ANFIS-Based Control for Low-Voltage Ride-Through Enhancement of PMSG Tidal Turbine

This paper reports an adaptive neural fuzzy inference system (ANFIS) based controller for a grid-connected tidal turbine (GCTT) system based on permanent magnet synchronous generator (PMSG). An energy storage system (ESS) provides the balance of power at the DC link to improve system stability under low-voltage ride-through (LVRT) conditions and tidal power fluctuations. The grid code suggests the required reactive power demanded by the grid during a fault. An ANFIS-based controller coordinates with the TT rotor speed and state-of-charge (SOC) to fulfill grid code requirements. During the occurrence of a fault, the operating conditions of the GCTT and the SOC of ESS may differ. So, it becomes necessary to establish coordination between both the TT rotor speed and the SOC of ESS. It results in different operating conditions of the GCTT and the ESS. The proposed control method generates the reference power for the machine-side converter of GCTT based on the current rotor speed and SOC of the ESS. Extensive numerical simulations have been performed on the MATLAB® Simulink platform to prove effectiveness of the proposed control method.