Patrick Volker

Simulation of wake effects between two wind farms

SCADA data, recorded on the downstream wind farm, has been used to identify flow cases with visible clustering effects. The inflow condition is derived from a partly undisturbed wind turbine, due to lack of mast measurements. The SCADA data analysis concludes that centre of the deficit for the downstream wind farm with disturbed inflow has a distinct visible maximum deficit zone located only 5-10D downstream from the entrance. This zone, representing 20-30% speed reduction, increases and moves downstream for increasing cluster effect and is not visible outside a flow sector of 20-30°. The eight flow models represented in this benchmark include both RANS models, mesoscale models and engineering models. The flow cases, identified according to the wind speed level and inflow sector, have been simulated and validated with the SCADA results. The model validation concludes that all models more or less are able to predict the location and size of the deficit zone inside the downwind wind farm.

Comparing satellite SAR and wind farm wake models

The aim of the paper is to present offshore wind farm wake observed from satellite Synthetic Aperture Radar (SAR) wind fields from RADARSAT-1/-2 and Envisat and to compare these wakes qualitatively to wind farm wake model results. From some satellite SAR wind maps very long wakes are observed. These extend several tens of kilometres downwind e.g. 70 km. Other SAR wind maps show near-field fine scale details of wake behind rows of turbines. The satellite SAR wind farm wake cases are modelled by different wind farm wake models including the PARK microscale model, the Weather Research and Forecasting (WRF) model in high resolution and WRF with coupled microscale parametrization.

Challenges in simulating coastal effects on an offshore wind farm

The effect of a coastline on an offshore wind farm is investigated with a Reynolds-averaged Navier-Stokes (RANS) model. The trends of the RANS model compare relatively well with results from a mesoscale model and measurements of wind turbine power. In addition, challenges of modeling a large domain in RANS are discussed.

Efficient large-scale wind turbine deployment can meet global electricity generation needs

Miller and Kleidon (1) study future global deployment of wind turbines. They use a general circulation model (GCM) with 2.8° resolution to simulate the electricity generation for different wind-power deployments using global constant installed capacity densities. Results from the simulations with the maximum electricity generation over land and over water form the foundation for their study: a generation over 100 times greater than the global electricity demand (2). Correctly modeling wind resources requires a proper terrain description and that meso- and microscale effects are resolved (3). Power density estimates from mesoscale models with a 10-km grid spacing can be more than 50% lower than those from high-resolution models … [↵][1]1To whom correspondence should be addressed. Email: jaba{at}dtu.dk. [1]: #xref-corresp-1-1

Downstream effects from contemporary wind turbine deployments

High-resolution regional simulations of the downstream effects of wind turbine arrays are presented. The simulations are conducted with the Weather Research and Forecasting (WRF) model using two different wind turbine parameterizations for a domain centered on the highest density of current wind turbine deployments in the contiguous US. The simulations use actual wind turbine geolocations and turbine specifications (e.g. power and thrust curves). Resulting analyses indicate that for both WT parameterizations impacts on temperature, specific humidity, precipitation, sensible and latent heat fluxes from current wind turbine deployments are statistically significant only in summer, are of very small magnitude, and are highly localized. It is also shown that use of the relatively recently developed new explicit wake parameterization (EWP) results in faster recovery of full array wakes. This in turn leads to smaller climate impacts and reduced array-array interactions, which at a systemwide scale lead to higher summertime capacity factors (2-6% higher) than those from the more commonly applied ‘Fitch’ parameterization. Our research implies that further expansion of wind turbine deployments can likely be realized without causing substantial downstream impacts on weather and climate, or array-array interactions of a magnitude that would yield substantial decreases in capacity factors.