Abstract
As the wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is how to efficiently operate the wind turbines in a wide range of wind speeds. Compared to fixed speed turbines, variable speed wind turbines yield higher energy efficiency, lower component stress and fewer grid connection power peaks. Generally, measurement of wind speed is required for the control of variable speed wind turbine system. However, wind speed measured by anemometers is not accurate owing to various reasons. In this work, an observer-based torque estimator and artificial neural network are utilized for estimation of effective wind speed. Finally, the performance of the proposed Maximum Power Point Tracking (MPPT) algorithm based on estimated wind speed is verified with simulation studies.
