Improving Wind Power Forecasting with Meteomatics High-Resolution Model Resolving Wind Turbine Wake Effects

Wind energy production depends heavily on weather conditions, and the growing deployment of wind turbines in complex terrain and offshore locations presents considerable forecasting challenges. Current numerical weather prediction (NWP) models often struggle to provide accurate forecasts in these environments due to limited spatial and temporal resolutions, infrequent model updates, and the lack of representation of wind turbine induced wake effects on atmospheric flows. These limitations lead to inaccuracies in power production forecasts, impacting the efficiency and reliability of renewable energy systems.

To address these limitations, Meteomatics has developed an operational high-resolution NWP model featuring a horizontal grid spacing of 1 km and an hourly update frequency. This model integrates data from Meteomatics' proprietary network of Meteodrones, along with traditional data sources such as ground-based weather stations, radar, satellite observations, and radiosondes. Meteodrones are small unmanned aircraft systems capable of collecting vertical atmospheric profiles up to altitudes of 6000 m.

Here, the impact of recent enhancements implemented in to Meteomatics' high-resolution NWP model on wind power forecasting is evaluated. Key updates include an extension of the forecast lead time to 72 hours and an increase in temporal resolution to 15-minute intervals, aligning with the interval used in energy trading. Additionally, the model's domain, covering the pan-European region (EURO1k), has been expanded with the introduction of a new domain covering the North American continent (US1k). Importantly, the model now incorporates a parameterization of wind turbine effects, enabling accurate representation of wind wake phenomena. The findings highlight the critical role of state-of-the-art high-resolution numerical weather forecasting in improving the cost efficiency of wind energy production. These advancements facilitate greater integration of wind energy into the broader energy mix, thereby contributing to a reduction in CO2​ emissions and supporting the transition to sustainable energy systems.