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ISSN Print: 2381-103X ISSN Online: 2381-1048

American Journal of Biomedical Science and Engineering

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Enhancement of Automatic Voltage Regulator and Load Frequency Control Performance Based on Radial Bases Neural Network to Optimize Terminal Voltage and Frequency Deviation

American Journal of Biomedical Science and Engineering
Vol.3 , No. 5, Publication Date: Sep. 8, 2017, Page: 50-53

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Authors

[1]	Jaber Ghaib Talib, Department of Computer Engineering, Al-Mustaqbal University College, Babylon, Iraq.

Abstract

In this paper, radial bases neural network RBNN is proposed to optimize the voltage and frequency response in the power system stations. The conventional automatic voltage regulator AVR causes high overshoot and undershoot with oscillation. In addition, the main problem of the load frequency control LFC is that slow response to reach steady state. Therefore, the proportional- integral- derivative PID controller and the RBNN are used separately on behalf of the integral block of LFC and AVR. The simulation results shows that the proposed method of RBNN- AVR and RBNN- LFC is effectiveness and fast response with more stability as compared with PID- AVR, PID- LFC and conventional system.

Keywords

RBNN, AVR, LFC, PID Controller, Turbine

Reference

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