Description
The rapid expansion of installed wind turbines highlights the need for good-quality weather forecasts for power prediction. Since wind turbines themselves modify the wind and turbulence in front, at the sides and especially down-wind of the farm, they need to be considered in numerical weather prediction (NWP) for accurate weather forecasts. In addition, the modified wind and turbulence fields also affect other meteorological variables such as temperature, humidity and clouds under certain meteorological conditions. Thus, including the effects of wind turbines on the atmosphere in NWP models can improve the weather forecast in general.To evaluate the impact of wind turbines on weather forecasts, we perform forecasts with the operational NWP model HARMONIE-AROME. The HARMONIE-AROME model is equipped with two wind farm parameterizations (WFP), namely the WFP by Fitch et al. (2012) implemented by van Stratum et al. (2022) and the Explicit Wake Parameterization (EWP) by Volker et al. (2015) implemented by Fischereit et al. (2022). Two one-month-long simulations are performed for each WFP and compared to a control simulation without wind farms for central and northern Europe.
To accurately represent existing wind turbines in the simulations, we developed an European wind turbine database by combining seven different, and sometimes open-access, data sets with a machine learning gap-filling approach to find missing information. The database contains the wind turbine locations and characteristics such as hub height, rotor diameter and thrust curves.
The simulations show that wind speed, temperature and humidity are affected locally by the presence of wind turbines in Europe (Figure 1). The magnitude and sometimes the sign of the effects depend on the chosen WFP. In the presentation, the wind farm effects and differences between the WFP will be highlighted and evaluated against measurements.
Fischereit, J., Vedel, H., Theeuwes, N. E., Larsén, X. G., Giebel, G., & Kaas, E. (2023). Modelling wind farm effects in HARMONIE-AROME - part 1: Implementation and evaluation. To Be Submitted.
Fitch, A. C., Olson, J. B., Lundquist, J. K., Dudhia, J., Gupta, A. K., Michalakes, J., & Barstad, I. (2012). Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model. Monthly Weather Review, 140(9), 3017–3038. https://doi.org/10.1175/MWR-D-11-00352.1
van Stratum, B., Theeuwes, N., Barkmeijer, J., van Ulft, B., & Wijnant, I. (2022). A one-year-long evaluation of a wind-farm parameterization in HARMONIE-AROME. Journal of Advances in Modeling Earth Systems, 14, e2021MS002947. https://doi.org/10.1029/2021MS002947
Volker, P. J. H., Badger, J., Hahmann, A. N., & Ott, S. (2015). The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF. Geoscientific Model Development, 8(11), 3715–3731. https://doi.org/10.5194/gmd-8-3715-2015
| Period | 25 May 2023 |
|---|---|
| Event title | Wind Energy Science Conference |
| Event type | Conference |
| Conference number | 4 |
| Location | Glasgow, United KingdomShow on map |