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Rapid growth in the offshore wind energy sector means more offshore wind farms are placed closer to each other and in the lee of large land masses. Synthetic aperture radar (SAR) offers maps of the wind speed offshore with high resolution over large areas. These can be used to detect horizontal wind speed gradients close to shore and wind farm wake effects. SAR observations have become much more available with the free and open-access data from European satellite missions through Copernicus. Examples of applications and tools for using large archives of SAR wind maps to aid offshore site assessment are few. The Anholt wind farm operated by the utility company Ørsted is located in coastal waters and experiences strong spatial variations in the mean wind speed. Wind speeds derived from the Supervisory Control And Data Acquisition (SCADA) system are available at the turbine locations for comparison with winds retrieved from SAR. The correlation is good, both for free-stream and waked conditions. Spatial wind speed variations along the rows of wind turbines derived from SAR wind maps prior to the wind farm construction agree well with information gathered by the SCADA system and a numerical weather prediction model. Wind farm wakes are detected by comparisons between images before and after the wind farm construction. SAR wind maps clearly show wakes for long and constant fetches but the wake effect is less pronounced for short and varying fetches. Our results suggest that SAR wind maps can support offshore wind energy site assessment by introducing observations in the early phases of wind farm projects.
Tobias Ahsbahs; Merete Badger; Patrick Volker; Kurt S. Hansen; Charlotte B. Hasager. Applications of satellite winds for the offshore wind farm site Anholt. Wind Energy Science 2018, 3, 573 -588.
AMA StyleTobias Ahsbahs, Merete Badger, Patrick Volker, Kurt S. Hansen, Charlotte B. Hasager. Applications of satellite winds for the offshore wind farm site Anholt. Wind Energy Science. 2018; 3 (2):573-588.
Chicago/Turabian StyleTobias Ahsbahs; Merete Badger; Patrick Volker; Kurt S. Hansen; Charlotte B. Hasager. 2018. "Applications of satellite winds for the offshore wind farm site Anholt." Wind Energy Science 3, no. 2: 573-588.
Rapid growth in the offshore wind energy sector means more offshore wind farms are placed closer to each other and in the lee of large land masses. Synthetic Aperture Radar (SAR) offers maps of the wind speed offshore with high resolution over large areas. These can be used to detect horizontal wind speed gradients close to shore and wind farm wake effects. SAR observations have become much more available with the free and open access to data from European satellite missions through Copernicus. Examples of applications and tools for using large archives of SAR wind maps to aid offshore site assessment are few. The Anholt wind farm operated by the utility company Ørsted is located in coastal waters and experiences strong spatial variations in the mean wind speed. Wind speeds derived from the Supervisory Control And Data Acquisition (SCADA) system are available at the turbine locations for comparison with winds retrieved from SAR. The correlation is good, both for free stream and waked conditions. Spatial wind speed variations within the wind farm derived from SAR wind maps prior to the wind farm construction are found to agree well with information gathered by the SCADA system and numerical weather prediction models. Wind farm wakes are detected by comparisons between images before and after the wind farm construction. SAR wind maps clearly show wakes for long constant fetches but the wake effect is less pronounced for short varying fetches. Our results suggest that SAR wind maps can support offshore wind energy site assessment by introducing observations in the early phases of wind farm projects.
Tobias Ahsbahs; Merete Badger; Patrick Volker; Kurt S. Hansen; Charlotte B. Hasager. Applications of satellite winds for the offshore wind farm site Anholt. 2018, 2018, 1 -24.
AMA StyleTobias Ahsbahs, Merete Badger, Patrick Volker, Kurt S. Hansen, Charlotte B. Hasager. Applications of satellite winds for the offshore wind farm site Anholt. . 2018; 2018 ():1-24.
Chicago/Turabian StyleTobias Ahsbahs; Merete Badger; Patrick Volker; Kurt S. Hansen; Charlotte B. Hasager. 2018. "Applications of satellite winds for the offshore wind farm site Anholt." 2018, no. : 1-24.
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 …
Jake Badger; Patrick J. H. Volker. Efficient large-scale wind turbine deployment can meet global electricity generation needs. Proceedings of the National Academy of Sciences 2017, 114, E8945 -E8945.
AMA StyleJake Badger, Patrick J. H. Volker. Efficient large-scale wind turbine deployment can meet global electricity generation needs. Proceedings of the National Academy of Sciences. 2017; 114 (43):E8945-E8945.
