Articles | Volume 2, issue 2
https://doi.org/10.5194/wes-2-477-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/wes-2-477-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
18 Oct 2017
Research article |
| 18 Oct 2017
An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects
Niko Mittelmeier
CORRESPONDING AUTHOR
Senvion GmbH, Überseering 10, 22297 Hamburg, Germany
Julian Allin
Senvion GmbH, Überseering 10, 22297 Hamburg, Germany
Tomas Blodau
Senvion GmbH, Überseering 10, 22297 Hamburg, Germany
Davide Trabucchi
ForWind – University of Oldenburg, Institute of Physics,
Küpkersweg 70, 26129 Oldenburg, Germany
Gerald Steinfeld
ForWind – University of Oldenburg, Institute of Physics,
Küpkersweg 70, 26129 Oldenburg, Germany
Andreas Rott
ForWind – University of Oldenburg, Institute of Physics,
Küpkersweg 70, 26129 Oldenburg, Germany
Martin Kühn
ForWind – University of Oldenburg, Institute of Physics,
Küpkersweg 70, 26129 Oldenburg, Germany
Related authors
No articles found.
Manuel Alejandro Zúñiga Inestroza, Paul Hulsman, Vlaho Petrović, and Martin Kühn
Wind Energ. Sci., 10, 2257–2278, https://doi.org/10.5194/wes-10-2257-2025, https://doi.org/10.5194/wes-10-2257-2025, 2025
Short summary
Short summary
Wake effects cause power losses that degrade wind farm efficiency. This paper presents a wind tunnel investigation of dynamic induction control (DIC), a strategy to mitigate wake losses by improving turbine–flow interactions. WindScanner lidar measurements are used to explore the wake development of model turbines in response to DIC. Our results demonstrate consistent benefits and adaptability under realistic inflow conditions, highlighting DIC’s potential to increase wind farm power production.
Hugo Rubio, Daniel Hatfield, Charlotte Bay Hasager, Martin Kühn, and Julia Gottschall
Atmos. Meas. Tech., 18, 4949–4968, https://doi.org/10.5194/amt-18-4949-2025, https://doi.org/10.5194/amt-18-4949-2025, 2025
Short summary
Short summary
Due to the scarcity of offshore in situ observations, alternative data sources are essential for a reliable understanding of offshore winds. Therefore, this study delves into the world of satellite remote sensing (ASCAT) and numerical models (ERA5), exploring their capabilities and limitations in characterising offshore winds. This investigation evaluates these two datasets against measurements from a floating ship-based lidar, collected during a novel measurement campaign in the Baltic Sea.
Arjun Anantharaman, Jörge Schneemann, Frauke Theuer, Laurent Beaudet, Valentin Bernard, Paul Deglaire, and Martin Kühn
Wind Energ. Sci., 10, 1849–1867, https://doi.org/10.5194/wes-10-1849-2025, https://doi.org/10.5194/wes-10-1849-2025, 2025
Short summary
Short summary
The offshore wind farm sector is expanding rapidly, and the interactions between wind farms are important to analyse for both existing and planned wind farms. We developed a new methodology to quantify how much the reductions in wind speed behind a farm can affect the loads on turbines which are tens of kilometres downstream. We find a 2.5 % increase in the turbine loads and discuss how further measurements could add to the design standards of future wind farms.
Daniel Ribnitzky, Vlaho Petrovic, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-143, https://doi.org/10.5194/wes-2025-143, 2025
Revised manuscript under review for WES
Short summary
Short summary
We developed controllers for the Hybrid-Lambda Rotor, which enables two operating modes below rated power via different tip speed ratios, balancing load reduction and power output. A baseline controller with a model-based wind speed estimator, a load feedback controller and an inflow feed-forward controller were implemented on the MoWiTO 1.8 model turbine and tested in wind tunnel experiments. In depth scaling considerations ensure the transferability of the results to the full-scale model.
Johannes Paulsen, Jörge Schneemann, Gerald Steinfeld, Frauke Theuer, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-118, https://doi.org/10.5194/wes-2025-118, 2025
Preprint under review for WES
Short summary
Short summary
While Low-Level Jets (LLJs) have been well-characterized, their impact on offshore wind farms is not well understood. This study uses multi-elevation lidar scans to derive vertical wind profiles up to 350 m and detect LLJs in up to 22.6 % of available measurements. Further, we analyze their effect on power production using operational wind farm data, observing a slightly negative influence and increased power fluctuations during LLJ events.
