Articles | Volume 6, issue 2
https://doi.org/10.5194/wes-6-521-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-6-521-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Offshore wind farm global blockage measured with scanning lidar
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Frauke Theuer
CORRESPONDING AUTHOR
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Andreas Rott
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Dörenkämper
Fraunhofer Institute for Wind Energy Systems, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Kühn
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Related authors
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.
Arjun Anantharaman, Jörge Schneemann, Frauke Theuer, Laurent Beaudet, Valentin Bernard, Paul Deglaire, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-20, https://doi.org/10.5194/wes-2025-20, 2025
Revised manuscript accepted for WES
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 kilometers downstream. We found a 2.5 % increase in the turbine loads and discuss how further measurements could add to the design standards of future wind farms.
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.
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.
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.
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
Preprint 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.
Johanna Borowski, Sandra Schwegmann, Kerstin Avila, and Martin Dörenkämper
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-117, https://doi.org/10.5194/wes-2025-117, 2025
Preprint under review for WES
Short summary
Short summary
Assessing the wind resource and mitigating its associated uncertainties are crucial to wind farm profitability. The study quantifies the uncertainty due to inter-annual variability, averaging 6.5 % and ranging from 1 % to 14 %, using long-term, quality-controlled wind measurements from tall met masts in terrain of varying complexity. Further, the results indicate that machine learning models are beneficial to mitigate the impact of inter-annual variability in heterogeneous and complex terrain.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
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.
Arjun Anantharaman, Jörge Schneemann, Frauke Theuer, Laurent Beaudet, Valentin Bernard, Paul Deglaire, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-20, https://doi.org/10.5194/wes-2025-20, 2025
Revised manuscript accepted for WES
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 kilometers downstream. We found a 2.5 % increase in the turbine loads and discuss how further measurements could add to the design standards of future wind farms.
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 under review 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.
Manuel Alejandro Zúñiga Inestroza, Paul Hulsman, Vlaho Petrović, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-171, https://doi.org/10.5194/wes-2024-171, 2025
Revised manuscript accepted for WES
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.
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.
Lukas Vollmer, Balthazar Arnoldus Maria Sengers, and Martin Dörenkämper
Wind Energ. Sci., 9, 1689–1693, https://doi.org/10.5194/wes-9-1689-2024, https://doi.org/10.5194/wes-9-1689-2024, 2024
Short summary
Short summary
This study proposes a modification to a well-established wind farm parameterization used in mesoscale models. The wind speed at the location of the turbine, which is used to calculate power and thrust, is corrected to approximate the free wind speed. Results show that the modified parameterization produces more accurate estimates of the turbine’s power curve.
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.
Hugo Rubio, Daniel Hatfield, Charlotte Bay Hasager, Martin Kühn, and Julia Gottschall
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-11, https://doi.org/10.5194/amt-2024-11, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Unlocking offshore wind farms’ potential demands a precise understanding of available wind resources. Yet, limited in situ data in marine environments call for innovative solutions. This study delves into the world of satellite remote sensing and numerical models, exploring their capabilities and challenges in characterizing offshore wind dynamics. This investigation evaluates these tools against measurements from a floating ship-based lidar, collected through a novel campaign in the Baltic Sea.
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.
Markus Sommerfeld, Martin Dörenkämper, Jochem De Schutter, and Curran Crawford
Wind Energ. Sci., 8, 1153–1178, https://doi.org/10.5194/wes-8-1153-2023, https://doi.org/10.5194/wes-8-1153-2023, 2023
Short summary
Short summary
This study investigates the performance of pumping-mode ground-generation airborne wind energy systems by determining power-optimal flight trajectories based on realistic, k-means clustered, vertical wind velocity profiles. These profiles, derived from mesoscale weather simulations at an offshore and an onshore site in Europe, are incorporated into an optimal control model that maximizes average cycle power by optimizing the kite's trajectory.
