Articles | Volume 9, issue 6
https://doi.org/10.5194/wes-9-1381-2024
© Author(s) 2024. 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-9-1381-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jun 2024
Research article |
| 25 Jun 2024
| 25 Jun 2024
Simulating low-frequency wind fluctuations
Department of Wind and Energy Systems, Technical University of Denmark, 4000 Roskilde, Denmark
Jakob Mann
Department of Wind and Energy Systems, Technical University of Denmark, 4000 Roskilde, Denmark
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Wind Energ. Sci., 8, 125–139, https://doi.org/10.5194/wes-8-125-2023, https://doi.org/10.5194/wes-8-125-2023, 2023
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Wind turbines extract energy from the incoming wind flow, which needs to be recovered. In very large offshore wind farms, the energy is recovered mostly from above the wind farm in a process called entrainment. In this study, we analyzed the effect of atmospheric stability on the entrainment process in large offshore wind farms using measurements recorded by a research aircraft. This is the first time that in situ measurements are used to study the energy recovery process above wind farms.
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This research investigates a novel method for directly estimating wind velocity variances from averaged Doppler spectra in the frequency domain. Compared to the conventional time-domain approach, the proposed method offers a substantial improvement. Despite some limitations, this study marks a significant advancement in turbulence estimation using pulsed Doppler lidars, which presents promising potential for wind turbine load assessments.
Isadora L. Coimbra, Jakob Mann, José M. L. M. Palma, and Vasco T. P. Batista
Atmos. Meas. Tech., 18, 287–303, https://doi.org/10.5194/amt-18-287-2025, https://doi.org/10.5194/amt-18-287-2025, 2025
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Dual-lidar measurements are explored here as a cost-effective alternative for measuring the wind at great heights. From measurements at a mountainous site, we showed that this methodology can accurately capture mean wind speeds and turbulence under different flow conditions, and we recommended optimal lidar placement and sampling rates. This methodology allows the construction of vertical wind profiles up to 430 m, surpassing traditional meteorological mast heights and single-lidar capabilities.
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024, https://doi.org/10.5194/amt-17-2721-2024, 2024
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Three-dimensional wind fields can be accurately measured by sonic anemometers. However, the traditional mast-mounted sonic anemometers are not flexible in various applications, which can be potentially overcome by drones. Therefore, we conducted a proof-of-concept study by applying three continuous-wave Doppler lidars to characterize the complex flow around a drone to validate the results obtained by CFD simulations. Both methods show good agreement, with a velocity difference of 0.1 m s-1.
Liqin Jin, Jakob Mann, Nikolas Angelou, and Mikael Sjöholm
Atmos. Meas. Tech., 16, 6007–6023, https://doi.org/10.5194/amt-16-6007-2023, https://doi.org/10.5194/amt-16-6007-2023, 2023
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By sampling the spectra from continuous-wave Doppler lidars very fast, the rain-induced Doppler signal can be suppressed and the bias in the wind velocity estimation can be reduced. The method normalizes 3 kHz spectra by their peak values before averaging them down to 50 Hz. Over 3 h, we observe a significant reduction in the bias of the lidar data relative to the reference sonic data when the largest lidar focus distance is used. The more it rains, the more the bias is reduced.
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Wind Energ. Sci., 8, 1511–1531, https://doi.org/10.5194/wes-8-1511-2023, https://doi.org/10.5194/wes-8-1511-2023, 2023
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Atmos. Meas. Tech., 15, 5323–5341, https://doi.org/10.5194/amt-15-5323-2022, https://doi.org/10.5194/amt-15-5323-2022, 2022
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Dominique P. Held and Jakob Mann
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Robert Menke, Nikola Vasiljević, Kurt S. Hansen, Andrea N. Hahmann, and Jakob Mann
Wind Energ. Sci., 3, 681–691, https://doi.org/10.5194/wes-3-681-2018, https://doi.org/10.5194/wes-3-681-2018, 2018
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Jakob Mann, Alfredo Peña, Niels Troldborg, and Søren J. Andersen
Wind Energ. Sci., 3, 293–300, https://doi.org/10.5194/wes-3-293-2018, https://doi.org/10.5194/wes-3-293-2018, 2018
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Turbulence is usually assumed to be unmodified by the stagnation occurring in front of a wind turbine rotor. All manufacturers assume this in their dynamic load calculations. If this assumption is not true it might bias the load calculations and the turbines might not be designed optimally. We investigate the assumption with a Doppler lidar measuring forward from the top of the nacelle and find small but systematic changes in the approaching turbulence that depend on the power curve.
