Micrometeorological impacts of offshore wind farms as seen in observations and simulations

Siedersleben, Simon; Lundquist, Julie K.; Platis, Andreas; Bange, Jens; Bärfuss, Konrad; Lampert, Astrid; Cañadillas, Beatriz; Neumann, Thomas; Emeis, Stefan

doi:10.1088/1748-9326/aaea0b

Cited by 106 publications

(92 citation statements)

References 33 publications

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“…Offshore wind power plant wakes can extend tens of km downwind (Platis et al, ; Siedersleben, Platis, et al, ; Siedersleben, Lundquist et al, ) in low‐turbulence, stably stratified conditions. These wakes undermine offshore power production (Nygaard, ).…”

Section: Discussionmentioning

confidence: 99%

“…Offshore ϵ has, on average, smaller values compared to those found in comparable studies onshore, with a weak diurnal cycle. The small average values of ϵ are conducive to strong and long‐lived wakes such as wakes observed in stable stratification in the North Sea (Platis et al, ; Siedersleben, Lundquist et al, ; Siedersleben, Platis, et al, ). Moreover, this extended persistence of wakes will occur throughout the diurnal cycle, given the absence of strong turbulence dissipation even in convective daytime conditions.…”

Section: Discussionmentioning

confidence: 99%

“…Turbulence also plays a key role in the development and subsequent erosion of wind turbine and wind farm wakes, whose spatial extent can be particularly long offshore (Platis et al, ; Siedersleben, Lundquist et al, ; Siedersleben, Platis, et al, ), with observed wakes extending beyond 45 km in some cases. While the erosion of wakes is related to ambient turbulent kinetic energy, the dissipation of turbulence within the wake, which represents the first step of wake erosion, is defined by the turbulence dissipation rate.…”

Section: Introductionmentioning

confidence: 99%

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U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Bodini

Lundquist

Kirincich

2019

Geophysical Research Letters

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The rapid growth of offshore wind energy requires accurate modeling of the wind resource, which can be depleted by wind farm wakes. Turbulence dissipation rate (ϵ) governs the accuracy of model predictions of hub‐height wind speed and the development and erosion of wakes. Here we assess the variability of turbulence kinetic energy and ϵ using 13 months of observations from a profiling lidar deployed on a platform off the Massachusetts coast. Offshore, ϵ is 2 orders of magnitude smaller than onshore, with a subtle diurnal cycle. Wind direction influences the annual cycle of turbulence, with larger values in winter when the wind flows from the land, and smaller values in summer, when the wind flows from open ocean. Because of the weak turbulence, wind plant wakes will be stronger and persist farther downwind in summer.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Bodini

Lundquist

Kirincich

2019

Geophysical Research Letters

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“…The aim of the campaign was to quantify wind‐farm‐cluster wakes in the North Sea for stable conditions . While the measured data enable investigation of a broad range of meteorological phenomena, our focus here is on the wind speed recovery of wakes downstream of wind farm clusters and its dependence on stability.…”

Section: Description Of the Airborne Measurement Campaignmentioning

confidence: 93%

“…The data collected within the WIPAFF (WInd PArk Far Field) project have already been compared with the wakes inferred from satellite measurements and those simulated with mesoscale numerical weather prediction models . However, the results of the airborne measurement campaign have not yet been analyzed and summarized in a form suitable for direct implementation in engineering models, with the view of assessing the expected reduced energy yields of downstream wind farms.…”

Section: Introductionmentioning

confidence: 99%

Offshore wind farm wake recovery: Airborne measurements and its representation in engineering models

Cañadillas¹,

Foreman²,

Barth³

et al. 2020

Wind Energy

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We present an analysis of wind measurements from a series of airborne campaigns conducted to sample the wakes from two North Sea wind farm clusters, with the aim of determining the dependence of the downstream wind speed recovery on the atmospheric stability. The consequences of the stability dependence of wake length on the expected annual energy yield of wind farms in the North Sea are assessed by an engineering model. Wakes are found to extend for significantly longer downstream distances (>50 km) in stable conditions than in neutral and unstable conditions (<15 km). The parameters of one common engineering model are modified to reproduce the observed wake decay at downstream distances >30 km. More significant effects on the energy yield are expected for wind farms separated by distances <30 km, which is generally the case in the North Sea, but additional data would be required to validate the suggested parameter modifications within the engineering model. A case study is accordingly performed to show reductions in the farm efficiency downstream of a wind farm. These results emphasize not only the importance of understanding the impact of atmospheric stability on offshore wind farms but also the need to update the representation of wakes in current industry models to properly include wake-induced energy losses, especially in large offshore clusters. KEYWORDS atmospheric stability, offshore wind farm cluster, wake recovery, wind farm efficiency

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Evaluation of a simple analytical model for offshore wind farm wake recovery by in situ data and Weather Research and Forecasting simulations

et al. 2020

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The recovery of offshore wind farm wakes in the German Bight was analyzed by a unique in situ data set, measured on‐board the research aircraft Dornier Do‐128 during the WIPAFF project in 2016 and 2017. These observations were used to validate a simple analytical wake recovery model in five case studies. The observed recovery rates were compared with the results of the mesoscale Weather Research and Forecasting (WRF) model. The airborne data show that the wake recovery can be described by an exponential function as expected by the analytical model and strengthens the hypothesis that the vertical downward moment flux has an important influence on the wake recovery. However, the predicted wake recovery rates (by the analytical model) do not always fully agree with the observations. Although, as a first‐order approximation, the model seems to perform well, further optimization has to be implemented to account for wind park layout, turbine induced turbulence, and horizontal momentum flux. WRF simulations reveal an exponential recovery, although the mesoscale model does not reproduce the correct atmospheric conditions for most of the cases. Therefore, the wake recovery rates estimated by WRF disagree with the measured data in most of the studied cases.

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Micrometeorological impacts of offshore wind farms as seen in observations and simulations

Cited by 106 publications

References 33 publications

U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Offshore wind farm wake recovery: Airborne measurements and its representation in engineering models

Evaluation of a simple analytical model for offshore wind farm wake recovery by in situ data and Weather Research and Forecasting simulations

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