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.
Anna von Brandis, Gabriele Centurelli, Jonas Schmidt, Lukas Vollmer, Bughsin' Djath, and Martin Dörenkämper
Wind Energ. Sci., 8, 589–606, https://doi.org/10.5194/wes-8-589-2023, https://doi.org/10.5194/wes-8-589-2023, 2023
Short summary
Short summary
We propose that considering large-scale wind direction changes in the computation of wind farm cluster wakes is of high relevance. Consequently, we present a new solution for engineering modeling tools that accounts for the effect of such changes in the propagation of wakes. The new model is evaluated with satellite data in the German Bight area. It has the potential to reduce uncertainty in applications such as site assessment and short-term power forecasting.
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.
Markus Sommerfeld, Martin Dörenkämper, Jochem De Schutter, and Curran Crawford
Wind Energ. Sci., 7, 1847–1868, https://doi.org/10.5194/wes-7-1847-2022, https://doi.org/10.5194/wes-7-1847-2022, 2022
Short summary
Short summary
This research explores the ground-generation airborne wind energy system (AWES) design space and investigates scaling effects by varying design parameters such as aircraft wing size, aerodynamic efficiency and mass. Therefore, representative simulated onshore and offshore wind data are implemented into an AWES trajectory optimization model. We estimate optimal annual energy production and capacity factors as well as a minimal operational lift-to-weight ratio.
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.
Beatriz Cañadillas, Maximilian Beckenbauer, Juan J. Trujillo, Martin Dörenkämper, Richard Foreman, Thomas Neumann, and Astrid Lampert
Wind Energ. Sci., 7, 1241–1262, https://doi.org/10.5194/wes-7-1241-2022, https://doi.org/10.5194/wes-7-1241-2022, 2022
Short summary
Short summary
Scanning lidar measurements combined with meteorological sensors and mesoscale simulations reveal the strong directional and stability dependence of the wake strength in the direct vicinity of wind farm clusters.
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.
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.
Julia Gottschall and Martin Dörenkämper
Wind Energ. Sci., 6, 505–520, https://doi.org/10.5194/wes-6-505-2021, https://doi.org/10.5194/wes-6-505-2021, 2021
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.
Frauke Theuer, Marijn Floris van Dooren, Lueder von Bremen, and Martin Kühn
Wind Energ. Sci., 5, 1449–1468, https://doi.org/10.5194/wes-5-1449-2020, https://doi.org/10.5194/wes-5-1449-2020, 2020
Short summary
Short summary
Very short-term wind power forecasts are gaining increasing importance with the rising share of renewables in today's energy system. In this work, we developed a methodology to forecast wind power of offshore wind turbines on minute scales utilising long-range single-Doppler lidar measurements. The model was able to outperform persistence during unstable stratification in terms of deterministic and probabilistic scores, while it showed large shortcomings for stable atmospheric conditions.
Andrea N. Hahmann, Tija Sīle, Björn Witha, Neil N. Davis, Martin Dörenkämper, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Bjarke T. Olsen, and Stefan Söderberg
Geosci. Model Dev., 13, 5053–5078, https://doi.org/10.5194/gmd-13-5053-2020, https://doi.org/10.5194/gmd-13-5053-2020, 2020
Short summary
Short summary
Wind energy resource assessment routinely uses numerical weather prediction model output. We describe the evaluation procedures used for picking the suitable blend of model setup and parameterizations for simulating European wind climatology with the WRF model. We assess the simulated winds against tall mast measurements using a suite of metrics, including the Earth Mover's Distance, which diagnoses the performance of each ensemble member using the full wind speed and direction distribution.