Chicago/Turabian StyleJake Badger; Patrick J. H. Volker. 2017. "Efficient large-scale wind turbine deployment can meet global electricity generation needs." Proceedings of the National Academy of Sciences 114, no. 43: E8945-E8945.
The growing share of electricity production from solar and mainly wind resources constantly increases the stochastic nature of the power system. Modelling the high share of renewable energy sources – and in particular wind power – crucially depends on the adequate representation of the intermittency and characteristics of the wind resource which is related to the accuracy of the approach in converting wind speed data into power values. One of the main factors contributing to the uncertainty in these conversion methods is the selection of the spatial resolution. Although numerical weather prediction models can simulate wind speeds at higher spatial resolution (up to 1 × 1 km) than a reanalysis (generally, ranging from about 25 km to 70 km), they require high computational resources and massive storage systems: therefore, the most common alternative is to use the reanalysis data. However, local wind features could not be captured by the use of a reanalysis technique and could be translated into misinterpretations of the wind power peaks, ramping capacities, the behaviour of power prices, as well as bidding strategies for the electricity market. This study contributes to the understanding what is captured by different wind speeds spatial resolution datasets, the importance of using high resolution data for the conversion into power and the implications in power system analyses. It is proposed a methodology to increase the spatial resolution from a reanalysis. This study presents an open access renewable generation time series dataset for the EU-28 and neighbouring countries at hourly intervals and at different geographical aggregation levels (country, bidding zone and administrative territorial unit), for a 30 year period taking into account the wind generating fleet at the end of 2015.JRC.C.7-Knowledge for the Energy Unio
I. González-Aparicio; F. Monforti; Patrick Volker; A. Zucker; F. Careri; Thomas Huld; J. Badger. Simulating European wind power generation applying statistical downscaling to reanalysis data. Applied Energy 2017, 199, 155 -168.
AMA StyleI. González-Aparicio, F. Monforti, Patrick Volker, A. Zucker, F. Careri, Thomas Huld, J. Badger. Simulating European wind power generation applying statistical downscaling to reanalysis data. Applied Energy. 2017; 199 ():155-168.
Chicago/Turabian StyleI. González-Aparicio; F. Monforti; Patrick Volker; A. Zucker; F. Careri; Thomas Huld; J. Badger. 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data." Applied Energy 199, no. : 155-168.
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.
M. P. Van Der Laan; A. Peña; Patrick Volker; K. S. Hansen; N. N. Sørensen; S. Ott; C. B. Hasager. Challenges in simulating coastal effects on an offshore wind farm. Journal of Physics: Conference Series 2017, 854, 12046 .
AMA StyleM. P. Van Der Laan, A. Peña, Patrick Volker, K. S. Hansen, N. N. Sørensen, S. Ott, C. B. Hasager. Challenges in simulating coastal effects on an offshore wind farm. Journal of Physics: Conference Series. 2017; 854 (1):12046.
Chicago/Turabian StyleM. P. Van Der Laan; A. Peña; Patrick Volker; K. S. Hansen; N. N. Sørensen; S. Ott; C. B. Hasager. 2017. "Challenges in simulating coastal effects on an offshore wind farm." Journal of Physics: Conference Series 854, no. 1: 12046.
Offshore wind farm wakes were observed and photographed in foggy conditions at Horns Rev 2 on 25 January 2016 at 12:45 UTC. These new images show highly contrasting conditions regarding the wind speed, turbulence intensity, atmospheric stability, weather conditions and wind farm wake development as compared to the Horns Rev 1 photographs from 12 February 2008. The paper examines the atmospheric conditions from satellite images, radiosondes, lidar and wind turbine data and compares the observations to results from atmospheric meso-scale modelling and large eddy simulation. Key findings are that a humid and warm air mass was advected from the southwest over cold sea and the dew-point temperature was such that cold-water advection fog formed in a shallow layer. The flow was stably stratified and the freestream wind speed was 13 m/s at hub height, which means that most turbines produced at or near rated power. The wind direction was southwesterly and long, narrow wakes persisted several rotor diameters downwind of the wind turbines. Eventually mixing of warm air from aloft dispersed the fog in the far wake region of the wind farm.
Charlotte Bay Hasager; Nicolai Gayle Nygaard; Patrick J. H. Volker; Ioanna Karagali; Søren Juhl Andersen; Jake Badger. Wind Farm Wake: The 2016 Horns Rev Photo Case. Energies 2017, 10, 317 .
