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Dr. mahomud Nasr said mohamed Elsisi :: Publications:

Title:
Model Predictive Control of Nonlinear Interconnected Hydro-Thermal System Load Frequency Control Based on Bat Inspired Algorithm
Authors: M Elsisi; M Soliman; M A S Aboelela; W Mansour
Year: 2015
Keywords: Bat Inspired Algorithm (BIA), Load Frequency Control (LFC), Model Predictive Control (MPC)
Journal: International Electrical Engineering Journal (IEEJ)
Volume: 6
Issue: 7
Pages: 1953-1961
Publisher: International Electrical Engineering Journal (IEEJ)
Local/International: International
Paper Link:
Full paper mahomud Nasr said mohamed Elsesy_Model Predictive Control of Nonlinear Interconnected Hydro-Thermal System Load Frequency Control Based on Bat Inspired Algorithm.pdf
Supplementary materials Not Available
Abstract:

Bat Inspired Algorithm (BIA) 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 BIA to enhance the damping of oscillations in a two-area power system. A two-area hydro-thermal system is considered to be equipped with Model Predictive Control (MPC). The proposed power system model considers generation rate constraint (GRC), dead band, and time delay imposed to the power system by governor-turbine, thermodynamic process, and communication channels. BIA 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 based on integral square error technique , and PI controller tuned by Genetic Algorithm (GA) in order to demonstrate the superior efficiency of the proposed MPC tuned by BIA. Simulation results emphasis on the better performance of the proposed BIA-based MPC compared to PI controller based on GA and conventional one over wide range of operating conditions, and system parameters variations.

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