Fuzzy adaptive model reference approach-based power system static VAR stabilizer

Abstract

Abstract This paper presents a power system Static VAR stabilizer based on the fuzzy adaptive model reference approach. The Static VAR Compensator SVC (thyristor controlled reactor-fixed capacitor (TCRFC) type) is used for voltage regulation and to improve power system stability. The proposed control system consists of a feedback fuzzy controller using the speed state deviation and its derivative as input signals. Moreover, a model reference with a fuzzy adaptive mechanism is built to make the power system speed deviation response follow a certain track. The reference model transfer function of second order is chosen which has desired performance specifications. The input signal to reference model is the speed state deviation response. While the error between model reference output response and the power system speed deviation response is an input signal to fuzzy adaptive mechanism, the other fuzzy adaptive mechanism signal is the derivative of the above mentioned error signal. The control signal to the SVC stabilizer comprises the sum of the feedback fuzzy controller output and the fuzzy adaptive mechanism output signals. The proposed control system is proved by digital simulation power system speed and torque angle states response due to various disturbances. Furthermore, the effect of the additional signal comes from the fuzzy adaptive mechanism for enhancing the power system stability. A comparison between power system response using the proposed SVC stabilizer and without adding the control signal of fuzzy adaptive mechanism is presented. The results show the effectiveness and power of the presented SVC.