Articles | Volume 3, issue 1
https://doi.org/10.5194/wes-3-313-2018
© Author(s) 2018. 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-3-313-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 May 2018
Research article |
| 31 May 2018
| 31 May 2018
Very short-term forecast of near-coastal flow using scanning lidars
Laura Valldecabres
CORRESPONDING AUTHOR
ForWind – University of Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
Alfredo Peña
DTU Wind Energy, Risø Campus, Technical University of Denmark, Frederiksborvej 399, 4000 Roskilde, Denmark
Michael Courtney
DTU Wind Energy, Risø Campus, Technical University of Denmark, Frederiksborvej 399, 4000 Roskilde, Denmark
Lueder von Bremen
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
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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
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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.
Daniel Ribnitzky, Vlaho Petrovic, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-168, https://doi.org/10.5194/wes-2024-168, 2024
Preprint under review for WES
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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.
Etienne Cheynet, Jan Markus Diezel, Hilde Haakenstad, Øyvind Breivik, Alfredo Peña, and Joachim Reuder
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-119, https://doi.org/10.5194/wes-2024-119, 2024
Preprint under review for WES
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This study aims to help future large offshore wind turbines and airborne wind energy systems by providing insights into wind speeds at much higher altitudes than previously examined. We assessed three wind models (ERA5, NORA3, and NEWA) to predict wind speeds up to 500 m. Using lidar data from Norway and the North Sea, we found that ERA5 excels offshore, while NORA3 performs best onshore. However, the performance of the models depends on the locations and the evaluation criteria.
Alfredo Peña, Ginka Georgieva Yankova, and Vasiliki Mallini
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-108, https://doi.org/10.5194/wes-2024-108, 2024
Revised manuscript accepted for WES
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Lidars are vastly used in wind energy but most users struggle when interpreting lidar turbulence measures. Here we explain why is difficult to convert them into standard measurements. We show two ways to convert lidar to in-situ turbulence measurements, both using neural networks with one of them based on physics while the other is purely data driven. They show promising results when compared to high-quality turbulence measurements from a tall mast.
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
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Oscar García-Santiago, Andrea N. Hahmann, Jake Badger, and Alfredo Peña
Wind Energ. Sci., 9, 963–979, https://doi.org/10.5194/wes-9-963-2024, https://doi.org/10.5194/wes-9-963-2024, 2024
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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
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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 under review for AMT
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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.
Wei Fu, Feng Guo, David Schlipf, and Alfredo Peña
Wind Energ. Sci., 8, 1893–1907, https://doi.org/10.5194/wes-8-1893-2023, https://doi.org/10.5194/wes-8-1893-2023, 2023
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A high-quality preview of the rotor-effective wind speed is a key element of the benefits of feedforward pitch control. We model a one-beam lidar in the spinner of a 15 MW wind turbine. The lidar rotates with the wind turbine and scans the inflow in a circular pattern, mimicking a multiple-beam lidar at a lower cost. We found that a spinner-based one-beam lidar provides many more control benefits than the one on the nacelle, which is similar to a four-beam nacelle lidar for feedforward control.
Alessandro Sebastiani, James Bleeg, and Alfredo Peña
Wind Energ. Sci., 8, 1795–1808, https://doi.org/10.5194/wes-8-1795-2023, https://doi.org/10.5194/wes-8-1795-2023, 2023
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The power curve of a wind turbine indicates the turbine power output in relation to the wind speed. Therefore, power curves are critically important to estimate the production of future wind farms as well as to assess whether operating wind farms are functioning correctly. Since power curves are often measured in wind farms, they might be affected by the interactions between the turbines. We show that these effects are not negligible and present a method to correct for them.
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
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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
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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
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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.
Maarten Paul van der Laan, Oscar García-Santiago, Mark Kelly, Alexander Meyer Forsting, Camille Dubreuil-Boisclair, Knut Sponheim Seim, Marc Imberger, Alfredo Peña, Niels Nørmark Sørensen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 8, 819–848, https://doi.org/10.5194/wes-8-819-2023, https://doi.org/10.5194/wes-8-819-2023, 2023
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Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses. In this work, an efficient numerical method is presented that can be used to estimate these energy losses. The novel method is verified with higher-fidelity numerical models and validated with measurements of an existing wind farm cluster.
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
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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.
Wei Fu, Alessandro Sebastiani, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 8, 677–690, https://doi.org/10.5194/wes-8-677-2023, https://doi.org/10.5194/wes-8-677-2023, 2023
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Nacelle lidars with different beam scanning locations and two types of systems are considered for inflow turbulence estimations using both numerical simulations and field measurements. The turbulence estimates from a sonic anemometer at the hub height of a Vestas V52 turbine are used as references. The turbulence parameters are retrieved using the radial variances and a least-squares procedure. The findings from numerical simulations have been verified by the analysis of the field measurements.
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.
