Offshore windfarm modelling over the North Sea with COSMO-CLM: model evaluation and application at kilometer-scale resolution

The rapid growth of the offshore wind energy sector emphasizes the need for realistic projections of the lifetime energy yield of existing and planned offshore windfarms. Analyses of CMIP5 data show that, even though near-future wind speed changes over Europe and the North Sea are uncertain across models, these changes should be taken into account by wind industries due to the potentially large impact on the energy. Thanks to advances in model design and the increase in computing resources over the past decades, regional climate models (RCMs) can be used for multi-decadal simulations and that at a spatial resolution of a couple of kilometers or less. These high-resolution simulations not only allow for an improved representation of weather systems, but also allow to represent the interactions between windfarms and the atmosphere through a wind farm parametrization. In this way, RCMs can be employed for a detailed wind resource assessment for the coming decades that takes into account the wakes and energy losses induced by upwind arrays and clusters.

In our wind resource assessment, we use the regional climate model COSMO-CLM, extended with the Fitch wind farm parametrization. An evaluation of a 10-year, ERA5-driven simulation at 2.8km resolution against in-situ anemometers, lidar measurements and satellite-borne ASCAT measurements that has been performed for the North Sea will be discussed. For the year 2019, the spatially-variable bias in the mean wind speed was found to be generally within +- 0.4 m/s and the overlap in the wind speed distributions generally larger than 92%. Next, array- and cluster-scale wakes, modelled at horizontal resolutions of 2.8km and 1km were analysed and compared for a present and near-future windfarm layout over the southern North Sea, providing valuable information on how regional changes to the wind farm layout will impact the farm-specific energy yields due to additional upwind wake generation under different atmospheric conditions. This research frames within the FREEWIND project of KU Leuven (freewind-project.eu), which aims to contribute to the scientific research of offshore wind energy and plans to provide wind farm planning and forecasting tools on multiple time scales over the coming years.