Artificial intelligence-based approach for the control of PMSG based wind energy system
Abstract
An intelligent approach for wind energy systems using artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) integrated with a permanent magnet synchronous generator (PMSG) system has been proposed. The proposed design is capable of estimating maximum power from the turbine at any given wind speed and generate an optimal reference shaft speed to drive the PMSG rotor. This approach employs the speed control method for the PMSG system, where the proportional-integral (PI) controller was feedback by the error signal of the reference shaft speed of ANN/ANFIS based wind turbine model and PMSG output rotor speed. Both the model has been tested with varying wind speed and found to be excellent with very small error. The model was also validated with real-time wind speed data for a location in the Kingdom of Saudi Arabia.