Andrea N. Hahmann, Oscar García-Santiago, and Alfredo Peña
Wind Energ. Sci., 7, 2373–2391, https://doi.org/10.5194/wes-7-2373-2022, https://doi.org/10.5194/wes-7-2373-2022, 2022
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We explore the changes in wind energy resources in northern Europe using output from simulations from the Climate Model Intercomparison Project (CMIP6) under the high-emission scenario. Our results show that climate change does not particularly alter annual energy production in the North Sea but could affect the seasonal distribution of these resources, significantly reducing energy production during the summer from 2031 to 2050.
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.
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
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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
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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.
Alessandro Sebastiani, Alfredo Peña, Niels Troldborg, and Alexander Meyer Forsting
Wind Energ. Sci., 7, 875–886, https://doi.org/10.5194/wes-7-875-2022, https://doi.org/10.5194/wes-7-875-2022, 2022
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The power performance of a wind turbine is often tested with the turbine standing in a row of several wind turbines, as it is assumed that the performance is not affected by the neighbouring turbines. We test this assumption with both simulations and measurements, and we show that the power performance can be either enhanced or lowered by the neighbouring wind turbines. Consequently, we also show how power performance testing might be biased when performed on a row of several wind turbines.
Wei Fu, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 7, 831–848, https://doi.org/10.5194/wes-7-831-2022, https://doi.org/10.5194/wes-7-831-2022, 2022
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Measuring the variability of the wind is essential to operate the wind turbines safely. Lidars of different configurations have been placed on the turbines’ nacelle to measure the inflow remotely. This work found that the multiple-beam lidar is the only one out of the three employed nacelle lidars that can give detailed information about the inflow variability. The other two commercial lidars, which have two and four beams, respectively, measure only the fluctuation in the along-wind direction.
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
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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
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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
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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
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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.
Davide Conti, Nikolay Dimitrov, Alfredo Peña, and Thomas Herges
Wind Energ. Sci., 6, 1117–1142, https://doi.org/10.5194/wes-6-1117-2021, https://doi.org/10.5194/wes-6-1117-2021, 2021
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We carry out a probabilistic calibration of the Dynamic Wake Meandering (DWM) model using high-spatial- and high-temporal-resolution nacelle-based lidar measurements of the wake flow field. The experimental data were collected from the Scaled Wind Farm Technology (SWiFT) facility in Texas. The analysis includes the velocity deficit, wake-added turbulence, and wake meandering features under various inflow wind and atmospheric-stability conditions.
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
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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.
Davide Conti, Vasilis Pettas, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci., 6, 841–866, https://doi.org/10.5194/wes-6-841-2021, https://doi.org/10.5194/wes-6-841-2021, 2021
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We define two lidar-based procedures for improving the accuracy of wind turbine load assessment under wake conditions. The first approach incorporates lidar observations directly into turbulence fields serving as inputs for aeroelastic simulations; the second approach imposes lidar-fitted wake deficit time series on the turbulence fields. The uncertainty in the lidar-based power and load predictions is quantified for a variety of scanning configurations and atmosphere turbulence conditions.
Alfredo Peña, Branko Kosović, and Jeffrey D. Mirocha
Wind Energ. Sci., 6, 645–661, https://doi.org/10.5194/wes-6-645-2021, https://doi.org/10.5194/wes-6-645-2021, 2021
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We investigate the ability of a community-open weather model to simulate the turbulent atmosphere by comparison with measurements from a 250 m mast at a flat site in Denmark. We found that within three main atmospheric stability regimes, idealized simulations reproduce closely the characteristics of the observations with regards to the mean wind, direction, turbulent fluxes, and turbulence spectra. Our work provides foundation for the use of the weather model in multiscale real-time simulations.
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
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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
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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.
Anders Tegtmeier Pedersen and Michael Courtney
Atmos. Meas. Tech., 14, 889–903, https://doi.org/10.5194/amt-14-889-2021, https://doi.org/10.5194/amt-14-889-2021, 2021
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This paper suggests and describes a method for calibrating wind lidars using a rotating flywheel. An uncertainty analysis shows that a standard uncertainty of 0.1 % can be achieved, with the main contributor being the width of the laser beam which is in agreement with experimental results. The method can potentially lower the calibration uncertainty of wind lidars, which today is often based on cup anemometers, and thus lead to better wind assessments and perhaps more widespread use.
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
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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.
Pedro Santos, Alfredo Peña, and Jakob Mann
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-960, https://doi.org/10.5194/acp-2020-960, 2020
Preprint withdrawn
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We show that the vector of vertical flux of horizontal momentum and the vector of the mean vertical gradient of horizontal velocity are not aligned, based on Doppler wind lidar observations up to 500 m, both offshore and onshore. We illustrate that a mesoscale model output matches the observed mean wind speed and momentum fluxes well, but that this model output as well as idealized large-eddy simulations have deviations with the observations when looking at the turning of the wind.
