Within WINS50, a wind atlas for the North Sea area will be produced that includes the effects of both current and future wind farms. Various offshore wind energy capacity scenarios will be explored. The model data will be made publicly available and thoroughly analysed to understand the feedbacks between the atmosphere and a 2050 offshore wind energy capacity scenario.

Currently, many research questions are high on the agenda of the wind energy sector. With the data that will be made available in the WINS50 project, many of these can be studied in detail.

A few examples of currently relevant research topics are briefly discussed here. In addition, backgound information on the two weather models that are used in WINS50 (HARMONIE and GRASP) is included.

Farm-to-farm interactions

Downstream of wind farms, the wind speed may be reduced for tens of kilometers (1). These wind farm wakes are especially persistent in stably stratified conditions, i.e. when warmer air is residing over a colder sea surface. When more and more large wind farms will become operational in a limited area like the Southern North Sea, the negative impact of wakes from neighboring wind farm on power prediction will increase.

The model simulations that are done within the WINS50 projects will enable a more detailed study of farm-to-farm interactions. Not only the impact of one wind farm on the power prediction of another can be studied, but also the physical properties of wake formation and dilution can be investigated.

Within WINS50, the quality of the modeled wind farm wakes will be evaluated using all kinds of available in-situ, lidar, aircraft and satellite observations.

Wind field at hub-height as modeled by Harmonie, showing extensive wakes in the German Bight.
Image: KNMI.

Global blockage

Not only downstream of wind farms the wind speed is reduced. Observational and modeling studies have shown evidence that also the first-row turbines of a wind farm (i.e. those that are not in the wakes of other turbines) experience a reduced wind speed (2). This phenomenon, called global blockage in the wind industry, occurs whenever an obstacle is placed in a flow. When the flow approaches the obstacle, it needs to deflect upwards and sidewards as it cannot pass unobstructed. And although a wind farm is not a rigid obstacle, this effect may lead to reduced wind speeds and significant power losses. On the other hand, in analogy with flow around buildings, the sidewards delection of the flow may lead to increased wind speeds and power production in other parts of the wind farm.

The high-resolution, turbine-resolving wind atlas that will be produced by the GRASP atmospheric model will allow for detailed analysis of this blockage effect. The full-scale, real-weather large-eddy simulations will allow for a unique climatological assessment of this phenomenon for a variety of present and future wind farms.

Fractional change in hubheight wind speed as a result of the presence of the wind farms. Composite image of 5 months of GRASP large-eddy simulations of the Borssele wind farm zone for northeasterly winds. A clear blockage effect is visible upstream of the wind farms.
Image: Whiffle.

Wake losses

The aerodynamics of the next generation of (clusters of) offshore wind farms that can exceed 5GW size, is still largely unexplored territory. The LES model simulations that will be performed within the WINS50 project will provide unique quantitative insights in efficiency of future wind farm (clusters) by studying the combined effects of global blockage, wake losses, and wind-farm-induced vertical mixing.

Sensitivity studies will be performed that will study the impact of, for instance, the geometrical arrangement of the turbines, the power density MW/km^2, or the types of turbines that will be applied (e.g. is it more efficient to have N number of 16 MW turbines or 2N number of 8 MW turbines in an offshore wind farm of fixed size?). Also the impact of different atmospheric conditions like stability will be assessed.

Reduction of the hub-height wind speed (fraction) within the Gemini wind farm as modeled by GRASP for easterly winds.
Image: Whiffle.

Vertical exchange of momentum

A second aspect of large-scale wind energy that has received a lot of attention is the limit to the vertical entrainment of mean kinetic energy. In very large wind farms, the vertical flux of kinetic energy will eventually be in equilibrium with the extraction by the turbines. How fast kinetic energy is transported from higher altitudes thus determines the limits of the wind energy power density (MW/km2) that can be achieved. Estimates of this vertical kinetic energy flux range from 1 MW/km2 (3) to 8 MW/km2 over certain areas of the Northern Atlantic Ocean (4). The methods and data delivered in the WINS50 project will markedly improve the previous studies and, furthermore, we will specifically focus on the North Sea area.

WINS50 Weather models


HARMONIE-AROME (HIRLAM ALADIN Research On Mesoscale Operational NWP in Europe) is the operational Numerical Weather Prediction model of KNMI since 2012. It is a limited area model, that was developed by a consortium involving many European countries. HARMONIE is intended to run on a high grid resolution of typically 2.5 km, but allows for grid resolutions well under the km scale. HARMONIE is a so-called non-hydrostatic model, meaning that instead of employing the hydrostatic approximation, which often breaks down in severe-weather events, the vertical momentum equation is solved explicitly. More details on HARMONIE/AROME are given in 5.

HARMONIE-AROME has been used to produced high-resolution wind atlases before. The KNMI North Sea Wind (KNW) atlas contains hourly undisturbed wind data (without wind turbine wake effects) based on more than 40 years (1979-2019) of re-analysed data. However, due to the applied method to create the KNW-atlas, the hourly correlation with measurements (e.g. daily cycle) is rather poor. A substantial improvement was achieved in the Dutch Offshore Wind Atlas (DOWA), both over sea and over land (6, 7), by introducing a new turbulence scheme and assimilating scatterometer (10m wind) and Mode-S EHS aircraft observations (wind). The DOWA is a 10 year climatology (2008-2017) with a better hourly correlation than the KNW-atlas. It has information up to 600 m height and covers a larger area compared to the KNW atlas. The DOWA-data and all information on the DOWA-project can be found on the Dutch Offhore Wind Atlas (DOWA) website.

