Estimation of the Energy Production in a Wind Farm Using Regression Methods and Wind Speed Forecast

Wind energy is an excellent source of alternative energy to complement the Brazilian energy matrix. However, one of the significant challenges lies in managing this resource, due to its intermittent behavior. This study addresses the estimation of the electric power production of the wind park, so its management could be more efficient. A real data from one-year records of wind speed and power from a wind park installed in a wind farm in Ceará State, Brazil, is used. At first, we provide a study of Logistic versus Least Squares regression to model the wind turbine power curve. Then, a novel variant of the Least Square Support Regression is used to forecast wind speed on the site. The Logistic regression demonstrated to be more suitable for the task of regression, and the wind speed forecasting with three steps ahead provided lower error rates. Our approach represents a system based on data from both wind turbine power and speed to serve as a tool for helping energy selling issues and scheduling turbine maintenance on periods of time with low energy production in the wind park.