Davide Conti, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci., 5, 1129–1154, https://doi.org/10.5194/wes-5-1129-2020, https://doi.org/10.5194/wes-5-1129-2020, 2020
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We propose a method for carrying out wind turbine load validation in wake conditions using measurements from forward-looking nacelle lidars. The uncertainty of aeroelastic load predictions is quantified against wind turbine on-board sensor data. This work demonstrates the applicability of nacelle-mounted lidar measurements to extend load and power validations under wake conditions and highlights the main challenges.
Nikola Vasiljević, Michael Courtney, and Anders Tegtmeier Pedersen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-321, https://doi.org/10.5194/amt-2020-321, 2020
Publication in AMT not foreseen
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In this paper, we present an analytical model for estimating the uncertainty of the horizontal wind speed based on dual-Doppler lidar measurements. The model follows the propagation of uncertainties method and takes into account the uncertainty of radial velocity estimation, azimuth and elevation pointing angles, and ranging. The model has been implemented in Python and made freely available as the Python package YADDUM (Yet Another Dual-Doppler Uncertainty Model).
Maarten Paul van der Laan, Mark Kelly, Rogier Floors, and Alfredo Peña
Wind Energ. Sci., 5, 355–374, https://doi.org/10.5194/wes-5-355-2020, https://doi.org/10.5194/wes-5-355-2020, 2020
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The design of wind turbines and wind farms can be improved by increasing the accuracy of the inflow models representing the atmospheric boundary layer (ABL). In this work we employ numerical simulations of the idealized ABL, which can represent the mean effects of Coriolis and buoyancy forces and surface roughness. We find a new model-based similarity that provides a better understanding of the idealized ABL. In addition, we extend the model to include effects of convective buoyancy forces.
Nikola Vasiljević, Michael Harris, Anders Tegtmeier Pedersen, Gunhild Rolighed Thorsen, Mark Pitter, Jane Harris, Kieran Bajpai, and Michael Courtney
Atmos. Meas. Tech., 13, 521–536, https://doi.org/10.5194/amt-13-521-2020, https://doi.org/10.5194/amt-13-521-2020, 2020
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In this paper we present the preliminary results of the proof-of-concept (POC) stage of a drone-based wind lidar system development process. To test the POC drone–lidar system we hovered the drone next to mast-mounted sonic anemometers at the Risø test center. The preliminary results of the intercomparison between the measurements derived from the POC system and those of the sonic anemometers show good agreement.
Jörge Schneemann, Andreas Rott, Martin Dörenkämper, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 5, 29–49, https://doi.org/10.5194/wes-5-29-2020, https://doi.org/10.5194/wes-5-29-2020, 2020
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Offshore wind farm clusters cause reduced wind speeds in downstream regions which can extend over more than 50 km.
We analysed the impact of these so-called cluster wakes on a distant wind farm using remote-sensing wind measurements and power production data.
Cluster wakes caused power losses up to 55 km downstream in certain atmospheric states.
A better understanding of cluster wake effects reduces uncertainties in offshore wind resource assessment and improves offshore areal planning.
Róbert Ungurán, Vlaho Petrović, Lucy Y. Pao, and Martin Kühn
Wind Energ. Sci., 4, 677–692, https://doi.org/10.5194/wes-4-677-2019, https://doi.org/10.5194/wes-4-677-2019, 2019
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A novel lidar-based sensory system for wind turbine control is proposed. The main contributions are the parametrization method of the novel measurement system, the identification of possible sources of measurement uncertainty, and their modelling. Although not the focus of the submitted paper, the mentioned contributions represent essential building blocks for robust feedback–feedforward wind turbine control development which could be used to improve wind turbine control strategies.
Mehdi Vali, Vlaho Petrović, Gerald Steinfeld, Lucy Y. Pao, and Martin Kühn
Wind Energ. Sci., 4, 139–161, https://doi.org/10.5194/wes-4-139-2019, https://doi.org/10.5194/wes-4-139-2019, 2019
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A new active power control (APC) approach is investigated to simultaneously reduce the wake-induced power tracking errors and structural fatigue loads of individual turbines within a wind farm. The non-unique solution of the APC problem with respect to the distribution of the individual powers is exploited. The simple control architecture and practical measurement system make the proposed approach prominent for real-time control of large wind farms with turbulent flows and wakes.
Alfredo Peña, Ebba Dellwik, and Jakob Mann
Atmos. Meas. Tech., 12, 237–252, https://doi.org/10.5194/amt-12-237-2019, https://doi.org/10.5194/amt-12-237-2019, 2019
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We propose a method to assess the accuracy of turbulence measurements by sonic anemometers. The idea is to compute the ratio of the vertical to along-wind velocity spectrum within the inertial subrange. We found that the Metek USA-1 and the Campbell CSAT3 sonic anemometers do not show the expected theoretical ratio. A wind-tunnel-based correction recovers the expected ratio for the USA-1. A correction for the CSAT3 does not, illustrating that this sonic anemometer suffers from flow distortion.