Martin Dörenkämper, Bjarke T. Olsen, Björn Witha, Andrea N. Hahmann, Neil N. Davis, Jordi Barcons, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Mariano Sastre-Marugán, Tija Sīle, Wilke Trei, Mark Žagar, Jake Badger, Julia Gottschall, Javier Sanz Rodrigo, and Jakob Mann
Geosci. Model Dev., 13, 5079–5102, https://doi.org/10.5194/gmd-13-5079-2020, https://doi.org/10.5194/gmd-13-5079-2020, 2020
Short summary
Short summary
This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulations and the microscale downscaling for generating the climatology. A comprehensive evaluation of each component of the NEWA model chain is presented using observations from a large set of tall masts located all over Europe.
Cited articles
Allaerts, D. and Meyers, J.:
Gravity Waves and Wind-Farm Efficiency in Neutral and Stable Conditions,
Bound.-Lay. Meteorol.,
166, 269–299, https://doi.org/10.1007/s10546-017-0307-5, 2017. a
Bell, T. M., Klein, P., Wildmann, N., and Menke, R.: Analysis of flow in complex terrain using multi-Doppler lidar retrievals, Atmos. Meas. Tech., 13, 1357–1371, https://doi.org/10.5194/amt-13-1357-2020, 2020. a
Bleeg, J.:
A Graph Neural Network Surrogate Model for the Prediction of Turbine Interaction Loss,
J. Phys. Conf. Ser.,
1618, 062054, https://doi.org/10.1088/1742-6596/1618/6/062054, 2020. a
Branlard, E. and Meyer Forsting, A. R.:
Assessing the blockage effect of wind turbines and wind farms using an analytical vortex model,
Wind Energy, 23, 2068–2086, https://doi.org/10.1002/we.2546, 2020. a, b
Branlard, E., Quon, E., Meyer Forsting, A. R., King, J., and Moriarty, P.:
Wind farm blockage effects: comparison of different engineering models,
J. Phys. Conf. Ser.,
1618, 062036, https://doi.org/10.1088/1742-6596/1618/6/062036, 2020. a, b
Copernicus marine service: Copernicus Marine environment monitoring service, available at: http://marine.copernicus.eu/, last access: 28 March 2021. a
Dyer, A. J.:
A review of flux-profile relationships,
Bound.-Lay. Meteorol.,
7, 363–372, https://doi.org/10.1007/BF00240838, 1974. a
Emeis, S.:
Wind Energy Meteorology, 2nd edition, Springer International Publishing AG, https://doi.org/10.1007/978-3-319-72859-9, 2018. a
EnBW:
EnBW Hohe See and Albatros wind farms, The construction diary for Hohe See, online, available at: https://www.enbw.com/renewable-energy/wind-energy/our-offshore-wind-farms/hohe-see/construction-diary.html (last access 28 March 2021), 2019. a
Global Tech I Offshore Wind GmbH:
Global Tech I, online,
available at: https://globaltechone.de/power/ (last access: 5 January 2021), 2021. a
Good, S., Fiedler, E., Mao, C., Martin, M. J., Maycock, A., Reid, R., Roberts-Jones, J., Searle, T., Waters, J., While, J., and Worsfold, M.:
The Current Configuration of the OSTIA System for Operational Production of Foundation Sea Surface Temperature and Ice Concentration Analyses,
Remote Sens.-Basel,
12, 720, https://doi.org/10.3390/rs12040720, 2020. a
Hasager, C. and Sjöholm, M.:
Editorial for the Special Issue “Remote Sensing of Atmospheric Conditions for Wind Energy Applications”,
Remote Sens.-Basel,
11, 781, https://doi.org/10.3390/rs11070781, 2019. a
Högström, U.:
Non-Dimensional Wind and Temperature Profiles in the Atmospheric Surface Layer: A Re-Evaluation,
Bound.-Lay. Meteorol.,
42, 55–78, https://doi.org/10.1007/BF00119875, 1988. a
IEC:
IEC 61400-12 Wind turbine generator systems – Part 12: Wind turbine power performance testing, International Electrotechnical Commission, Geneva, Switzerland, 2017. a
Kitaigorodskii, S. A. and Joffre, S. M.:
In search of a simple scaling for the height of the stratified atmospheric boundary layer,
Tellus A,
40, 419–433, https://doi.org/10.3402/tellusa.v40i5.11812, 1988. a
Käsler, Y., Rahm, S., Simmet, R., and Kühn, M.:
Wake Measurements of a Multi-MW Wind Turbine with Coherent Long-Range Pulsed Doppler Wind Lidar,
J. Atmos. Ocean. Tech.,
27, 1529–1532, https://doi.org/10.1175/2010JTECHA1483.1, 2010. a
McKillup, S.:
Statistics Explained: An Introductory Guide for Life Scientists, chap. 6 – Working from samples – data, populations and statistics, Cambridge University Press, https://doi.org/10.1017/CBO9780511815935, pp. 57–76, 2005. a
Menke, R., Vasiljević, N., Wagner, J., Oncley, S. P., and Mann, J.: Multi-lidar wind resource mapping in complex terrain, Wind Energ. Sci., 5, 1059–1073, https://doi.org/10.5194/wes-5-1059-2020, 2020. a
Meyer Forsting, A. R., Troldborg, N., and Gaunaa, M.:
The flow upstream of a row of aligned wind turbine rotors and its effect on power production,
Wind Energy,
20, 63–77, https://doi.org/10.1002/we.1991, 2016. a
Meyer Forsting, A. R., Troldborg, N., Bechmann, A., and Réthoré, P.-E.:
Modelling Wind Turbine Inflow: The Induction Zone,
PhD thesis,
DTU Wind Energy, https://doi.org/10.11581/DTU:00000022, 2017. a
Møller, M., Domagalski, P., and Sætran, L. R.: Comparing abnormalities in onshore and offshore vertical wind profiles, Wind Energ. Sci., 5, 391–411, https://doi.org/10.5194/wes-5-391-2020, 2020. a
Nygaard, N. G. and Newcombe, A. C.:
Wake behind an offshore wind farm observed with dual-Doppler radars,
J. Phys. Conf. Ser.,
1037, 072008, https://doi.org/10.1088/1742-6596/1037/7/072008, 2018. a, b
Nygaard, N. G., Steen, S. T., Poulsen, L., and Pedersen, J. G.:
Modelling cluster wakes and wind farm blockage,
J. Phys. Conf. Ser.,
1618, 062072, https://doi.org/10.1088/1742-6596/1618/6/062072, 2020. a
OpenStreetMap Foundation on behalf of the community: OpenStreetMap, available at: https://www.openstreetmap.org/, last access: 28 March 2021. a
Ørsted A/S:
Ørsted presents update on its long-term financial targets, online, available at: https://orsted.com/en/Company-Announcement-List/2019/10/1937002/ (last access: 28 March 2021), 2019. a
Peña, A., Gryning, S.-E., and Hasager, C. B.:
Measurements and Modellin of the Wind Speed Profile in the Marine Atmospheric Boundary Layer,
Bound.-Lay. Meteorol.,
129, 479–495, https://doi.org/10.1007/s10546-008-9323-9, 2008. a
Porté-Agel, F., Bastankhah, M., and Shamsoddin, S.:
Wind-Turbine and Wind-Farm Flows: A Review,
Bound.-Lay. Meteorol.,
174, 1–59, https://doi.org/10.1007/s10546-019-00473-0, 2019. a, b, c, d
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, 012044, https://doi.org/10.1088/1742-6596/625/1/012044, 2015. a
