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The aim of the paper is to examine the nowadays well-known wind farm wake photographs taken on 12 February 2008 at the offshore Horns Rev 1 wind farm. The meteorological conditions are described from observations from several satellite sensors quantifying clouds, surface wind vectors and sea surface temperature as well as ground-based information a...
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High-fidelity wind farm models typically employ large-eddy simulation (LES) formulations and turbine parametrisations (e.g. actuator disc models) to resolve the turbine wakes at spatial and temporal scales so that all flow features of engineering improtance are well-captured. Such features include the low frequency dynamic wake meandering, which pl...
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Citations
... Horns Rev wind farm in salt spray weather[6].J. Mar. Sci. ...
... Eng. 2025, 13, x FOR PEER REVIEW 4 Horns Rev wind farm in salt spray weather[6]. ...
With the urgent demand for net-zero emissions, renewable energy is taking the lead and wind power is becoming increasingly important. Among the most promising sources, offshore wind energy located in deep water has gained significant attention. This review focuses on the experimental methods, simulation approaches, and wake characteristics of floating offshore wind turbines (FOWTs). The hydrodynamics and aerodynamics of FOWTs are not isolated and they interact with each other. Under the environmental load and mooring force, the floating platform has six degrees of freedom motions, which bring the changes in the relative wind speed to the turbine rotor, and furthermore, to the turbine aerodynamics. Then, the platform’s movements lead to a complex FOWT wake evolution, including wake recovery acceleration, velocity deficit fluctuations, wake deformation and wake meandering. In scale FOWT tests, it is challenging to simultaneously satisfy Reynolds number and Froude number similarity, resulting in gaps between scale model experiments and field measurements. Recently, progress has been made in scale model experiments; furthermore, a “Hardware in the loop” technique has been developed as an effective solution to the above contradiction. In numerical simulations, the coupling of hydrodynamics and aerodynamics is the concern and a typical numerical simulation of multi-body and multi-physical coupling is reviewed in this paper. Furthermore, recent advancements have been made in the analysis of wake characteristics, such as the application of instability theory and modal decomposition techniques in the study of FOWT wake evolution. These studies have revealed the formation of vortex rings and leapfrogging behavior in adjacent helical vortices, which deepens the understanding of the FOWT wake. Overall, this paper provides a comprehensive review of recent research on FOWT wake dynamics.
... 41,42 Although previous research suggested bat fatalities caused by barotrauma, 43,44 more recent studies Impacts on wind resources and weather The increasing number and size of wind farms can affect local weather and climate patterns, 84 though the magnitude of these effects is debated. 85 There is broad evidence based on photographs, 86 satellite imagery, 87,88 measurements, [89][90][91] and modeling. 92 Wind turbines extract kinetic energy from the wind flowing through their rotors, replenished downstream of the flow above the wind farm. ...
Wind power accounted for 8% of global electricity generation in 2023 and is one of the cheapest forms of low-carbon electricity. Although fully commercial, many challenges remain in achieving the required scale-up, relating to integrating wind farms into wider technical, economic, social, and natural systems. We review the main challenges, outline existing solutions, and propose future research needed to overcome existing problems. Although the techno-economic challenges of grid and market integration are seen as significant obstacles to scaling up wind power, the field is replete with solutions. In many countries, planning and permitting are immediate barriers to wind-power deployment; although solutions are emerging in the EU and several countries, the effectiveness and long-term acceptance of fast-track permissions and go-to areas remains to be seen. Environmental impacts on wildlife and recycling challenges are rising issues for which tested and scalable solutions are often still lacking, pointing to large remaining research requirements.
... For all wind directions, the difference between CCLM_WF15 and CCLM_WF5 is low as well with approximately 0.1%. This additional formation of clouds above wind farms has also been observed 50 . ...