Elliot Simon, Michael Courtney, and Nikola Vasiljevic
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2018-71, https://doi.org/10.5194/wes-2018-71, 2018
Publication in WES not foreseen
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Remotely measured winds upstream of a wind farm presents the opportunity for improving wind energy forecasts on minute timescales. Forward looking information about conditions which advect to some degree downwind provides useful information not available in existing methods. In order to explore this, a field experiment was conduced using scanning lidar to measure winds 7 km ahead of a reference met-mast. Using this dataset, an online learning forecast system has been demonstrated and benchmarked.
Andreas Rott, Bart Doekemeijer, Janna Kristina Seifert, Jan-Willem van Wingerden, and Martin Kühn
Wind Energ. Sci., 3, 869–882, https://doi.org/10.5194/wes-3-869-2018, https://doi.org/10.5194/wes-3-869-2018, 2018
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Active wake deflection (AWD) aims to increase the power output of a wind farm by misaligning the yaw of upstream turbines. We analysed the effect of dynamic wind direction changes on AWD. The results show that AWD is very sensitive towards these dynamics. Therefore, we present a robust active wake control, which considers uncertainties and wind direction changes, increasing the overall power output of a wind farm. A side effect is a significant reduction of the yaw actuation of the turbines.
Niko Mittelmeier and Martin Kühn
Wind Energ. Sci., 3, 395–408, https://doi.org/10.5194/wes-3-395-2018, https://doi.org/10.5194/wes-3-395-2018, 2018
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Upwind horizontal axis wind turbines need to be aligned with the main wind direction to maximize energy yield. This paper presents new methods to improve turbine alignment and detect changes during operational lifetime with standard nacelle met mast instruments. The flow distortion behind the rotor is corrected with a multilinear regression model and two alignment changes are detected with an accuracy of ±1.4° within 3 days of operation after the change is introduced.
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.
Alfredo Peña, Kurt Schaldemose Hansen, Søren Ott, and Maarten Paul van der Laan
Wind Energ. Sci., 3, 191–202, https://doi.org/10.5194/wes-3-191-2018, https://doi.org/10.5194/wes-3-191-2018, 2018
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We analyze the wake of the Anholt offshore wind farm in Denmark by intercomparing models and measurements. We also look at the effect of the land on the wind farm by intercomparing mesoscale winds and measurements. Annual energy production and capacity factor estimates are performed using different approaches. Lastly, the uncertainty of the wake models is determined by bootstrapping the data; we find that the wake models generally underestimate the wake losses.
Lukas Vollmer, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 2, 603–614, https://doi.org/10.5194/wes-2-603-2017, https://doi.org/10.5194/wes-2-603-2017, 2017
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A model chain to simulate changing atmospheric conditions at the location of an offshore wind farm is introduced and validated. The methodology is used to simulate the wind flow upstream and downstream of an offshore wind turbine of the German wind farm Alpha ventus. The model results show a good agreement with wind measurements from the met mast that is located at the wind farm and with remote sensing measurements of the horizontal wind field.
Davide Trabucchi, Lukas Vollmer, and Martin Kühn
Wind Energ. Sci., 2, 569–586, https://doi.org/10.5194/wes-2-569-2017, https://doi.org/10.5194/wes-2-569-2017, 2017
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The wakes of wind turbines cause losses in the energy production of a wind farm. The accuracy of models applied to predict wake losses is a key factor for new wind projects. This paper presents an engineering wake model that can simulate merging wakes on the basis of physical principles. We used high-fidelity simulations of merging wakes to assess this model and found a better agreement with the reference than commonly used models implementing the superposition of individual wakes.
Niko Mittelmeier, Julian Allin, Tomas Blodau, Davide Trabucchi, Gerald Steinfeld, Andreas Rott, and Martin Kühn
Wind Energ. Sci., 2, 477–490, https://doi.org/10.5194/wes-2-477-2017, https://doi.org/10.5194/wes-2-477-2017, 2017
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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.
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.
Maria Krutova, Alexander Kies, Bruno U. Schyska, and Lueder von Bremen
Adv. Sci. Res., 14, 253–260, https://doi.org/10.5194/asr-14-253-2017, https://doi.org/10.5194/asr-14-253-2017, 2017
Marijn Floris van Dooren, Filippo Campagnolo, Mikael Sjöholm, Nikolas Angelou, Torben Mikkelsen, and Martin Kühn
Wind Energ. Sci., 2, 329–341, https://doi.org/10.5194/wes-2-329-2017, https://doi.org/10.5194/wes-2-329-2017, 2017
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We conducted measurements in a wind tunnel with the remote sensing technique lidar to map the flow around a row of three model wind turbines. Two lidars were positioned near the wind tunnel walls to measure the two-dimensional wind vector over a defined scanning line or area without influencing the flow itself. A comparison of the lidar measurements with a hot-wire probe and a thorough uncertainty analysis confirmed the usefulness of lidar technology for such flow measurements in a wind tunnel.