Daniel Ribnitzky, Vlaho Petrović, and Martin Kühn
Wind Energ. Sci., 10, 1329–1349, https://doi.org/10.5194/wes-10-1329-2025, https://doi.org/10.5194/wes-10-1329-2025, 2025
Short summary
Short summary
In this paper, the Hybrid-Lambda Rotor is scaled to wind tunnel size and validated in wind tunnel experiments. The objectives are to derive a scaling methodology, to investigate the influence of the steep gradients of axial induction along the blade span, and to characterize the near wake. The study reveals complex three-dimensional flow patterns for blade designs with non-uniform loading, and it can offer new inspirations when solving other scaling problems for complex wind turbine systems.
David Onnen, Gunner Christian Larsen, Alan Wai Hou Lio, Paul Hulsman, Martin Kühn, and Vlaho Petrović
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-188, https://doi.org/10.5194/wes-2024-188, 2025
Revised manuscript accepted for WES
Short summary
Short summary
Neighbouring wind turbines influence each other, as they leave a complex footprint of reduced wind speed and changed turbulence in the flow, called wake. Modern wind farm control sees the turbines as team players and aims to mitigate the negative effects of such interaction. To do so, the exact flow situation in the wind farm must be known. We show, how to use wind turbines as sensors for waked inflow, test this in the field and compare with independent laser measurements of the flow field.
Frauke Theuer, Janna Kristina Seifert, Jörge Schneemann, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-141, https://doi.org/10.5194/wes-2024-141, 2024
Preprint under review for WES
Short summary
Short summary
To be useful for end-users the forecast horizon of lidar-based minute-scale forecasts needs to be extended to at least 15 minutes. In this work, we adapt a lidar-based forecasting methodology to predict wind speed and power with horizons of up to 30 minutes. We found that the skill of the lidar-based approach highly depends on atmospheric conditions and the forecast characteristics. It was able to outperform persistence up to a 16 minute forecast horizon during unstable conditions.
Sonja Steinbrück, Thorben Eilers, Lukas Vollmer, Kerstin Avila, and Gerald Steinfeld
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-146, https://doi.org/10.5194/wes-2024-146, 2024
Preprint withdrawn
Short summary
Short summary
This paper introduces an enhanced coupling between the LES code PALM and the aeroelastic code FAST, enabling detailed turbine output in temporally and spatially heterogeneous atmospheric flows while maintaining computational efficiency. A wind speed correction is added to reduce errors from force smearing on the numerical grid. Results were evaluated through comparisons between different model setups and turbine measurements, including assessments in a two-turbine wake situation.
Anantha Padmanabhan Kidambi Sekar, Paul Hulsman, Marijn Floris van Dooren, and Martin Kühn
Wind Energ. Sci., 9, 1483–1505, https://doi.org/10.5194/wes-9-1483-2024, https://doi.org/10.5194/wes-9-1483-2024, 2024
Short summary
Short summary
We present induction zone measurements conducted with two synchronised lidars at a two-turbine wind farm. The induction zone flow was characterised for free, fully waked and partially waked flows. Due to the short turbine spacing, the lidars captured the interaction of the atmospheric boundary layer, induction zone and wake, evidenced by induction asymmetry and induction zone–wake interactions. The measurements will aid the process of further improving existing inflow and wake models.
Daniel Ribnitzky, Frederik Berger, Vlaho Petrović, and Martin Kühn
Wind Energ. Sci., 9, 359–383, https://doi.org/10.5194/wes-9-359-2024, https://doi.org/10.5194/wes-9-359-2024, 2024
Short summary
Short summary
This paper provides an innovative blade design methodology for offshore wind turbines with very large rotors compared to their rated power, which are tailored for an increased power feed-in at low wind speeds. Rather than designing the blade for a single optimized operational point, we include the application of peak shaving in the design process and introduce a design for two tip speed ratios. We describe how enlargement of the rotor diameter can be realized to improve the value of wind power.
Andreas Rott, Leo Höning, Paul Hulsman, Laura J. Lukassen, Christof Moldenhauer, and Martin Kühn
Wind Energ. Sci., 8, 1755–1770, https://doi.org/10.5194/wes-8-1755-2023, https://doi.org/10.5194/wes-8-1755-2023, 2023
Short summary
Short summary
This study examines wind vane measurements of commercial wind turbines and their impact on yaw control. The authors discovered that rotor interference can cause an overestimation of wind vane measurements, leading to overcorrection of the yaw controller. A correction function that improves the yaw behaviour is presented and validated in free-field experiments on a commercial wind turbine. This work provides new insights into wind direction measurements and suggests ways to optimize yaw control.