The EU aims for carbon neutrality by 2050, focusing on offshore wind energy. Investments in North Sea wind farms, with optimal wind resources, play a crucial role. We employed a high-resolution regional climate model, which incorporates a wind farm parametrization, to investigate and address potential mitigating impacts of large wind farms on power generation and air-sea fluxes. Specifically, we examined the effects of replacing 5 MW turbines with larger 15 MW turbines while maintaining total capacity. Our study found that substituting 15 MW turbines increases the capacity factor by 2–3%, enhancing efficiency. However, these turbines exhibit a slightly smaller impact on 10 m wind speed (1.2–1.5%) and near-surface kinetic energy (0.1–0.2%), leading to reduced effects on sea surface heat fluxes compared to 5 MW turbines. This was confirmed by a stronger reduction in net heat flux of about 0.6–1.3% in simulations with 5 MW compared to 15 MW wind turbines. Air-sea fluxes influence ocean dynamics and marine ecosystems; therefore, minimizing these impacts is crucial. Overall, deploying 15 MW turbines in offshore wind farms may offer advantages for ocean dynamics and marine ecosystems, supporting the EU's carbon–neutral objectives.
... Photographs of the offshore wind farm Horns Rev 2 in foggy conditions observed on 16 April 2018 at 15:13 UTC are complementary to a case in 2008 at the Horns Rev 1 wind farm [19] and another case in 2016 at the Horns Rev 2 wind farm [20]. The photographs are fascinating due to the wind farm effects becoming visible in those particular moments where atmospheric water transforms between gaseous and liquid phases through condensation and dispersion. ...
... There is a gap in the literature on the blockage effect revealed by fog at offshore wind farms. The iconic photographs of offshore wind farm wake [19,20] are often shown in the wind industry. The new photographs might be supportive of learning about blockage effects. ...
... The hub height is 68 m above mean sea level (aMSL). The wind farm entered full operation in November 2009 [19]. The Horns Rev 3 wind farm (not shown) north of Horns Rev 2 was in construction and produced its first power in December 2018. ...
Fog conditions at the offshore wind farm Horns Rev 2 were photographed on 16 April 2018. In this study, we present the results of an analysis of the meteorological conditions on the day of the photographs. The aim of the study was to examine satellite images, meteorological observations, wind turbine data, lidar data, reanalysis data, and wake and blockage model results to assess whether wind farm blockage was a likely cause for the formation of fog upstream of the wind farm. The analysis indicated the advection of warm and moist air mass from the southwest over a cool ocean, causing cold sea fog. Wind speeds at hub height were slightly above cut-in, and there was a strong veer in the shallow stable boundary layer. The most important finding is that the wake and blockage model indicated stagnant air mass arcs to the south and west of the wind farm. In the photographs, sea fog is visible in approximately the same area. Therefore, it is likely that the reduced wind triggered the sea fog condensation due to blockage in this area. A discrepancy between the blockage model and sea fog in the photographs appears in the southwest direction. Slightly higher winds might have occurred locally in a southwesterly direction, which may have dissolved sea fog. The wake model predicted long and narrow wind turbine wakes similar to those observed in the photographs. The novelty of the study is new evidence of wind farm blockage. It fills the gap in knowledge about flow in wind farms. Implications for future research include advanced modeling of flow phenomena near large offshore wind farms relevant to wind farm operators.
... In [5], it is estimated that the wake effects account for a 28% AEP loss. Another paradigmatic test case is the Horns Rev wind farm [6][7][8][9]. In that wind farm, the turbine spacing is higher (7, 9.3, and 10.4 rotor diameters) and the particular interest of the test case is in the fact that the wind farm is very large (80 Vestas V80 wind turbines). ...
Wakes between neighboring wind turbines are a significant source of energy loss in wind farm operations. Extensive research has been conducted to analyze and understand wind turbine wakes, ranging from aerodynamic descriptions to advanced control strategies. However, there is a relatively overlooked research area focused on characterizing real-world wind farm operations under wake conditions using Supervisory Control And Data Acquisition (SCADA) parameters. This study aims to address this gap by presenting a detailed discussion based on SCADA data analysis from a real-world test case. The analysis focuses on two selected wind turbines within an onshore wind farm operating under wake conditions. Operation curves and data-driven methods are utilized to describe the turbines’ performance. Particularly, the analysis of the operation curves reveals that a wind turbine operating within a wake experiences reduced power production not only due to the velocity deficit but also due to increased turbulence intensity caused by the wake. This effect is particularly prominent during partial load operation when the rotational speed saturates. The turbulence intensity, manifested in the variability of rotational speed and blade pitch, emerges as the crucial factor determining the extent of wake-induced power loss. The findings indicate that turbulence intensity is strongly correlated with the proximity of the wind direction to the center of the wake sector. However, it is important to consider that these two factors may convey slightly different information, possibly influenced by terrain effects. Therefore, both turbulence intensity and wind direction should be taken into account to accurately describe the behavior of wind turbines operating within wakes.