Bruno U. Schyska, António Couto, Lueder von Bremen, Ana Estanqueiro, and Detlev Heinemann
Adv. Sci. Res., 14, 131–138, https://doi.org/10.5194/asr-14-131-2017, https://doi.org/10.5194/asr-14-131-2017, 2017
Niko Mittelmeier, Tomas Blodau, and Martin Kühn
Wind Energ. Sci., 2, 175–187, https://doi.org/10.5194/wes-2-175-2017, https://doi.org/10.5194/wes-2-175-2017, 2017
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Efficient detection of wind turbines operating below their expected power output and immediate corrections help maximize asset value. The method presented estimates the environmental conditions from turbine states and uses pre-calculated power lookup tables from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output are an indication of underperformance. A demonstration of the method's ability to detect underperformance is given.
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.
Lukas Vollmer, Gerald Steinfeld, Detlev Heinemann, and Martin Kühn
Wind Energ. Sci., 1, 129–141, https://doi.org/10.5194/wes-1-129-2016, https://doi.org/10.5194/wes-1-129-2016, 2016
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The wake flow downstream of yaw misaligned wind turbines is studied in numeric simulations of different atmospheric turbulence and shear conditions. We find that the average trajectory of the wake as well as the variation about this average is influenced by the thermal stability of the atmosphere. The results suggest that an intentional intervention in the yaw control of individual turbines to increase overall wind farm performance might be not successful during unstable thermal conditions.
Alfredo Peña, Andreas Bechmann, Davide Conti, and Nikolas Angelou
Wind Energ. Sci., 1, 101–114, https://doi.org/10.5194/wes-1-101-2016, https://doi.org/10.5194/wes-1-101-2016, 2016
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We have developed flow models from different complexities. Unfortunately, high quality and reliable wind observations affected by obstacles are rare and so we have few means to evaluate our models. We have therefore performed a campaign in which we measured the effect of a fence on the atmosphere using laser-based instruments. The effect can still be noticed as far as 11 fence heights. A wake theory seems to predict the obstacle effect when we are looking at distances beyond 6 fence heights.
Juan José Trujillo, Janna Kristina Seifert, Ines Würth, David Schlipf, and Martin Kühn
Wind Energ. Sci., 1, 41–53, https://doi.org/10.5194/wes-1-41-2016, https://doi.org/10.5194/wes-1-41-2016, 2016
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We present the analysis of the trajectories followed by the wind, in the immediate vicinity, behind an offshore wind turbine and their dependence on its yaw misalignment. We apply wake tracking on wind fields measured with a lidar (light detection and ranging) system located at the nacelle of the wind turbine and pointing downstream. The analysis reveals discrepancies of the estimated mean wake paths against theoretical and wind tunnel experiments using different wake-tracking techniques.
Related subject area
Electricity conversion, forecasting, grid & market integration
Power fluctuations in high-installation- density offshore wind fleets
Future economic perspective and potential revenue of non-subsidized wind turbines in Germany
Characterisation of intra-hourly wind power ramps at the wind farm scale and associated processes
North Sea region energy system towards 2050: integrated offshore grid and sector coupling drive offshore wind power installations
Comparison of electrical collection topologies for multi-rotor wind turbines
Generic characterization of electrical test benches for AC- and HVDC-connected wind power plants
Ancillary services from wind turbines: automatic generation control (AGC) from a single Type 4 turbine
Feasibility study for 100 % renewable energy microgrids in Switzerland
Field-test of wind turbine by voltage source converter
The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality
Juan Pablo Murcia Leon, Matti Juhani Koivisto, Poul Sørensen, and Philippe Magnant
Wind Energ. Sci., 6, 461–476, https://doi.org/10.5194/wes-6-461-2021, https://doi.org/10.5194/wes-6-461-2021, 2021
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Detailed wind generation simulations of the 2028 Belgian offshore fleet are performed in order to quantify the distribution and extremes of power fluctuations in several time windows. A model validation with respect to the operational data of the 2018 fleet shows that the methodology presented in this article is able to capture the distribution of wind power and its spatiotemporal characteristics. The results show that the standardized generation ramps are expected to be reduced in the future.
Lucas Blickwedel, Freia Harzendorf, Ralf Schelenz, and Georg Jacobs
Wind Energ. Sci., 6, 177–190, https://doi.org/10.5194/wes-6-177-2021, https://doi.org/10.5194/wes-6-177-2021, 2021
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Revenues from the operation of wind turbines in Germany will be insecure in the future due to the expiration of federal support. Alternative ways of selling electricity are usually based on exchange prices. Therefore, the long-term revenue potential of wind turbines is assessed based on levelized revenue of energy (LROE), using a new forecasting model and open-source data. Results show how different expansion scenarios and emission prices may affect profitability of future plants.