Nikola Vasiljević, José M. L. M. Palma, Nikolas Angelou, José Carlos Matos, Robert Menke, Guillaume Lea, Jakob Mann, Michael Courtney, Luis Frölen Ribeiro, and Vitor M. M. G. C. Gomes
Atmos. Meas. Tech., 10, 3463–3483, https://doi.org/10.5194/amt-10-3463-2017, https://doi.org/10.5194/amt-10-3463-2017, 2017
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In this paper we present a methodology for atmospheric multi-Doppler lidar experiments accompanied with the description and results from the Perdigão-2015 experiment, where the methodology was demonstrated. To our knowledge, this is the first time that steps leading to the acquisition of high-quality datasets from field studies are described and systematically defined and organized.
Alfredo Peña, Jakob Mann, and Nikolay Dimitrov
Wind Energ. Sci., 2, 133–152, https://doi.org/10.5194/wes-2-133-2017, https://doi.org/10.5194/wes-2-133-2017, 2017
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Nacelle lidars are nowadays extensively used to scan the turbine inflow. Thus, it is important to characterize turbulence from their measurements. We present two methods to perform turbulence estimation and demonstrate them using two types of lidars. With one method we can estimate the along-wind unfiltered variance accurately. With the other we can estimate the filtered radial velocity variance accurately and velocity-tensor parameters under neutral and high wind-speed conditions.
Ryan Kilpatrick, Horia Hangan, Kamran Siddiqui, Dan Parvu, Julia Lange, Jakob Mann, and Jacob Berg
Wind Energ. Sci., 1, 237–254, https://doi.org/10.5194/wes-1-237-2016, https://doi.org/10.5194/wes-1-237-2016, 2016
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This paper contributes to the scientific knowledge of flow behaviour over complex topography by extending the physical modelling work of the flow over the Bolund Hill escarpment, a test case for the validation of numerical models in complex terrain for wind resource assessment. The influence of inflow conditions on the flow over the topography has been examined in detail using a large-scale topographic model at high resolution at the unique WindEEE dome wind research facility.
G. A. M. van Kuik, J. Peinke, R. Nijssen, D. Lekou, J. Mann, J. N. Sørensen, C. Ferreira, J. W. van Wingerden, D. Schlipf, P. Gebraad, H. Polinder, A. Abrahamsen, G. J. W. van Bussel, J. D. Sørensen, P. Tavner, C. L. Bottasso, M. Muskulus, D. Matha, H. J. Lindeboom, S. Degraer, O. Kramer, S. Lehnhoff, M. Sonnenschein, P. E. Sørensen, R. W. Künneke, P. E. Morthorst, and K. Skytte
Wind Energ. Sci., 1, 1–39, https://doi.org/10.5194/wes-1-1-2016, https://doi.org/10.5194/wes-1-1-2016, 2016
C. F. Abari, A. T. Pedersen, E. Dellwik, and J. Mann
Atmos. Meas. Tech., 8, 4145–4153, https://doi.org/10.5194/amt-8-4145-2015, https://doi.org/10.5194/amt-8-4145-2015, 2015
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Continuous-wave coherent Doppler lidars (CW CDL) are a class of short-range wind lidars. This paper presents the measurement results from a field campaign where the performance of a recently built all-fiber image-reject homodyne CW CDL is compared against a sonic anemometer. The results are weighed against another instrument, i.e., a CW CDL benefiting from a heterodyne receiver. The results show that the new system has a superior measurement performance, especially for close-to-zero velocities.
