Coastal impacts on offshore wind farms – a review focussing on the German Bight area

Schulz‐Stellenfleth, Johannes; Emeis, Stefan; Dörenkämper, Martin; Bange, Jens; Cañadillas, Beatriz; Neumann, Thomas; Schneemann, Jörge; Weber, Ines; Berge, Kjell zum; Platis, Andreas; Djath, Bughsin; Gottschall, Julia; Vollmer, Lukas; Rausch, Thomas; Barekzai, Mares; Hammel, J.; Steinfeld, G.; Lampert, Astrid

doi:10.1127/metz/2022/1109

Cited by 10 publications

(10 citation statements)

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“…There are several pronounced features: Wind from the South-West sector was frequently associated with a wind speed between 5 m s −1 and 15 m s −1 . This corresponds to the most frequent wind direction for the North Sea (Platis et al, 2018), and is typically associated with stable conditions in spring and summer (Schulz-Stellenfleth et al, 2022). Further, conditions with wind directions from East were measured, which is also typically associated with stable conditions.…”

Section: Wind Directionmentioning

confidence: 85%

“…The phenomenon of the coastal transition was another target of the measurement flights. The coastal effect means that the abrupt changes of the surface properties at the coast, with lower surface roughness and different heat capacity, lead to modifications of the wind field and the thermal stratification (Schulz-Stellenfleth et al, 2022), which is particularly challenging to include in simulations (Siedersleben et al, 2018). The increase or decrease of wind speed due to synoptic scale changes and the coastal effect can be in the order of several m s −1 (e.g., Platis et al, 2018;Djath et al, 2022).…”

Section: Flight Planning and Flight Patternsmentioning

confidence: 99%

“…Results using the COAST flight patterns have been published in Schulz-Stellenfleth et al (2022) and Cañadillas et al (2023).…”

Section: Coastal Effect (Coast)mentioning

confidence: 99%

“…Further, the vertical exchange is increased, which results in enhanced latent heat fluxes (Platis et al, 2023). The wake effects are superposed by spatial variability of the wind field, in particular for wind from land to sea with sudden changes in surface properties at the coastal transition (Djath et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes

Lampert,

Hankers,

Feuerle

et al. 2024

Preprint

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Abstract. Between 14 March 2020 and 11 September 2021, meteorological measurement flights were conducted above the German Bight in the framework of the project X-Wakes. The scope of the measurements was to study the transition of the wind field and atmospheric stability from the coast to the sea, to study the interaction of wind park wakes, and to study the large-scale modification of the marine atmospheric boundary layer by the presence of wind parks. In total 49 measurement flights were performed with the research aircraft Dornier 128 of the Technische Universität (TU) Braunschweig during different seasons and different stability conditions. Seven of the flights in the time period from 24 to 30 July 2021 were coordinated with a second research aircraft, the Cessna F406 of TU Braunschweig. The instrumentation of both aircraft consisted of a nose boom with sensors for measuring the wind vector, temperature and humidity, and additionally a surface temperature sensor. The Dornier 128 was further equipped with a laser scanner for deriving sea state properties and two downward looking cameras in the visible and infrared wavelength range. The Cessna F406 was additionally equipped with shortwave and longwave broadband radiation sensors for measuring upward and downward solar and terrestrial radiation. A detailed overview of the aircraft, sensors, data post-processing and flight patterns is provided here. Further, averaged profiles of atmospheric parameters illustrate the range of conditions. The potential use of the data set has been shown already by first publications. The data of both aircraft are publicly available in the world data centre PANGAEA: https://doi.pangaea.de/10.1594/PANGAEA.955382 (Rausch et al., 2023).