Mathieu Pichault, Claire Vincent, Grant Skidmore, and Jason Monty
Wind Energ. Sci., 6, 131–147, https://doi.org/10.5194/wes-6-131-2021, https://doi.org/10.5194/wes-6-131-2021, 2021
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This paper assesses the behaviour and causality of sudden variations in wind power generation over a short period of time, also called "ramp events". It is shown, amongst other things, that ramps at the study site are mostly associated with frontal activity. Overall, the research contributes to a better understanding of the drivers and behaviours of wind power ramps at the wind farm scale, beneficial to ramp forecasting and ramp modelling.
Matti Koivisto, Juan Gea-Bermúdez, Polyneikis Kanellas, Kaushik Das, and Poul Sørensen
Wind Energ. Sci., 5, 1705–1712, https://doi.org/10.5194/wes-5-1705-2020, https://doi.org/10.5194/wes-5-1705-2020, 2020
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Several energy system scenarios towards 2050 for the North Sea region are analysed. With a focus on offshore wind, the impacts of meshed offshore grid and sector coupling are studied. The results show that the introduction of a meshed grid can increase offshore wind power installations by around 10 GW towards 2050. However, sector coupling is expected to increase offshore wind power installations by tens of gigawatts.
Paul Pirrie, David Campos-Gaona, and Olimpo Anaya-Lara
Wind Energ. Sci., 5, 1237–1252, https://doi.org/10.5194/wes-5-1237-2020, https://doi.org/10.5194/wes-5-1237-2020, 2020
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Multi-rotor wind turbines are an innovative solution to achieving cost-effective large-scale wind turbines. They utilize a large number of small rotors connected to one support structure instead of one large rotor. Benefits include reduction in cost, transport and installation simplicity, modular design, and standardization. This work compares different electrical systems in terms of cost, mass and efficiency and finds a star-type system (each rotor has its own cable) to be the most suitable.
Behnam Nouri, Ömer Göksu, Vahan Gevorgian, and Poul Ejnar Sørensen
Wind Energ. Sci., 5, 561–575, https://doi.org/10.5194/wes-5-561-2020, https://doi.org/10.5194/wes-5-561-2020, 2020
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This research paper proposes a generic structure of electrical test benches and a novel categorization of test options for experimental analysis of wind turbines and wind power plants. The new proposed test structure would concern the increasing challenges in wind power integration and control including reliability, stability, harmonic interactions, and control performance of WPPs in connection to different types of AC and HVDC transmission systems.
Eldrich Rebello, David Watson, and Marianne Rodgers
Wind Energ. Sci., 5, 225–236, https://doi.org/10.5194/wes-5-225-2020, https://doi.org/10.5194/wes-5-225-2020, 2020
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As more electrical energy is generated by wind turbines, older generation technologies such as coal and gas are being displaced. This situation presents a challenge in the sense that the additional services once provided by fossil generators must now be sourced from elsewhere. Our work provides real-world data showing the capabilities of wind generators in providing the specific service of secondary frequency regulation (automatic generation control, AGC).
Sarah Barber, Simon Boller, and Henrik Nordborg
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-97, https://doi.org/10.5194/wes-2019-97, 2019
Revised manuscript not accepted
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The growing worldwide level of renewable power generation requires innovative solutions to maintain grid reliability and stability. In this work, twelve sites in Switzerland are chosen for a 100 % renewable energy microgrid feasibility study. For all of these sites, a combination of wind and PV performs consistently better than wind only and PV only. Five of the sites are found to be potentially economically viable, if investors would be prepared to make extra investments of 0.05–0.2 $/kWh.
Nicolás Espinoza and Ola Carlson
Wind Energ. Sci., 4, 465–477, https://doi.org/10.5194/wes-4-465-2019, https://doi.org/10.5194/wes-4-465-2019, 2019
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An important design criterion for the electric drive system of a wind turbine is the fulfilment of grid codes given by transmission system operators. The grid codes state how wind turbines/farms must behave when connected to the grid in normal and abnormal conditions. A type of testing equipment that comprises the use of fully-rated voltage source converter in back-to-back configuration for grid code testing is proposed. Test results of a 4 MW wind turbine and an 8 MW test equipment are shown.
Tyler C. McCandless and Sue Ellen Haupt
Wind Energ. Sci., 4, 343–353, https://doi.org/10.5194/wes-4-343-2019, https://doi.org/10.5194/wes-4-343-2019, 2019
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Often in wind power forecasting the mean wind speed is forecasted at a plant, converted to power, and multiplied by the number of turbines to predict the plant's generating capacity. This methodology ignores the variability among turbines caused by localized weather, terrain, and array orientation. We show that the wind farm mean wind speed approach for power conversion is impacted by Jensen's inequality, quantify the differences, and show machine learning can overcome these differences.