A. Sathe, J. Mann, N. Vasiljevic, and G. Lea
Atmos. Meas. Tech., 8, 729–740, https://doi.org/10.5194/amt-8-729-2015, https://doi.org/10.5194/amt-8-729-2015, 2015
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A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method is presented as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence.
A. Sathe and J. Mann
Atmos. Meas. Tech., 6, 3147–3167, https://doi.org/10.5194/amt-6-3147-2013, https://doi.org/10.5194/amt-6-3147-2013, 2013
E. Branlard, A. T. Pedersen, J. Mann, N. Angelou, A. Fischer, T. Mikkelsen, M. Harris, C. Slinger, and B. F. Montes
Atmos. Meas. Tech., 6, 1673–1683, https://doi.org/10.5194/amt-6-1673-2013, https://doi.org/10.5194/amt-6-1673-2013, 2013
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Mehtab Ahmed Khan, Dries Allaerts, Simon J. Watson, and Matthew J. Churchfield
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To guide realistic atmospheric gravity wave simulations, we study flow over a two-dimensional hill and through a wind farm canopy, examining optimal domain size and damping layer setup. Wave properties based on non-dimensional numbers determine the optimal domain and damping parameters. Accurate solutions require the domain length to exceed the effective horizontal wavelength, height, and damping thickness to equal the vertical wavelength and non-dimensional damping strength between 1 and 10.
Adam S. Wise, Robert S. Arthur, Aliza Abraham, Sonia Wharton, Raghavendra Krishnamurthy, Rob Newsom, Brian Hirth, John Schroeder, Patrick Moriarty, and Fotini K. Chow
Wind Energ. Sci., 10, 1007–1032, https://doi.org/10.5194/wes-10-1007-2025, https://doi.org/10.5194/wes-10-1007-2025, 2025
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Wind farms can be subject to rapidly changing weather events. In the United States Great Plains, some of these weather events can result in waves in the atmosphere that ultimately affect how much power a wind farm can produce. We modeled a specific event of waves observed in Oklahoma. We determined how to accurately model the event and analyzed how it affected a wind farm’s power production, finding that the waves both decreased power and made it more variable.
Adriel J. Carvalho, Francisco L. Albuquerque Neto, and Denisson Q. Oliveira
Wind Energ. Sci., 10, 971–986, https://doi.org/10.5194/wes-10-971-2025, https://doi.org/10.5194/wes-10-971-2025, 2025
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Wind profilers are important to the wind power industry since they capture wind velocity and direction at higher altitudes than meteorological masts. Although some studies have investigated their performance in different scenarios, this paper covers a gap in knowledge by investigating and comparing their performance under rain events. This investigation is important since the data collected support strategic decisions in the wind power industry, where high data availability in all situations is critical.
Jeffrey D. Thayer, Gerard Kilroy, and Norman Wildmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-38, https://doi.org/10.5194/wes-2025-38, 2025
Revised manuscript accepted for WES
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With increasing wind energy in the German energy grid, it is crucial to better understand how different types of weather (including thunderstorms) can impact wind turbines and the surrounding atmosphere. We find rapid wind changes associated with the leading edge of thunderstorm outflows within the height range of wind turbines that would quickly increase wind power output, with longer-lasting changes in the near-surface atmosphere that would affect subsequent wind turbine operations.
Ye Liu, Timothy W. Juliano, Raghavendra Krishnamurthy, Brian J. Gaudet, and Jungmin Lee
Wind Energ. Sci., 10, 483–495, https://doi.org/10.5194/wes-10-483-2025, https://doi.org/10.5194/wes-10-483-2025, 2025
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Our study reveals how different weather patterns influence wind conditions off the US West Coast. We identified key weather patterns affecting wind speeds at potential wind farm sites using advanced machine learning. This research helps improve weather prediction models, making wind energy production more reliable and efficient.
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
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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.
