Transient Performance Improvement of Power Systems Using Fuzzy Logic Controlled Capacitive-Bridge Type Fault Current Limiter

Abstract

This paper proposes the novel application of a genetic algorithm optimized fuzzy logic controller as a nonlinear controller for capacitive bridge type fault current limiter (CBFCL) to improve the stability performance of the power systems. The proposed controller provides fast convergence for the system and uses data from the system as a feedback in the controller loops. The performance of the proposed genetic algorithm optimized fuzzy logic controlled CBFCL is compared with that of a static nonlinear controller based CBFCL and a static nonlinear controller-based bridge type fault current limiter (BFCL). The detail controller design and stability analysis are carried out on the IEEE 39 bus power system in MATLAB/SIMULINK. To capture a realistic system's response, a wind farm is connected to bus one in the IEEE 39 bus system. From the simulation results and several quantifying parameters, it is shown that the proposed genetic algorithm optimized fuzzy logic controlled CBFCL can effectively improve the stability and the performance of the power system as well as the grid connected wind farm. Further, the proposed controller performs better than the static nonlinear controller based CBFCL and the static nonlinear controller based BFCL.