Intelligent Controller Based Multiarea Automatic Generation Control Scheme for Restructured Power System

Abstract

The presented work provides a methodical understanding of the power system newlineAGC, and presents numerous new schemes using intelligent algorithms for newlinereducing the deviation in frequency and tie-line power to counterpart total newlinegeneration and load demand.A study is performed on Automatic Generation Control (AGC) for a single newlinearea, where, a Genetic Algorithm (GA)-based design and optimization of Fuzzy newlineLogic Controller (FLC) is carried out by automatically tuning (off-line) the newlineparameters of the membership functions. Tuning is based on maximization of a newlinecomprehensive fitness function constructed as inverse of a weighted average of newlinethree performance indices, i.e., Integral Square Deviation (ISD), or the Integral of newlineSquare of the frequency deviation, Peak overshoot (Mp), and Settling time (ts). The newlineGA-optimized FLC (in short, GAFLC) shows better performance as compared to newlinea conventional Proportional Integral (PI) and a hand-designed Fuzzy Logic newlinecontroller not only for a standard system (displaying frequency deviations) but newlinealso under parametric and load disturbances. Further the work is carried over by newlinemodeling of a two-area non-reheat thermal system.The design of the FLC is carried out by automatically tuning the parameters of membership functions of the newlineFLC using GA by minimizing the integral time absolute error (ITAE) based newlinefitness function. The effectiveness of GAFLC is revealed over GA tuned PI newlinecontroller (GAPI) for the same model.Additionally in this work the main structures, configurations, and newlinecharacteristics of AGC systems in a deregulated environment is presented. A newlineRobust Fuzzy Logic controller is presented for the automatic generation control of newline2-area interconnected system in market based Deregulated system with reheat newlineturbine. newline