Control Strategy of Maximum Wind Energy Capture of Direct-Drive Wind Turbine Generator Based on Neural-Network

The wind power varies mainly depending on the wind speed. Many methods have been proposed to track the maximum power point (MPPT) of the wind, such as the fuzzy logic (FL), artificial neural network (ANN) and Neuro-Fuzzy. In this paper, a variable speed wind generator MPPT based on artificial neural network (ANN) is presented. It is designed as a combination of the generator speed forecasting model and neural network. The ANN is used to predict the optimal speed rotation using the variation of the wind speed and the generator speed as the inputs. The wind energy control system employs a permanent magnet synchronous generator connected to a DC bus using a power converter is presented. The performance of the control system with the proposed ANN controller is tested for wind speed variation. System simulation results have confirmed the functionality and performance of this method.