Wind Speed Prediction Based on Error Compensation.

Wind speed prediction is very important in the field of wind power generation technology. It is helpful for increasing the quantity and quality of generated wind power from wind farms. By using univariate wind speed time series, this paper proposes a hybrid wind speed prediction model based on Autoregressive Moving Average-Support Vector Regression (ARMA-SVR) and error compensation.

L adaptive pitch angle controller of wind energy conversion systems.

In conditions of above rated wind speed, the power output of a wind turbine should be maintained at rated power to prevent overheating of generators and power electronics systems. Furthermore, extreme wind conditions, such as wind gusts, can even lead to shut-downs. In this paper, a novel L adaptive controller is designed for blade pitch control of wind energy conversion systems (WECS) to achieve stable output power and generator speed, in the presence of turbulent wind conditions.