Rolling Prediction Method of Input Wind Power of Wind Turbine Generators in Wind Farm

Abstract

The power system's inertia and capability of frequency regulation decrease as the proportion of renewable energy generation in the system rises. The current system includes a significant amount of wind power generation, and the contribution of wind power to frequency control has a significant impact on the frequency stability of the power grid. The ability of wind turbine generators to regulate frequency is significantly impacted by variations in wind speed. To accurately evaluate the frequency response capability of wind power generation, it is necessary to predict the change in wind speed or wind power after the wind turbine generator starts the frequency response. Because the wind speed measured by the wind turbine generator is not accurate, this paper uses accurate power measurement data to represent the change in wind power. In this paper, a rolling prediction method for the power of downwind turbines in a wind farm is proposed using spatial correlation. The future power curves of the downwind turbines are obtained by weighting and summing the power curves of several upwind turbines while taking into account time lags. The validity of the method is verified using measured data from an actual wind farm. The prediction results of the power of wind turbine generators can provide a basis for rolling evaluation of the wind farm's frequency response capability at different moments.