Sub-Synchronous Resonance Damping Using Static Var Compensator SVC Enhanced with Adaptive Neuro-Fuzzy Inference Systems ANFIS Controller

Nowadays renewable energy sources, particularly wind power, are considered as important generation in electric power systems because of their no exhausted nature and benign environmental effects. With increasing usage wind power in power systems, impact of wind generator on sub-synchronous resonance (SSR) is going to more important. The main purpose of this paper is to confirm the ability of the Static Var Compensator (SVC) as a member of FACTS family in mitigating the SSR. Imperialist competitive algorithm (ICA)-based Conventional Damping Controller (CDC) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are designed as two novel controllers In order to provide the effective damping of SSR. Simulation results are performed by MATLAB/Simulink on the IEEE Second Benchmark Model (SBM) amassed with the SVC. The system stability is studied through time domain simulations and Fast Fourier Transform (FFT) analysis which is defined based on the dynamics of the power system. To compare the performance of two controllers, two various cases of study are considered.

کلیدواژه ها:

Sub-Synchronous Resonance ، Adaptive Neuro-Fuzzy Inference Systems ، Conventional Damping Controller ، Imperialist competitive algorithm