Balthazar Arnoldus Maria Sengers, Andreas Rott, Eric Simley, Michael Sinner, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 8, 1693–1710, https://doi.org/10.5194/wes-8-1693-2023, https://doi.org/10.5194/wes-8-1693-2023, 2023
Short summary
Short summary
Unexpected wind direction changes are undesirable, especially when performing wake steering. This study explores whether the yaw controller can benefit from accessing wind direction information before a change reaches the turbine. Results from two models with different fidelities demonstrate that wake steering can indeed benefit from preview information.
Paul Hulsman, Luis A. Martínez-Tossas, Nicholas Hamilton, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-112, https://doi.org/10.5194/wes-2023-112, 2023
Manuscript not accepted for further review
Short summary
Short summary
This paper presents an approach to analytically estimate the wake deficit within the near-wake region by modifying the curled wake model. This is done by incorporating a new initial condition at the rotor using an azimuth-dependent Gaussian profile, an adjusted turbulence model in the near-wake region and the far-wake region and an iterative process to determine the velocity field, while considering the relation of the pressure gradient and accounting the conservation of mass.
Balthazar Arnoldus Maria Sengers, Gerald Steinfeld, Paul Hulsman, and Martin Kühn
Wind Energ. Sci., 8, 747–770, https://doi.org/10.5194/wes-8-747-2023, https://doi.org/10.5194/wes-8-747-2023, 2023
Short summary
Short summary
The optimal misalignment angles for wake steering are determined using wake models. Although mostly analytical, data-driven models have recently shown promising results. This study validates a previously proposed data-driven model with results from a field experiment using lidar measurements. In a comparison with a state-of-the-art analytical model, it shows systematically more accurate estimates of the available power. Also when using only commonly available input data, it gives good results.
Hugo Rubio, Martin Kühn, and Julia Gottschall
Wind Energ. Sci., 7, 2433–2455, https://doi.org/10.5194/wes-7-2433-2022, https://doi.org/10.5194/wes-7-2433-2022, 2022
Short summary
Short summary
A proper development of offshore wind farms requires the accurate description of atmospheric phenomena like low-level jets. In this study, we evaluate the capabilities and limitations of numerical models to characterize the main jets' properties in the southern Baltic Sea. For this, a comparison against ship-mounted lidar measurements from the NEWA Ferry Lidar Experiment has been implemented, allowing the investigation of the model's capabilities under different temporal and spatial constraints.
Frauke Theuer, Andreas Rott, Jörge Schneemann, Lueder von Bremen, and Martin Kühn
Wind Energ. Sci., 7, 2099–2116, https://doi.org/10.5194/wes-7-2099-2022, https://doi.org/10.5194/wes-7-2099-2022, 2022
Short summary
Short summary
Remote-sensing-based approaches have shown potential for minute-scale forecasting and need to be further developed towards an operational use. In this work we extend a lidar-based forecast to an observer-based probabilistic power forecast by combining it with a SCADA-based method. We further aggregate individual turbine power using a copula approach. We found that the observer-based forecast benefits from combining lidar and SCADA data and can outperform persistence for unstable stratification.
Frederik Berger, Lars Neuhaus, David Onnen, Michael Hölling, Gerard Schepers, and Martin Kühn
Wind Energ. Sci., 7, 1827–1846, https://doi.org/10.5194/wes-7-1827-2022, https://doi.org/10.5194/wes-7-1827-2022, 2022
Short summary
Short summary
We proof the dynamic inflow effect due to gusts in wind tunnel experiments with MoWiTO 1.8 in the large wind tunnel of ForWind – University of Oldenburg, where we created coherent gusts with an active grid. The effect is isolated in loads and rotor flow by comparison of a quasi-steady and a dynamic case. The observed effect is not caught by common dynamic inflow engineering models. An improvement to the Øye dynamic inflow model is proposed, matching experiment and corresponding FVWM simulations.
