On the impact of the assimilation of nacelle winds and yaw angles with WRF-FDDA and WRF-DART for short-term wind energy predictions

摘要

Several kinds of observations are used today in operational NWP models with the aim of better forecasts by improving the analyses used by models. With the ongoing numerous offshore deployments of wind farms, especially in Europe (e.g., Denmark, UK, and Germany), but also in the US, a new set of measurements becomes available: wind speeds measured on the nacelle of a wind turbine (located at about 70 m above the sea surface) and the turbine yaws (a proxy for wind direction), which are used by the turbine control system for optimal operation of the wind turbine. In this study we explore the potential of nacelle wind speeds and turbine yaws as a new set of observations to be assimilated into the Weather Research and Forecasting (WRF) Model. We present two assimilation strategies and their impact on 0-6 h forecasts for the large Danish offshore wind farm Horns Rev I. These strategies include nudging (Four Dimensional Data Assimilation, FDDA) and the Ensemble Kalman Filter (Data Assimilation Research Testbed, DART). Since offshore wind farms are generally near the coast, nacelle wind speeds and yaws constitute also a promising data set to improve wind forecasts inland.