AMA StyleCharlotte Bay Hasager, Nicolai Gayle Nygaard, Patrick J. H. Volker, Ioanna Karagali, Søren Juhl Andersen, Jake Badger. Wind Farm Wake: The 2016 Horns Rev Photo Case. Energies. 2017; 10 (3):317.
Chicago/Turabian StyleCharlotte Bay Hasager; Nicolai Gayle Nygaard; Patrick J. H. Volker; Ioanna Karagali; Søren Juhl Andersen; Jake Badger. 2017. "Wind Farm Wake: The 2016 Horns Rev Photo Case." Energies 10, no. 3: 317.
The decarbonisation of energy sources requires additional investments in renewable technologies, including the installation of onshore and offshore wind farms. For wind energy to remain competitive, wind farms must continue to provide low-cost power even when covering larger areas. Inside very large wind farms, winds can decrease considerably from their free-stream values to a point where an equilibrium wind speed is reached. The magnitude of this equilibrium wind speed is primarily dependent on the balance between turbine drag force and the downward momentum influx from above the wind farm. We have simulated for neutral atmospheric conditions, the wind speed field inside different wind farms that range from small (25 km2) to very large (105 km2) in three regions with distinct wind speed and roughness conditions. Our results show that the power density of very large wind farms depends on the local free-stream wind speed, the surface characteristics, and the turbine density. In onshore regions with moderate winds the power density of very large wind farms reaches 1 W m−2, whereas in offshore regions with very strong winds it exceeds 3 W m−2. Despite a relatively low power density, onshore regions with moderate winds offer potential locations for very large wind farms. In offshore regions, clusters of smaller wind farms are generally preferable; under very strong winds also very large offshore wind farms become efficient.
Patrick Volker; Andrea N. Hahmann; Jake Badger; Hans Ejsing Jørgensen. Prospects for generating electricity by large onshore and offshore wind farms. Environmental Research Letters 2017, 12, 034022 .
AMA StylePatrick Volker, Andrea N. Hahmann, Jake Badger, Hans Ejsing Jørgensen. Prospects for generating electricity by large onshore and offshore wind farms. Environmental Research Letters. 2017; 12 (3):034022.
Chicago/Turabian StylePatrick Volker; Andrea N. Hahmann; Jake Badger; Hans Ejsing Jørgensen. 2017. "Prospects for generating electricity by large onshore and offshore wind farms." Environmental Research Letters 12, no. 3: 034022.
We describe the theoretical basis, implementation, and validation of a new parametrisation that accounts for the effect of large offshore wind farms on the atmosphere and can be used in mesoscale and large-scale atmospheric models. This new parametrisation, referred to as the Explicit Wake Parametrisation (EWP), uses classical wake theory to describe the unresolved wake expansion. The EWP scheme is validated for a neutral atmospheric boundary layer against filtered in situ measurements from two meteorological masts situated a few kilometres away from the Danish offshore wind farm Horns Rev I. The simulated velocity deficit in the wake of the wind farm compares well to that observed in the measurements, and the velocity profile is qualitatively similar to that simulated with large eddy simulation models and from wind tunnel studies. At the same time, the validation process highlights the challenges in verifying such models with real observations.
P. J. H. Volker; J. Badger; A. N. Hahmann; S. Ott. The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF. Geoscientific Model Development 2015, 8, 3715 -3731.
AMA StyleP. J. H. Volker, J. Badger, A. N. Hahmann, S. Ott. The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF. Geoscientific Model Development. 2015; 8 (11):3715-3731.
Chicago/Turabian StyleP. J. H. Volker; J. Badger; A. N. Hahmann; S. Ott. 2015. "The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF." Geoscientific Model Development 8, no. 11: 3715-3731.
K S Hansen; Pierre-Elouan Réthoré; J Palma; B G Hevia; J Prospathopoulos; A Peña; S Ott; G Schepers; A Palomares; M P Van Der Laan; Patrick Volker. Simulation of wake effects between two wind farms. Journal of Physics: Conference Series 2015, 625, 012008 .
AMA StyleK S Hansen, Pierre-Elouan Réthoré, J Palma, B G Hevia, J Prospathopoulos, A Peña, S Ott, G Schepers, A Palomares, M P Van Der Laan, Patrick Volker. Simulation of wake effects between two wind farms. Journal of Physics: Conference Series. 2015; 625 ():012008.