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Section: Wind Directionmentioning

confidence: 85%

Section: Flight Planning and Flight Patternsmentioning

confidence: 99%

“…Results using the COAST flight patterns have been published in Schulz-Stellenfleth et al (2022) and Cañadillas et al (2023).…”

Section: Coastal Effect (Coast)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes

Lampert,

Hankers,

Feuerle

et al. 2024

Preprint

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“…In coastal regions, LLJ, characterized by a maximum in the wind speed profile in the lower troposphere [7,8], can have different driving mechanisms [9]. According to Schulz-Stellenfleth et al [10], LLJ can be attributed to frictional decoupling from the underlying surface or baroclinicity due to the temperature contrast between the land and sea. Over the southern North Sea, relatively warm continental air advected over the cooler sea surface supports the development of surface temperature inversion, leading to the decoupling of the surface friction and acceleration of an air mass [11,12].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning and Deterministic Methods for Detection Meteorological Phenomena from Ground Measurements: Application for Low-Level Jet and Sea-Breeze Identification in Northern France

et al. 2022

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This study focused on the detection of mesoscale meteorological phenomena, such as the nocturnal low-level jet (NLLJ) and sea breeze (SB), using automatic deterministic detection wavelet technique algorithms (HWTT and SWT) and the machine learning recurrent neural network (RNN) algorithm. The developed algorithms were applied for detection of NLLJ and SB events from ultrasonic anemometer measurements, performed between January 2018 and December 2019 at a nearshore experimental site in the north of France. Both algorithms identified the SB and NLLJ days successfully. The accuracy of SB event detection by the RNN algorithm attained 95%, and we identified 67 and 78 SB days in 2018 and 2019, respectively. Additionally, a total of 192 and 168 NLLJ days were found in 2018 and 2019, respectively. To demonstrate the capability of the algorithms to detect SB and NLLJ events from near-ground ultrasonic anemometer measurements, analysis of the simultaneous wind lidar measurements available for 86 days were performed. The results show a good agreement between the RNN-based detection method and the lidar observations, detecting 88% of SB. Deterministic algorithms (HWTT and SWT) detected a similar number of NLLJ events and provided high correlation (0.98) with the wind lidar measurements. The meteorological phenomena studied can significantly affect the energy production of offshore wind farms. It was found that the maximum hourly average peak power production could be to 5 times higher than that of the reference day due to higher wind speed observed during NLLJ events. During SB events, hourly average peak power production could be up to 2.5 times higher. In this respect, the developed algorithms applied for analysis, from near-ground anemometer measurements, may be helpful for monitoring and forecasting the meteorological phenomena capable of disturbing the energy production of offshore wind turbines.

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Effect of an abrupt rough-to-smooth surface roughness transition on wind farm wakes: An LES and analytical modeling study

Kethavath,

Ghaisas

2024

Journal of Renewable and Sustainable Energy

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Large-eddy simulations (LES) are performed on the flow over a wind farm sited behind an abrupt rough-to-smooth surface roughness jump. The change in surface roughness affects both the first-order and second-order turbulent statistics. The usual deficit, i.e., the difference between the velocities upstream of the entire wind farm and downstream of a turbine, attains negative values close to the ground, which makes it difficult for modeling within the usual Gaussian radial-shape framework. A different definition, i.e., the difference in velocity at the same location with and without a turbine on a heterogeneous surface, is always positive and is amenable to Gaussian shape-based modeling. For the setup considered here, wind farms sited downstream of a surface roughness jump produce more power than a wind farm sited on a homogeneously rough surface. This increase is primarily because of the larger power generated by the downstream turbines and only slightly due to the increased power of the first-row turbine. The farm performance is affected by the distance between the abrupt change in surface roughness and the position of the first row of turbines. The wind farm performance is also dependent on the aerodynamic roughness upstream of the surface roughness jump. Two single-turbine analytical models and three wake-merging strategies are evaluated for their ability to predict the velocity deficits. A corrected form of the standard Gaussian model with a recently proposed wake-merging methodology, applicable for a varying background field, is found to be insensitive to the tunable model parameter and is consistently in line with the LES results.

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Coastal impacts on offshore wind farms – a review focussing on the German Bight area

Cited by 10 publications

References 0 publications

In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes

In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes

Machine Learning and Deterministic Methods for Detection Meteorological Phenomena from Ground Measurements: Application for Low-Level Jet and Sea-Breeze Identification in Northern France

Effect of an abrupt rough-to-smooth surface roughness transition on wind farm wakes: An LES and analytical modeling study

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