Balthazar Arnoldus Maria Sengers, Matthias Zech, Pim Jacobs, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 7, 1455–1470, https://doi.org/10.5194/wes-7-1455-2022, https://doi.org/10.5194/wes-7-1455-2022, 2022
Short summary
Short summary
Wake steering aims to redirect the wake away from a downstream turbine. This study explores the potential of a data-driven surrogate model whose equations can be interpreted physically. It estimates wake characteristics from measurable input variables by utilizing a simple linear model. The model shows encouraging results in estimating available power in the far wake, with significant improvements over currently used analytical models in conditions where wake steering is deemed most effective.
Marijn Floris van Dooren, Anantha Padmanabhan Kidambi Sekar, Lars Neuhaus, Torben Mikkelsen, Michael Hölling, and Martin Kühn
Atmos. Meas. Tech., 15, 1355–1372, https://doi.org/10.5194/amt-15-1355-2022, https://doi.org/10.5194/amt-15-1355-2022, 2022
Short summary
Short summary
The remote sensing technique lidar is widely used for wind speed measurements for both industrial and academic applications. Lidars can measure wind statistics accurately but cannot fully capture turbulent fluctuations in the high-frequency range, since they are partly filtered out. This paper therefore investigates the turbulence spectrum measured by a continuous-wave lidar and analytically models the lidar's measured spectrum with a Lorentzian filter function and a white noise term.
Sonja Krüger, Gerald Steinfeld, Martin Kraft, and Laura J. Lukassen
Wind Energ. Sci., 7, 323–344, https://doi.org/10.5194/wes-7-323-2022, https://doi.org/10.5194/wes-7-323-2022, 2022
Short summary
Short summary
Detailed numerical simulations of turbines in atmospheric conditions are challenging with regard to their computational demand. We coupled an atmospheric flow model and a turbine model in order to deliver extensive details about the flow and the turbine response within reasonable computational time. A comparison to measurement data was performed and showed a very good agreement. The efficiency of the tool enables applications such as load calculation in wind farms or during low-level-jet events.
Andreas Rott, Jörge Schneemann, Frauke Theuer, Juan José Trujillo Quintero, and Martin Kühn
Wind Energ. Sci., 7, 283–297, https://doi.org/10.5194/wes-7-283-2022, https://doi.org/10.5194/wes-7-283-2022, 2022
Short summary
Short summary
We present three methods that can determine the alignment of a lidar placed on the transition piece of an offshore wind turbine based on measurements with the instrument: a practical implementation of hard targeting for north alignment, a method called sea surface levelling to determine the levelling of the system from water surface measurements, and a model that can determine the dynamic levelling based on the operating status of the wind turbine.
Paul Hulsman, Martin Wosnik, Vlaho Petrović, Michael Hölling, and Martin Kühn
Wind Energ. Sci., 7, 237–257, https://doi.org/10.5194/wes-7-237-2022, https://doi.org/10.5194/wes-7-237-2022, 2022
Short summary
Short summary
Due to the possibility of mapping the wake fast at multiple locations with the WindScanner, a thorough understanding of the development of the wake is acquired at different inflow conditions and operational conditions. The lidar velocity data and the energy dissipation rate compared favourably with hot-wire data from previous experiments, lending credibility to the measurement technique and methodology used here. This will aid the process to further improve existing wake models.
Frederik Berger, David Onnen, Gerard Schepers, and Martin Kühn
Wind Energ. Sci., 6, 1341–1361, https://doi.org/10.5194/wes-6-1341-2021, https://doi.org/10.5194/wes-6-1341-2021, 2021
Short summary
Short summary
Dynamic inflow denotes the unsteady aerodynamic response to fast changes in rotor loading and leads to load overshoots. We performed a pitch step experiment with MoWiTO 1.8 in the large wind tunnel of ForWind – University of Oldenburg. We measured axial and tangential inductions with a recent method with a 2D-LDA system and performed load and wake measurements. These radius-resolved measurements allow for new insights into the dynamic inflow phenomenon.
Janna Kristina Seifert, Martin Kraft, Martin Kühn, and Laura J. Lukassen
Wind Energ. Sci., 6, 997–1014, https://doi.org/10.5194/wes-6-997-2021, https://doi.org/10.5194/wes-6-997-2021, 2021
Short summary
Short summary
Fluctuations in the power output of wind turbines are one of the major challenges in the integration and utilisation of wind energy. By analysing the power output fluctuations of wind turbine pairs in an offshore wind farm, we show that their correlation depends on their location within the wind farm and their inflow. The main outcome is that these correlation dependencies can be characterised by statistics of the power output of the wind turbines and sorted by a clustering algorithm.