Cited articles
Alexiadis, M., Dokopoulos, P., Sahsamanoglou, H., and Manousaridis, I.:
Short-term forecasting of wind speed and related electrical power,
Sol. Energy,
63, 61–68, https://doi.org/10.1016/S0038-092X(98)00032-2, 1998. a
Barthelmie, R., Murray, F., and Pryor, S.:
The economic benefit of short-term forecasting for wind energy in the UK electricity market,
Energ. Policy,
36, 1687–1696, https://doi.org/10.1016/j.enpol.2008.01.027, 2008. a
Beck, H. and Kühn, M.:
Dynamic data filtering of long-range Doppler LiDAR wind speed measurements,
Remote Sensing-Basel,
9, 561, https://doi.org/10.3390/rs9060561, 2017. a
Box, G. E. P. and Jenkins, G. M.: Time series analysis: forecasting and
control, J. Time Ser. Anal., 31, p. 303,
https://doi.org/10.1111/j.1467-9892.2009.00643.x, 1976. a
Cadenas, E. and Rivera, W.:
Wind speed forecasting in the South Coast of Oaxaca, México,
Renew. Energ.,
32, 2116–2128, https://doi.org/10.1016/j.renene.2006.10.005, 2007. a
Cadenas, E. and Rivera, W.:
Short term wind speed forecasting in La Venta, Oaxaca, México, using artificial neural networks,
Renew. Energ.,
34, 274–278, https://doi.org/10.1016/j.renene.2008.03.014, 2009. a
Charnock, H.:
Wind stress on a water surface,
Q. J. Roy. Meteor. Soc.,
81, 639–640, https://doi.org/10.1002/qj.49708135027, 1955. a
Damousis, I. G., Alexiadis, M. C., Theocharis, J. B., and Dokopoulos, P. S.:
A fuzzy model for wind speed prediction and power generation in wind parks
using spatial correlation, IEEE T. Energy Conver., 19, 352–361,
https://doi.org/10.1109/Tec.2003.821865, 2004. a
Danish Wind Industry Association (DWIA): Wind Energy Production as
a Percentage of Total Electricity Consumtion 2005–2017, available at:
http://www.windpower.org/en/knowledge/statistics/the_danish_market.html
(last access: 22 January 2018), 2018. a
Dickey, D. A. and Fuller, W. A.: Distribution of the estimators for
autoregressive time series with a unit root, J. Am. Stat. Assoc., 74,
427–431, https://doi.org/10.2307/2286348, 1979. a
EPEXSPOT: Intraday Lead Times, available at:
https://www.epexspot.com/en/product-info/intradaycontinuous/intraday_lead_time
(last access: 25 September 2017), 2017. a
Floors, R., Lea, G., Pena Diaz, A., Karagali, I., and Ahsbahs, T.:
Report on RUNE's Coastal Experiment and First Inter-Comparisons Between Measurements Systems,
Tech. rep.,
DTU Wind Energy E-0115(EN), DTU Wind Energy, Roskilde, Denmark, 2016a. a
Frehlich, R.:
Scanning Doppler lidar for input into short-term wind power forecasts,
J. Atmos. Ocean. Tech.,
30, 230–244, https://doi.org/10.1175/JTECH-D-11-00117.1, 2013. a
Geostyrelsen: available at:
http://download.kortforsyningen.dk/content/dhm-2007overflade-16-mgrid
(last access: 5 April 2017), 2016. a
Giebel, G., Brownsword, R., Kariniotakis, G., Denhard, M., and Draxl, C.: The
State-of-the-Art in Short-Term Prediction of Wind Power – A Literature
Overview, Technical Report, EU Project ANEMOS, 109 pp., available at:
http://orbit.dtu.dk/getResource?recordId=274635&objectId=1&versionId=1
(last access: 28 May 2018), 2011. a
Gonzalez-Aparicio, I. and Zucker, A.:
Impact of wind power uncertainty forecasting on the market integration of wind energy in Spain,
Appl. Energ.,
159, 334–349, https://doi.org/10.1016/j.apenergy.2015.08.104, 2015. a
Hill, D. C., McMillan, D., Bell, K. R. W., and Infield, D.:
Application of auto-regressive models to U.K. wind speed data for power system impact studies,
IEEE T. Sustain. Energ.,
3, 134–141, https://doi.org/10.1109/TSTE.2011.2163324, 2012. a
Holttinen, H., Meibom, P., Orths, A., Hulle, F. V., Lange, B., O'Malley, M.,
Pierik, J., Ummels, B., Tande, J. O., Estanqueiro, A., Gomez, E., Söder,
L., Strbac, G., Shakoor, A., Ricardo, J., Smith, C., Milligan, M., and Ela,
E.: Design and Operation of Power Systems with Large Amounts of Wind Power,
Final Summary Report, IEA Wind Task 25, available at:
https://community.ieawind.org/task25/viewdocument/design-and-operation-of-power-syste-2?CommunityKey=4aa82210-1b2e-43c5-b37b-1cdf11020dc8
(last access: 28 May 2018), 2016. a
Høyer, J. L. and She, J.:
Optimal interpolation of sea surface temperature for the North Sea and Baltic Sea,