In the WINS50 project the DOWA will be extended by three years (2019, 2020, 2021). In order to create a homogeneous dataset, changes in method should be avoided, but it turned out that the HARMONIE-AROME Cycle 40 that was used for DOWA could no longer be used for WINS50. Instead, for WINS50 an updated version of HARMONIE was used: HARMONIE-AROME Cycle 43. The consequences for the continuity between the the DOWA and WINS50 dataset is discussed in the memo Comparison DOWA and WINS50-data.

Within WINS50, also a model simulation that includes wind turbine wakes will be performed (current and future capactity). For modeling wind farm wakes, HARMONIE uses the Fitch et. al, 2012 (8) wind farm parameterization. In this parameterization wind turbines act as a sink for momentum leading to a reduction of the wind speed. The released energy is distributed between increased levels of turbulent kinetic energy and power production. The Fitch 2012 parameterization is commonly used in numerical weather prediction models and has the advantage of very little tuning parameters.


GRASP (GPU-Resident Atmospheric Simulation Platform) is a large-eddy simulation (LES) model operated by Whiffle. GRASP originates from the Dutch Atmosperic Large-Eddy Simulation (DALES) model, which is extensively described in 9. DALES has been and is still widely used in the boundary-layer meteorology community. To overcome the barrier of the large computational costs that have long prohibited the use of LES in operational weather forecasting, the DALES model was translated to a code that runs most of its computational routines on GPUs (10). GRASP is used both as an operation weather model (to provide high-resultion wind and power forecasts) and for making wind resource assessments.

GRASP uses an actuator disk parametrisation as described by 11. This parametrisation only needs information about the power curve, thrust curve, rotor diameter and hub height. This information is publicly available or can be estimated with good accuracy. The parametrisation calculates the drag forces (using the thrust curve) and rotational forces (using the power curve) based on the local wind speed, taking the actual induction into account. Individual yaw control based on the local wind direction is applied to the turbines.

Just as HARMONIE, also GRASP was used in the DOWA project. A basic validation of the model of multi-year simulations around three offshore wind farms showed good agreement between model results and observations (12)

  1. A Platis, SK Siedersleben, J Bange, A Lampert, K Bärfuss, R Hankers, B Cañadillas, R Foreman, J Schulz-Stellenfleth, B Djath, T. Neumann, S Emeis (2018): First in situ evidence of wakes in the far field behind offshore wind farms, Scientific Reports, 8, Article number: 2163.
  2. J Bleeg, M Purcell, R Ruisi, E Traiger (2018): Wind farm blockage and the consequences of neglecting its impact on energy production, Energies, 11, https:doi:10.3390/en11061609.
  3. LM Miller, NA Brunsell, DB Mechem, F Gans, AJ Monaghan, R Vautard, DW Keith, and A Kleidon (2018): Two methods for estimating limits to large-scale wind power generation, PNAS, 112, 1609.
  4. A Possner, K Caldeira (2017): Geophysical potential for wind energy over the open oceans, PNAS, 114, 11338–11343.
  5. L Bengtsson, U Andrae, T Aspelien, Y Batrak, J Calvo , W de Rooy, E Gleeson, B Hansen-Sass, M Homleid, M Hortal, KI Ivarsson, G Lenderink, S Niemelä, K Pagh Nielsen, J Onvlee, L Rontu, P Samuelsson, D Santos Muñoz, A Subias, S Tijm, V Toll, X Yang, M Ødegaard Køltzow (2017): The HARMONIE-AROME Model Configuration in the ALADIN–HIRLAM NWP System, Monthly Weather Review, 145, 1919–1935.
  6. JB Duncan, IL Wijnant, S Knoop (2019): DOWA validation against offshore mast and LiDAR measurements, TNO report 2019 R10062.
  7. S Knoop, P Ramakrishnan, I Wijnant (2020): Dutch Offshore Wind Atlas Validation against Cabauw Meteomast Wind Measurements, Energies, 13, 6558.
  8. AC Fitch, JB Olson, JK Lundquist, J Dudhia, AK Gupta, J Michalakes, I Barstad (2012): Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model, Monthly Weather Review, 140, 3017–3038.
  9. T Heus, CC van Heerwaarden, HJJ Jonker, AP Siebesma, S Axelsen, K van den Dries, O Geoffroy, AF Moene, D Pino, SR de Roode, J Vilà-Guerau de Arellano (2010): Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications, Geosci. Model Dev., 3, 415–444.
  10. J Schalkwijk, EJ Griffith, FH Post, HJJ Jonker (2012): High-Performance Simulations of Turbulent Clouds on a Desktop PC: Exploiting the GPU, Bull. Am. Met. Soc., 93, 307–314.
  11. J Meyers, C Meneveau (2012): Large Eddy Simulations of large wind-turbine arrays in the atmospheric boundary layer, in 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition.
  12. E Wiegant, R Verzijlbergh (2019): GRASP model description & validation report, Whiffle report 2019.