Jörge Schneemann, Frauke Theuer, Andreas Rott, Martin Dörenkämper, and Martin Kühn
Wind Energ. Sci., 6, 521–538, https://doi.org/10.5194/wes-6-521-2021, https://doi.org/10.5194/wes-6-521-2021, 2021
Short summary
Short summary
A wind farm can reduce the wind speed in front of it just by its presence and thus also slightly impact the available power. In our study we investigate this so-called global-blockage effect, measuring the inflow of a large offshore wind farm with a laser-based remote sensing method up to several kilometres in front of the farm. Our results show global blockage under a certain atmospheric condition and operational state of the wind farm; during other conditions it is not visible in our data.
Anantha Padmanabhan Kidambi Sekar, Marijn Floris van Dooren, Andreas Rott, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-16, https://doi.org/10.5194/wes-2021-16, 2021
Preprint withdrawn
Short summary
Short summary
Turbine-mounted lidars performing inflow scans can be used to optimise wind turbine performance and extend their lifetime. This paper introduces a new method to extract wind inflow information from a turbine-mounted scanning SpinnerLidar based on Proper Orthogonal Decomposition. This method offers a balance between simple reconstruction methods and complicated physics-based solvers. The results show that the model can be used for lidar assisted control, loads validation and turbulence studies.
Cited articles
Archer, C. L., Colle, B. A., Veron, D. L., Veron, F. and Sienkiewicz, M. J.: On the predominance of unstable atmospheric conditions in the marine boundary layer offshore of the U.S. northeastern coast, J. Geophys. Res.-Atmos., 121, 8869–8885, https://doi.org/10.1002/2016JD024896, 2016.
Beck, H., Trabucchi, D., Bitter, M., and Kühn, M.: The Ainslie Wake Model An Update for Multi Megawatt Turbines based on State-of-the-Art Wake Scanning Techniques, in Proceedings of the European Wind Energy Association, Barcelona, Spain, 10–13 March, 2014.
Dörenkämper, M.: An investigation of the atmospheric influence on spatial and temporal power fluctuations in offshore wind farms, PhD Thesis, University of Oldenburg, Oldenburg, 2015.
Dörenkämper, M., Tambke, J., Steinfeld, G., Heinemann, D., and Kühn, M.: Influence of marine boundary layer characteristics on power curves of multi megawatt offshore wind turbines, Proceedings of 11th German Wind Energy Conference, Bremen, Germany, 7–8 November, 2012.
Dörenkämper, M., Tambke, J., Steinfeld, G., Heinemann, D., and Kühn, M.: Atmospheric Impacts on Power Curves of Multi-Megawatt Offshore Wind Turbines, J. Phys. Conf. Ser., 555, 12029, https://doi.org/10.1088/1742-6596/555/1/012029, 2014.
Göçmen, T. and Giebel, G.: Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms, Renew. Energy, 99, 524–532, https://doi.org/10.1016/j.renene.2016.07.038, 2016.
Hamilton, N.: Functions Relating to the Smoothing of Numerical Data, CRAN R, 1–5, 2015.
Hansen, K. S., Barthelmie, R. J., Jensen, L. E., and Sommer, A.: The impact of turbulence intensity and atmospheric stability on power deficits due to wind turbine wakes at Horns Rev wind farm, Wind Energy, 15, 183–196, https://doi.org/10.1002/we.512, 2012.
Iungo, G. V. and Porté-Agel, F.: Volumetric scans of wind turbine wakes performed with three simultaneous wind LiDARs under different atmospheric stability regimes, J. Phys. Conf. Ser., 524, 12164, https://doi.org/10.1088/1742-6596/524/1/012164, 2014.
Keane, A., Aguirre, P. E. O., Ferchland, H., Clive, P., and Gallacher, D.: An analytical model for a full wind turbine wake, J. Phys. Conf. Ser., 753, 32039, https://doi.org/10.1088/1742-6596/753/3/032039, 2016.
Mittelmeier, N., Blodau, T., and Kühn, M.: Monitoring offshore wind farm power performance with SCADA data and an advanced wake model, Wind Energ. Sci., 2, 175–187, https://doi.org/10.5194/wes-2-175-2017, 2017.
Monin, A. S. and Obukhov, A. M.: Basic laws of turbulent mixing in the surface layer of the atmosphere, Inst. Contract Number, 24(19604), 163–187, available at: http://mcnaughty.com/keith/papers/Monin_and_Obukhov_1954.pdf (last access: 21 May 2017), 1954.
