Impact of wake effect on wind power prediction

Abstract

Wind power prediction is an effective way to ensure the rational use of wind energy and improve the economy of power system. A physical approach of wind power prediction based on CFD pre-calculated flow fields is used in this paper, which improves the accuracy and timeliness of the prediction. The Jensen and Larsen wake model are adopted respectively to simulate the wake effect of single wind turbine. A one-year wind power prediction has been carried on in a real wind farm. Via the comparison of the predicted and measured wind power, the results show that the wind power prediction method based on CFD pre-calculated flow fields has high forecast accuracy, and taking the wake effect into account can improve the prediction accuracy further. As to the selected wind farm, the prediction results of the two models have not much difference. The RMSE of the whole wind farm's predicted wind power is less than 16%, and a single wind turbine's RMSE is about 25%. The Jensen wake model has a higher prediction precision than the Larsen wake model. The power reduction of downwind turbine caused by wake effect can be up to 35%, the wake effect is a factor that must be considered in the accurate prediction of wind power.