control (LFC) based ICA to enhance the damping of oscillations in a two-area power system. A two-area non-reheat thermal system is considered to be equipped with Model Predictive Control (MPC). ICA is utilized to search for optimal controller parameters by minimizing a time-domain based objective function. The performance of the proposed controller has been evaluated with the performance of the conventional PI controller, and PI controller tuned by ICA in order to demonstrate the superior efficiency of the proposed MPC tuned by ICA. Simulation results emphasis on the better performance of the optimized MPC based on ICA in compare to optimized PI controller based on ICA and conventional one over wide range of operating conditions, and system parameters variations.
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