AUTOMATIC GENERATION CONTROL IN A DEREGULATED POWER SYSTEM USING Al TECHNIQUES

Abstract

This thesis deals with optimum selection of controller parameters in the design of an appropriate governor for automatic generation control of an inter-connected power system in deregulated environment. The optimization of the parameters is done using the conventional ISE technique and also with artificial intelligence technique like genetic algorithm. The effect of frequency deviation and tie line power flow deviation on optimal gain settings has been studied. In deregulated power system, because of inherent characteristic of changing load i.e with change in Disco Participation Matrix (DPM) there is difficulty in optimizing the controller gains. This is because a fixed controller may not be suitable in all operating conditions. To improve the performance of the Automatic Generation Control and to overcome the limitations of Conventional controller has necessitated the use of intelligent systems. Artificial Intelligence techniques like Fuzzy Logic and Genetic algorithms can be applied. In this thesis a new controller i.e a hybrid controller based on fuzzy logic is applied. The optimization of the controller parameters is done using the genetic algorithm technique. The dynamic response is compared with the dynamic response obtained by the conventional integral controller. Simulation study has been done for a two area non reheat thermal-thermal system in deregulated environment. Dynamic performances of two area system have been studied for different Disco Participation Matrix (DPM). The system study has been done using MATLAB 7.01 and the toolboxes available with it.