More, G. and Gallacher, D.: Lidar Measurements and Visualisation of Turbulence and Wake Decay Length, Proceedings of the European Wind Energy Association, Barcelona, Spain, 10–13 March, 2014.
Mortensen, N. G., Nielsen, M., and Ejsing Jørgensen, H.: Offshore CREYAP Part 2 – final results, European Wind Energy Association (EWEA), Helsinki, Finland, 2 Juni 2015, 2015.
Ott, S. and Nielsen, M.: Developments of the offshore wind turbine wake model Fuga, E-0046 Report 2014, DTU Wind Energy, Lyngby, Denmark, 2014.
Özdemir, H., Versteeg, M. C., and Brand, A. J.: Improvements in ECN Wake Model, in Proceedings of the ICOWES2013 Conference, Lyngby, Denmark, 17–19 June, 2013.
R_Core_Team: R: A Language and Environment for Statistical Computing, available at: https://www.r-project.org/, R 3.3.1 ( last access: June, 2016), 2015.
Rajewski, D. A., Takle, E. S., Lundquist, J. K., Oncley, S., Prueger, J. H., Horst, T. W., Rhodes, M. E., Pfeiffer, R., Hatfield, J. L., Spoth, K. K., Doorenbos, R. K., Rajewski, D. A., Takle, E. S., Lundquist, J. K., Oncley, S., Prueger, J. H., Horst, T. W., Rhodes, M. E., Pfeiffer, R., Hatfield, J. L., Spoth, K. K., and Doorenbos, R. K.: Crop Wind Energy Experiment (CWEX): Observations of Surface-Layer, Boundary Layer, and Mesoscale Interactions with a Wind Farm, B. Am. Meteorol. Soc., 94, 655–672, https://doi.org/10.1175/BAMS-D-11-00240.1, 2013.
Sanz Rodrigo, J., Cantero, E., García, B., Borbón, F., Irigoyen, U., Lozano, S., Fernande, P. M., Chávez, R. a, Rodrigo, J. S., Cantero, E., García, B., Borbón, F., Irigoyen, U., Lozano, S., Fernande, P. M., and Chávez, R. a: Atmospheric stability assessment for the characterization of offshore wind conditions, J. Phys. Conf. Ser., 625, 12044, https://doi.org/10.1088/1742-6596/625/1/012044, 2015.
Schneemann, J., Trabucchi, D., Trujillo, J. J., and Voß, S.: Long range scanning lidar measurement campaign report, ClusterDesign Deliverable 7.1, ClusterDesign, Project No. 283145 (FP7 Energy), 2016.
Tambke, J., Claveri, L., Bye, J. A. T., Poppinga, C., Lange, B., von Bremen, L., and Wolff, J.-O.: Marine Meteorology for Multi-Mega-Watt Turbines, Proceedings of Copenhagen Offshore Wind, Copenhagen, Denmark, 2005.
Tuerk, M.: Ermittlung designrelevanter Belastungsparameter für Offshore-Windkraftanlagen, PhD Thesis, Universität zu Köln, 2008.
Türk, M. and Emeis, S.: The dependence of offshore turbulence intensity on wind speed, J. Wind Eng. Ind. Aerodyn., 98, 466–471, https://doi.org/10.1016/j.jweia.2010.02.005, 2010.
Vollmer, L., Steinfeld, G., Heinemann, D., and Kühn, M.: Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study, Wind Energ. Sci., 1, 129–141, https://doi.org/10.5194/wes-1-129-2016, 2016.
Westerhellweg, A., Cañadillas, B., Kinder, F., and Neumann, T.: Wake Measurements at alpha ventus – Dependence on Stability and Turbulence Intensity, J. Phys. Conf. Ser., 555, 12106, https://doi.org/10.1088/1742-6596/555/1/012106, 2014.
Short summary
Stability classification is usually based on measurements from met masts, buoys or lidars. The objective of this paper is to find a classification for stability based on wind turbine supervisory control and data acquisition measurements in order to fit engineering wake models better to the current ambient conditions. The proposed signal is very sensitive to increased turbulence. It allows us to distinguish between conditions with different magnitudes of wake effects.
Stability classification is usually based on measurements from met masts, buoys or lidars. The...
Special issue
Altmetrics
Final-revised paper
Preprint