Tsvetelina Ivanova, Sara Porchetta, Sophia Buckingham, Gertjan Glabeke, Jeroen van Beeck, and Wim Munters
Wind Energ. Sci., 10, 245–268, https://doi.org/10.5194/wes-10-245-2025, https://doi.org/10.5194/wes-10-245-2025, 2025
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This study explores how wind and power predictions can be improved by introducing local forcing of measurement data in a numerical weather model while taking into account the presence of neighboring wind farms. Practical implications for the wind energy industry include insights for informed offshore wind farm planning and decision-making strategies using open-source models, even under adverse weather conditions.
William Radünz, Bruno Carmo, Julie K. Lundquist, Stefano Letizia, Aliza Abraham, Adam S. Wise, Miguel Sanchez Gomez, Nicholas Hamilton, Raj K. Rai, and Pedro S. Peixoto
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-166, https://doi.org/10.5194/wes-2024-166, 2025
Revised manuscript accepted for WES
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This study investigates how simple terrain can cause significant variations in wind speed, especially during specific atmospheric conditions like low-level jets. By combining simulations and observations from a real wind farm, we found that downstream turbines generate more power than upstream ones, despite wake effects only impacting the upstream turbines. We highlight the crucial role of the strong vertical wind speed gradient in low-level jets in driving this effect.
Laura Bianco, Reagan Mendeke, Jake Lindblom, Irina V. Djalalova, David D. Turner, and James M. Wilczak
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-133, https://doi.org/10.5194/wes-2024-133, 2024
Revised manuscript accepted for WES
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Including more renewable energy into the electric grid is a critical part of the strategy to mitigate climate change. Reliable numerical weather prediction (NWP) models need to be able to predict the intrinsic nature of weather-dependent resources, such as wind ramp events, as wind energy could quickly be available in abundance or temporarily cease to exist. We assess the ability of the operational High Resolution Rapid Refresh NWP model to forecast wind ramp events in two most recent versions.
Jonathan Minz, Axel Kleidon, and Nsilulu T. Mbungu
Wind Energ. Sci., 9, 2147–2169, https://doi.org/10.5194/wes-9-2147-2024, https://doi.org/10.5194/wes-9-2147-2024, 2024
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Estimates of power output from regional wind turbine deployments in energy scenarios assume that the impact of the atmospheric feedback on them is minimal. But numerical models show that the impact is large at the proposed scales of future deployment. We show that this impact can be captured by accounting only for the kinetic energy removed by turbines from the atmosphere. This can be easily applied to energy scenarios and leads to more physically representative estimates.
Jérôme Neirynck, Jonas Van de Walle, Ruben Borgers, Sebastiaan Jamaer, Johan Meyers, Ad Stoffelen, and Nicole P. M. van Lipzig
Wind Energ. Sci., 9, 1695–1711, https://doi.org/10.5194/wes-9-1695-2024, https://doi.org/10.5194/wes-9-1695-2024, 2024
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In our study, we assess how mesoscale weather systems influence wind speed variations and their impact on offshore wind energy production fluctuations. We have observed, for instance, that weather systems originating over land lead to sea wind speed variations. Additionally, we noted that power fluctuations are typically more significant in summer, despite potentially larger winter wind speed variations. These findings are valuable for grid management and optimizing renewable energy deployment.
Sebastiano Stipa, Mehtab Ahmed Khan, Dries Allaerts, and Joshua Brinkerhoff
Wind Energ. Sci., 9, 1647–1668, https://doi.org/10.5194/wes-9-1647-2024, https://doi.org/10.5194/wes-9-1647-2024, 2024
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We introduce a novel way to model the impact of atmospheric gravity waves (AGWs) on wind farms using high-fidelity simulations while significantly reducing computational costs. The proposed approach is validated across different atmospheric stability conditions, and implications of neglecting AGWs when predicting wind farm power are assessed. This work advances our understanding of the interaction of wind farms with the free atmosphere, ultimately facilitating cost-effective research.