Rohrig, K., Berkhout, V., Callies, D., Durstewitz, M., Faulstich, S., Hahn, B., Jung, M., Pauscher, L., Seibel, A., Shan, M., Siefert, M., Steffen, J., Collmann, M., Czichon, S., Dörenkämper, M., Gottschall, J., Lange, B., Ruhle, A., Sayer, F., Stoevesandt, B., and Wenske, J.:
Powering the 21st century by wind energy—Options, facts, figures,
Appl. Phys. Rev.,
6, 031303, https://doi.org/10.1063/1.5089877, 2019. a
Rott, A., Schneemann, J., Trabucchi, D., Trujillo, J. J., and Kühn, M.:
Accurate deployment of long range scanning lidar on offshore platforms by means of sea surface leveling,
in: Poster presentation NAWEA Windtech, Windtech 2017 – International Conference on Future Technologies for Wind Energy, Boulder, Colorado, USA, 24–26 October 2017. a, b
Schneemann, J., Voß, S., Rott, A., and Kühn, M.:
Doppler wind lidar plan position indicator scans and atmospheric measurements at the offshore wind farm “Global Tech I”, PANGAEA – Data Publisher for Earth & Environmental Science, https://doi.org/10.1594/PANGAEA.909721, 2019. a
Segalini, A. and Dahlberg, J.-Å.:
Blockage effects in wind farms,
Wind Energy,
23, 120–128, https://doi.org/10.1002/we.2413, 2019. a, b
Smith, S. D.:
Wind Stress and Heat Flux over the Ocean in Gale Force Winds,
J. Phys. Oceanogr.,
10, 709–726, https://doi.org/10.1175/1520-0485(1980)010<0709:WSAHFO>2.0.CO;2, 1980. a
Stawiarski, C., Träumner, K., Knigge, C., and Calhoun, R.:
Scopes and Challenges of Dual-Doppler Lidar Wind Measurements—An Error Analysis,
J. Atmos. Ocean. Tech.,
30, 2044 – 2062, https://doi.org/10.1175/JTECH-D-12-00244.1, 2013. a
Stull, R. B. (ed.):
An Introduction to Boundary Layer Meteorology, Kluwer Academic Publishers,
Dordrecht, The Netherlands, https://doi.org/10.1007/978-94-009-3027-8, 1988. a
Theuer, F., van Dooren, M. F., von Bremen, L., and Kühn, M.:
On the accuracy of a logarithmic extrapolation of the wind speed measured by horizontal lidar scans,
J. Phys. Conf. Ser.,
1618, 032043, https://doi.org/10.1088/1742-6596/1618/3/032043, 2020a. a, b, c, d
Theuer, F., van Dooren, M. F., von Bremen, L., and Kühn, M.: Minute-scale power forecast of offshore wind turbines using long-range single-Doppler lidar measurements, Wind Energ. Sci., 5, 1449–1468, https://doi.org/10.5194/wes-5-1449-2020, 2020b. a, b, c
Trabucchi, D., Trujillo, J. J., Schneemann, J., Bitter, M., and Kühn, M.:
Application of staring lidars to study the dynamics of wind turbine wakes,
Meteorol. Z.,
24, 557–564, https://doi.org/10.1127/metz/2014/0610, 2014. a
van Dooren, M., Trabucchi, D., and Kühn, M.:
A Methodology for the Reconstruction of 2D Horizontal Wind Fields of Wind Turbine Wakes Based on Dual-Doppler Lidar Measurements,
Remote Sens.-Basel,
8, 809, https://doi.org/10.3390/rs8100809, 2016. a
Werner, C.:
Doppler Wind Lidar,
in: Lidar,
edited by: Weitkamp, C.,
vol. 102 of Springer Series in Optical Sciences,
Springer-Verlag, New York, NY, https://doi.org/10.1007/0-387-25101-4_12, pp. 325–354, 2005. a
Wu, K. and Porté-Agel, F.:
Flow Adjustment Inside and Around Large Finite-Size Wind Farms,
Energies,
10, 2164, https://doi.org/10.3390/en10122164, 2017. a, b
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.
A wind farm can reduce the wind speed in front of it just by its presence and thus also slightly...
Altmetrics
Final-revised paper
Preprint