Chicago/Turabian StyleK S Hansen; Pierre-Elouan Réthoré; J Palma; B G Hevia; J Prospathopoulos; A Peña; S Ott; G Schepers; A Palomares; M P Van Der Laan; Patrick Volker. 2015. "Simulation of wake effects between two wind farms." Journal of Physics: Conference Series 625, no. : 012008.
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.
Charlotte Bay Hasager; P Vincent; R Husson; A Mouche; Merete Badger; A Peña; Patrick Volker; J Badger; Alessandro Di Bella; A Palomares; E Cantero; P M F Correia. Comparing satellite SAR and wind farm wake models. Journal of Physics: Conference Series 2015, 625, 012035 .
AMA StyleCharlotte Bay Hasager, P Vincent, R Husson, A Mouche, Merete Badger, A Peña, Patrick Volker, J Badger, Alessandro Di Bella, A Palomares, E Cantero, P M F Correia. Comparing satellite SAR and wind farm wake models. Journal of Physics: Conference Series. 2015; 625 ():012035.
Chicago/Turabian StyleCharlotte Bay Hasager; P Vincent; R Husson; A Mouche; Merete Badger; A Peña; Patrick Volker; J Badger; Alessandro Di Bella; A Palomares; E Cantero; P M F Correia. 2015. "Comparing satellite SAR and wind farm wake models." Journal of Physics: Conference Series 625, no. : 012035.
Offshore wind farm cluster effects between neighboring wind farms increase rapidly with the large-scale deployment of offshore wind turbines. The wind farm wakes observed from Synthetic Aperture Radar (SAR) are sometimes visible and atmospheric and wake models are here shown to convincingly reproduce the observed very long wind farm wakes. The present study mainly focuses on wind farm wake climatology based on Envisat ASAR. The available SAR data archive covering the large offshore wind farms at Horns Rev has been used for geo-located wind farm wake studies. However, the results are difficult to interpret due to mainly three issues: the limited number of samples per wind directional sector, the coastal wind speed gradient, and oceanic bathymetry effects in the SAR retrievals. A new methodology is developed and presented. This method overcomes effectively the first issue and in most cases, but not always, the second. In the new method all wind field maps are rotated such that the wind is always coming from the same relative direction. By applying the new method to the SAR wind maps, mesoscale and microscale model wake aggregated wind-fields results are compared. The SAR-based findings strongly support the model results at Horns Rev 1.
Charlotte Bay Hasager; Pauline Vincent; Jake Badger; Merete Badger; Alessandro Di Bella; Alfredo Peña; Romain Husson; Patrick J. H. Volker. Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms. Energies 2015, 8, 5413 -5439.
AMA StyleCharlotte Bay Hasager, Pauline Vincent, Jake Badger, Merete Badger, Alessandro Di Bella, Alfredo Peña, Romain Husson, Patrick J. H. Volker. Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms. Energies. 2015; 8 (6):5413-5439.
Chicago/Turabian StyleCharlotte Bay Hasager; Pauline Vincent; Jake Badger; Merete Badger; Alessandro Di Bella; Alfredo Peña; Romain Husson; Patrick J. H. Volker. 2015. "Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms." Energies 8, no. 6: 5413-5439.
We describe the theoretical basis, implementation and validation of a new parametrisation that accounts for the effect of large offshore wind farms on the atmosphere and can be used in mesoscale and large-scale atmospheric models. This new parametrisation, referred to as the Explicit Wake Parametrisation (EWP), uses classical wake theory to describe the unresolved wake expansion. The EWP scheme is validated against filtered in situ measurements from two meteorological masts situated a few kilometres away from the Danish offshore wind farm Horns Rev I. The simulated velocity deficit in the wake of the wind farm compares well to that observed in the measurements and the velocity profile is qualitatively similar to that simulated with large eddy simulation models and from wind tunnel studies. At the same time, the validation process highlights the challenges in verifying such models with real observations.
P. J. H. Volker; J. Badger; A. N. Hahmann; S. Ott. The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF. Geoscientific Model Development Discussions 2015, 1 .
AMA StyleP. J. H. Volker, J. Badger, A. N. Hahmann, S. Ott. The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF. Geoscientific Model Development Discussions. 2015; ():1.
Chicago/Turabian StyleP. J. H. Volker; J. Badger; A. N. Hahmann; S. Ott. 2015. "The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF." Geoscientific Model Development Discussions , no. : 1.