Sara Müller, Xiaoli Guo Larsén, and David Robert Verelst
Wind Energ. Sci., 9, 1153–1171, https://doi.org/10.5194/wes-9-1153-2024, https://doi.org/10.5194/wes-9-1153-2024, 2024
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Tropical cyclone winds are challenging for wind turbines. We analyze a tropical cyclone before landfall in a mesoscale model. The simulated wind speeds and storm structure are sensitive to the boundary parametrization. However, independent of the boundary layer parametrization, the median change in wind speed and wind direction with height is small relative to wind turbine design standards. Strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads.
Sebastiano Stipa, Arjun Ajay, Dries Allaerts, and Joshua Brinkerhoff
Wind Energ. Sci., 9, 1123–1152, https://doi.org/10.5194/wes-9-1123-2024, https://doi.org/10.5194/wes-9-1123-2024, 2024
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This paper introduces the multi-scale coupled (MSC) model, an engineering framework aimed at modeling turbine–wake and wind farm–gravity wave interactions, as well as local and global blockage effects. Comparisons against large eddy simulations show that the MSC model offers a valid contribution towards advancing our understanding of the coupled wind farm–atmosphere interaction, helping refining power estimation methodologies for existing and future wind farm sites.
David Rosencrans, Julie K. Lundquist, Mike Optis, Alex Rybchuk, Nicola Bodini, and Michael Rossol
Wind Energ. Sci., 9, 555–583, https://doi.org/10.5194/wes-9-555-2024, https://doi.org/10.5194/wes-9-555-2024, 2024
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The US offshore wind industry is developing rapidly. Using yearlong simulations of wind plants in the US mid-Atlantic, we assess the impacts of wind turbine wakes. While wakes are the strongest and longest during summertime stably stratified conditions, when New England grid demand peaks, they are predictable and thus manageable. Over a year, wakes reduce power output by over 35 %. Wakes in a wind plant contribute the most to that reduction, while wakes between wind plants play a secondary role.
Mohammad Golam Mostafa Khan and Mohammed Rafiuddin Ahmed
Wind Energ. Sci., 8, 1277–1298, https://doi.org/10.5194/wes-8-1277-2023, https://doi.org/10.5194/wes-8-1277-2023, 2023
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A robust technique for wind resource assessment with a Bayesian approach for estimating Weibull parameters is proposed. Research conducted using seven sites' data in the tropical region from 1° N to 21° S revealed that the three-parameter (3-p) Weibull distribution with a non-zero shift parameter is a better fit for wind data that have a higher percentage of low wind speeds. Wind data with higher wind speeds are a special case of the 3-p distribution. This approach gives accurate results.
Sue Ellen Haupt, Branko Kosović, Larry K. Berg, Colleen M. Kaul, Matthew Churchfield, Jeffrey Mirocha, Dries Allaerts, Thomas Brummet, Shannon Davis, Amy DeCastro, Susan Dettling, Caroline Draxl, David John Gagne, Patrick Hawbecker, Pankaj Jha, Timothy Juliano, William Lassman, Eliot Quon, Raj K. Rai, Michael Robinson, William Shaw, and Regis Thedin
Wind Energ. Sci., 8, 1251–1275, https://doi.org/10.5194/wes-8-1251-2023, https://doi.org/10.5194/wes-8-1251-2023, 2023
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The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy. It also points to code, assessment tools, and data for testing the methods.
Miguel Sanchez Gomez, Julie K. Lundquist, Jeffrey D. Mirocha, and Robert S. Arthur
Wind Energ. Sci., 8, 1049–1069, https://doi.org/10.5194/wes-8-1049-2023, https://doi.org/10.5194/wes-8-1049-2023, 2023
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The wind slows down as it approaches a wind plant; this phenomenon is called blockage. As a result, the turbines in the wind plant produce less power than initially anticipated. We investigate wind plant blockage for two atmospheric conditions. Blockage is larger for a wind plant compared to a stand-alone turbine. Also, blockage increases with atmospheric stability. Blockage is amplified by the vertical transport of horizontal momentum as the wind approaches the front-row turbines in the array.