... When a wind turbine absorbs energy from the air, the air downstream of the wind turbine has reduced power, which often reduces the power production of downstream turbines. This is known as the wake effect (Sanderse, 2009;Hasager et al., 2013). When a new wind power plant is to be constructed, optimal turbine locations are determined using engineering wind farm models (Samorani, 2013;Ning. ...
It is important to optimize wind turbine positions to mitigate potential wake losses. To perform this optimization, atmospheric conditions, such as the inflow speed and direction, are assigned probability distributions according to measured data, which are propagated through engineering wake models to estimate the annual energy production (AEP). This study presents stochastic gradient descent (SGD) for wind farm optimization, which is an approach that estimates the gradient of the AEP using Monte Carlo simulation, allowing for the consideration of an arbitrarily large number of atmospheric conditions. SGD is demonstrated using wind farms with square and circular boundaries, considering cases with 100, 144, 225, and 325 turbines, and the results are compared to a deterministic optimization approach. It is shown that SGD finds a larger optimal AEP in substantially less time than the deterministic counterpart as the number of wind turbines is increased.
... The wake effect was described through the expressions of N.O. Jensen in 1983 and has been continuously improved for different situations [15]. Analysis from [16] study shows the case of optimising the placement of 5 turbines in a specific terrain and the role played by the wake effect in each realised scenario. ...
... Regarding 2D distance, for Arc, I, L, M, and V layouts, the values are 84. 607 15, and 87.457 GWh/yr. The indicators used to find the optimised form are: comparing the annual energy results and the performance coefficient for the considered forms. ...
Among the current challenges facing the energy sector is finding environmentally friendly and high-performance forms of energy generation. One such form of energy generation is from the wind. In addition to the fluctuations that cause changes in the generated energy, another factor that significantly affects the overall efficiency of wind farms is the distance between the turbines. In that context, a distance of at least three diameters (3D) onwards is necessary to enable a stable operation. This is more difficult to implement for mountainous terrain due to the terrain configuration’s influence, the turbine units’ positioning, and the mutual influence resulting from their position in the area under consideration. This work investigates the interdependence of the terrain features, the placement of ten turbines in different scenarios, and the impact on the overall efficiency of the wind farm. The place where the wind farm is considered is in Koznica, a mountainous area near Prishtina. An analysis has been carried out for two-diameter (2D), three-diameter (3D), and five-diameter (5D) turbine blade spacing for turbines with a rated power of 3.4 MW. The study considers placement in the following forms: Arc, I, L, M, and V. The results show that for 2D distance layout, the capacity factors for Arc, I, L, M, and V placements have the values: 32.9%, 29.8%, 31.1%, 30.6%, and 37.1%. For the 3D distance, according to these scenarios, the capacity factor values are: 29.9%, 30.8%, 30.4%, 29.3%, and 35.6%. For the longest distance, 5D, the capacity factor values are: 28.9%, 29.9%, 29.4%, 27.6%, and 30.6%. The value of the capacity factor for an optimal layout; is achieved at 39.3%.
... Offshore wind farms (OWFs) convert kinetic wind energy into electricity, creating regions of reduced wind speed and high atmospheric turbulence intensity downstream of wind turbine arrays. Christiansen and Hasager (2005); Christiansen and Hasager (2006) were the first to describe these wind-wakes by synthetic aperture radar (SAR)derived wind speed images and well-known wind farm wake photographs (Hasager et al., 2013). Numerical analyses by Broström (2008) triggered a series of modeling studies (Paskyabi and Fer, 2012;Paskyabi, 2015;Ludewig, 2015), which all predicted that a wind speed of 5-10 m s -1 generates so-called upwelling/downwelling dipoles in a stratified ocean with vertical velocities exceeding 1 m day -1 . ...