J. Marine Syst.,
65, 176–189, https://doi.org/10.1016/j.jmarsys.2005.03.008, 2007. a
Ibanez, E. and Milligan, M.: Impact of transmission on resource adequacy in
systems with wind and solar power, in: IEEE Power and Energy Society General
Meeting, 1–5, https://doi.org/10.1109/PESGM.2012.6343955, 2012. a
Kameyama, S., Sakimura, T., Watanabe, Y., Ando, T., Asaka, K.,
Tanaka, H., Yanagisawa, T., Hirano, Y., and Inokuchi, H.: Wind
sensing demonstration of more than 30 km measurable range with
a 1.5 µm coherent Doppler lidar which has the laser amplifier
using Er,Yb:glass planar waveguide, Proc. SPIE, 8526,
https://doi.org/10.1117/12.977330, 2012. a
Kavasseri, R. G. and Seetharaman, K.:
Day-ahead wind speed forecasting using f-ARIMA models,
Renew. Energ.,
34, 1388–1393, https://doi.org/10.1016/j.renene.2008.09.006, 2009. a, b
Kraus, E. B.:
Atmosphere-Ocean Interaction,
Oxford University Press, New York, p. 275, 1972. a
Larson, K. A. and Westrick, K.:
Short-term wind forecasting using off-site observations,
Wind Energy,
9, 55–62, https://doi.org/10.1002/we.179, 2006. a
Li, G. and Shi, J.:
On comparing three artificial neural networks for wind speed forecasting,
Appl. Energ.,
87, 2313–2320, https://doi.org/10.1016/j.apenergy.2009.12.013, 2010. a
Mikkelsen, T., Angelou, N., Hansen, K., Sjöholm, M., Harris, M., Slinger, C., Hadley, P., Scullion, R., Ellis, G., and Vives, G.:
A spinner-integrated wind lidar for enhanced wind turbine control,
Wind Energy,
16, 625–643, https://doi.org/10.1002/we.1564, 2013. a
Monfared, M., Rastegar, H., and Kojabadi, H. M.:
A new strategy for wind speed forecasting using artificial intelligent methods,
Renew. Energ.,
34, 845–848, https://doi.org/10.1016/j.renene.2008.04.017, 2009. a
Peña, A., Floors, R., Sathe, A., Gryning, S. E., Wagner, R., Courtney, M. S., Larsén, X. G., Hahmann, A. N., and Hasager, C. B.:
Ten years of boundary-layer and wind-power meteorology at Høvsøre, Denmark,
Bound.-Lay. Meteorol.,
158, 1–26, https://doi.org/10.1007/s10546-015-0079-8, 2016. a
Peña, A., Mann, J., and Dimitrov, N.: Turbulence characterization from a
forward-looking nacelle lidar, Wind Energ. Sci., 2, 133–152,
https://doi.org/10.5194/wes-2-133-2017, 2017. a
Sanchez, R. and Rørbæk, K.: Metocean Buoy Deployment, Technical
Report, DHI, 2016. a
Schlueter, R. A., Sigari, G., and Costi, A.:
Wind array power prediction for improved operating economics and reliability,
IEEE T. Power Syst.,
1, 137–142, https://doi.org/10.1109/TPWRS.1986.4334859, 1986. a
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
Taylor, G. I.:
The spectrum of turbulence,
P. Roy Soc. A-Math. Phy.,
164, 476–490, https://doi.org/10.1098/rspa.1938.0032, 1938. a
Torres, J. L., Garcia, A., De Blas, M., and De Francisco, A.:
Forecast of hourly average wind speed with ARMA models in Navarre (Spain),
Sol. Energy,
79, 65–77, https://doi.org/10.1016/j.solener.2004.09.013, 2005. a, b
Troen, I. and Lundtang Petersen, E.:
European Wind Atlas,
Risø National Laboratory, Roskilde, p. 656, 1989. a
Wang, Q., Martinez-Anido, C. B., Wu, H., Florita, A. R., and Hodge, B. M.:
Quantifying the economic and grid reliability impacts of improved wind power
forecasting, IEEE T. Sustain. Energ., 7, 1525–1537,
https://doi.org/10.1109/TSTE.2016.2560628, 2016. a
Wharton, S., Newman, J., Qualley, G., and Miller, W.:
Measuring turbine inflow with vertically-profiling lidar in complex terrain,
J. Wind Eng. Ind. Aerod.,
142, 217–231, https://doi.org/10.1016/j.jweia.2015.03.023, 2015. a
Short summary
This paper focuses on the use of scanning lidars for very short-term forecasting of wind speeds in a near-coastal area. An extensive data set of offshore lidar measurements up to 6 km has been used for this purpose. Using dual-doppler measurements, the topographic characteristics of the area have been modelled. Assuming Taylor's frozen turbulence and applying the topographic corrections, we demonstrate that we can forecast wind speeds with more accuracy than the benchmarks persistence or ARIMA.
This paper focuses on the use of scanning lidars for very short-term forecasting of wind speeds...
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