Stephanie Redfern, Mike Optis, Geng Xia, and Caroline Draxl
Wind Energ. Sci., 8, 1–23, https://doi.org/10.5194/wes-8-1-2023, https://doi.org/10.5194/wes-8-1-2023, 2023
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As wind farm developments expand offshore, accurate forecasting of winds above coastal waters is rising in importance. Weather models rely on various inputs to generate their forecasts, one of which is sea surface temperature (SST). In this study, we evaluate how the SST data set used in the Weather Research and Forecasting model may influence wind characterization and find meaningful differences between model output when different SST products are used.
Merete Badger, Haichen Zuo, Ásta Hannesdóttir, Abdalmenem Owda, and Charlotte Hasager
Wind Energ. Sci., 7, 2497–2512, https://doi.org/10.5194/wes-7-2497-2022, https://doi.org/10.5194/wes-7-2497-2022, 2022
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When wind turbine blades are exposed to strong winds and heavy rainfall, they may be damaged and their efficiency reduced. The problem is most pronounced offshore where turbines are tall and the climate is harsh. Satellites provide global half-hourly rain observations. We use these rain data as input to a model for blade lifetime prediction and find that the satellite-based predictions agree well with predictions based on observations from weather stations on the ground.
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
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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.
Thomas Muschinski, Moritz N. Lang, Georg J. Mayr, Jakob W. Messner, Achim Zeileis, and Thorsten Simon
Wind Energ. Sci., 7, 2393–2405, https://doi.org/10.5194/wes-7-2393-2022, https://doi.org/10.5194/wes-7-2393-2022, 2022
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The power generated by offshore wind farms can vary greatly within a couple of hours, and failing to anticipate these ramp events can lead to costly imbalances in the electrical grid. A novel multivariate Gaussian regression model helps us to forecast not just the means and variances of the next day's hourly wind speeds, but also their corresponding correlations. This information is used to generate more realistic scenarios of power production and accurate estimates for ramp probabilities.
William J. Shaw, Larry K. Berg, Mithu Debnath, Georgios Deskos, Caroline Draxl, Virendra P. Ghate, Charlotte B. Hasager, Rao Kotamarthi, Jeffrey D. Mirocha, Paytsar Muradyan, William J. Pringle, David D. Turner, and James M. Wilczak
Wind Energ. Sci., 7, 2307–2334, https://doi.org/10.5194/wes-7-2307-2022, https://doi.org/10.5194/wes-7-2307-2022, 2022
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This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.
Andrew Clifton, Sarah Barber, Alexander Stökl, Helmut Frank, and Timo Karlsson
Wind Energ. Sci., 7, 2231–2254, https://doi.org/10.5194/wes-7-2231-2022, https://doi.org/10.5194/wes-7-2231-2022, 2022
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The transition to low-carbon sources of energy means that wind turbines will need to be built in hilly or mountainous regions or in places affected by icing. These locations are called
complexand are hard to develop. This paper sets out the research and development (R&D) needed to make it easier and cheaper to harness wind energy there. This includes collaborative R&D facilities, improved wind and weather models, frameworks for sharing data, and a clear definition of site complexity.
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
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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.
Adithya Vemuri, Sophia Buckingham, Wim Munters, Jan Helsen, and Jeroen van Beeck
Wind Energ. Sci., 7, 1869–1888, https://doi.org/10.5194/wes-7-1869-2022, https://doi.org/10.5194/wes-7-1869-2022, 2022
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The sensitivity of the WRF mesoscale modeling framework in accurately representing and predicting wind-farm-level environmental variables for three extreme weather events over the Belgian North Sea is investigated in this study. The overall results indicate highly sensitive simulation results to the type and combination of physics parameterizations and the type of the weather phenomena, with indications that scale-aware physics parameterizations better reproduce wind-related variables.
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Short summary
Wind flow consists of swirling patterns of air called eddies, some as big as many kilometers across, while others are as small as just a few meters. This paper introduces a method to simulate these large swirling patterns on a flat grid. Using these simulations we can better figure out how these large eddies affect big wind turbines in terms of loads and forces.
Wind flow consists of swirling patterns of air called eddies, some as big as many kilometers...
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