The operational principle of offshore wind farms (OWF) is to extract kinetic energy from the atmosphere and convert it into electricity. Consequently, a region of reduced wind speed in the shadow zone of an OWF, the so-called wind-wake, is generated. As there is a horizontal wind speed deficit between the wind-wake and the undisturbed neighboring regions, the locally reduced surface stress results in an adjusted Ekman transport. Subsequently, the creation of a dipole pattern in sea surface elevation induces corresponding anomalies in the vertical water velocities. The dynamics of these OWF wind-wake induced upwelling/downwelling dipoles have been analyzed in earlier model studies, and strong impacts on stratified pelagic ecosystems have been predicted. Here we provide for the first time empirical evidence of the existence of such upwelling/downwelling dipoles. The data were obtained by towing a remotely operated vehicle (TRIAXUS ROTV) through leeward regions of operational OWFs in the summer stratified North Sea. The undulating TRIAXUS transects provided high-resolution CTD data which enabled the characterization of three different phases of the ephemeral life cycle of a wind-wake-induced upwelling/downwelling dipole: development, operation, and erosion. We identified two characteristic hydrographic signatures of OWF-induced dipoles: distinct changes in mixed layer depth and potential energy anomaly over a distance < 5 km and a diagonal excursion of the thermocline of ~10–14 m over a dipole dimension of ~10–12 km. Whether these anthropogenically induced abrupt changes are significantly different from the corridor of natural variability awaits further investigations.
... Decentralized multi-objective optimization framework in a large-scale wind farm[29,30]. ...
Operation optimization for large-scale offshore wind farms can cause the fatigue loads of single wind turbines to exceed their limits. This study aims to improve the economic profit of offshore wind farms by conducting multi-objective optimization via decoupled group operations of turbines. To do this, a large-scale wind farm is firstly divided into several decoupled subsets through the parallel depth-first search (PDFS) and hyperlink-induced topic search (HITS) algorithms based on the wake-based direction graph. Next, three optimization objectives are considered, including total output power, total fatigue load, and fatigue load dispatch on a single wind turbine (WT) in a wind farm. And then, the combined Monte Carlo and beetle swarm optimization (CMC-BSO) algorithms are applied to solve the multi-objective non-convex optimization problem based on the decentralized communication network topology. Finally, the simulation results demonstrate that the proposed method balances the total power output, fatigue load, and single fatigue loads with fast convergence.
... Fish and top-predators rely on these repeated tidal patterns, but scientific evidence of the possible effects of this variation are lacking. The most known consequence of wind farms relate to the atmosphere: the "wake effect" (the wind speed reduction behind wind turbines) can induce a change of air temperature and sea surface pressure up to 15 km away from the wind farms Hasager et al. (2013) causing local climates variations and cloudiness. ...
Can satellite data be used to address challenges currently faced by the Offshore Renewable Energy (ORE) sector? What benefit can satellite observations bring to resource assessment and maintenance of ORE farms? Can satellite observations be used to assess the environmental impact of offshore renewables leading towards a more sustainable ORE sector? This review paper faces these questions presenting a holistic view of the current interactions between satellite and ORE sectors, and future needs to make this partnerships grow. The aim of the work is to start the conversation between these sectors by establishing a common ground. We present offshore needs and satellite technology limitations, as well as potential opportunities and areas of growth. To better understand this, the reader is guided through the history, current developments, challenges and future of offshore wind, tidal and wave energy technologies. Then, an overview on satellite observations for ocean applications is given, covering types of instruments and how they are used to provide different metocean variables, satellite performance, and data processing and integration. Past, present and future satellite missions are also discussed. Finally, the paper focuses on innovation opportunities and the potential of synergies between the ORE and satellite sectors. Specifically, we pay attention to improvements that satellite observations could bring to standard measurement techniques: assessing uncertainty, wind, tidal and wave conditions forecast, as well as environmental monitoring from space. Satellite-enabled measurement of ocean physical processes and applications for fisheries, mammals and birds, and habitat change, are also discussed in depth.
