Stability Analysis of Synchronous Generator among Four Intelligent Fuzzy Logic Based Excitation Controllers

Electrical power systems are widely distributed systems, consisting of a large number of interconnected synchronous generators through transmission lines, mounting real and reactive power. Moreover, with deregulation and growth of the power industry, power systems elements are forced to operate very near to their maximum capacity and hence, the system becomes vulnerable. Therefore, controlled operation of power systems is very critical and of utmost importance in order to achieve stable power system. Naturally, this paves ways for implementing fast, efficient and reliable control algorithms. Robustness and efficiency of power system controllers can be improved by using complimentary models of intelligent systems. Difficulties encountered in designing controls for nonlinear, dynamic and uncertain systems can be easily tackled by using intrinsic observability property of various intelligent systems. Intelligent controllers have been successfully applied to enhance operation and control of power system. This paper presents an implementation of four different Fuzzy Logic based intelligent controllers through the excitation system of the synchronous generator:
Conventional Fuzzy Logic Controller (CFLC), Adaptive Fuzzy Logic Controller (AFLC), Adaptive Neuro-Fuzzy Logic Controller (ANFLC) and Takagi-Sugeno Fuzzy Logic Controller (TSFLC). A comparison between the four proposed intelligent
controllers are presented.