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Abstracted/indexed
WES | Articles | Volume 5, issue 2
Wind Energ. Sci., 5, 775–792, 2020
https://doi.org/10.5194/wes-5-775-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-775-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue: Wind Energy Science Conference 2019
Wind Energ. Sci., 5, 775–792, 2020
https://doi.org/10.5194/wes-5-775-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-775-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article 19 Jun 2020
Research article | 19 Jun 2020
Dynamic wake meandering model calibration using nacelle-mounted lidar systems
Inga Reinwardt et al.
Related authors
No articles found.
Sven Störtenbecker, Peter Dalhoff, Mukunda Tamang, and Rudolf Anselm
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-46, https://doi.org/10.5194/wes-2020-46, 2020
Revised manuscript accepted for WES
Short summary
Short summary
Multi rotor wind turbine systems show the potential to reduce the levelized cost of energy. In this study a simplified and fast method as a first venture to find an optimal number of rotors is presented. A variety of space frame designs are dimensioned based on ultimate loads and buckling, as a preliminary step for later detailed analyses.
Related subject area
Wind and turbulence
First characterization of a new perturbation system for gust generation: the chopper
Cross-contamination effect on turbulence spectra from Doppler beam swinging wind lidar
The importance of round-robin validation when assessing machine-learning-based vertical extrapolation of wind speeds
Exploring the complexities associated with full-scale wind plant wake mitigation control experiments
Validation of uncertainty reduction by using multiple transfer locations for WRF-CFD coupling in numerical wind energy assessments
Mitigating impact of spatial variance of turbulence in wind energy applications
Comparing abnormalities in onshore and offshore vertical wind profiles
Europe's offshore winds assessed with synthetic aperture radar, ASCAT and WRF
Rossby number similarity of an atmospheric RANS model using limited-length-scale turbulence closures extended to unstable stratification
Optimizing wind farm control through wake steering using surrogate models based on high-fidelity simulations
How to improve the state of the art in metocean measurement datasets
Aero-elastic load validation in wake conditions using nacelle-mounted lidar measurements
The Power Curve Working Group's assessment of wind turbine power performance prediction methods
Multipoint Reconstruction of Wind Speeds
Evaluation of the Lattice Boltzmann Method for wind modelling in complex terrain
Aeroelastic response of a multi-megawatt upwind horizontal axis wind turbine (HAWT) based on fluid–structure interaction simulation
Clustering wind profile shapes to estimate airborne wind energy production
Effect of tip spacing, thrust coefficient and turbine spacing in multi-rotor wind turbines and farms
Cluster wakes impact on a far-distant offshore wind farm's power
A double-multiple streamtube model for vertical axis wind turbines of arbitrary rotor loading
How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine
Multi-lidar wind resource mapping in complex terrain
On the self-similarity of wind turbine wakes in a complex terrain using large eddy simulation
Adjoint-based calibration of inlet boundary condition for atmospheric computational fluid dynamics solvers
Wind turbine load dynamics in the context of turbulence intermittency
Improving mesoscale wind speed forecasts using lidar-based observation nudging for airborne wind energy systems
Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland
Decreasing Wind Speed Extrapolation Error via Domain-Specific Feature Extraction and Selection
Significant multidecadal variability in German wind energy generation
First identification and quantification of detached-tip vortices behind a wind energy converter using fixed-wing unmanned aircraft system
Lidar estimation of rotor-effective wind speed – an experimental comparison
Detection of wakes in the inflow of turbines using nacelle lidars
Detection and characterization of extreme wind speed ramps
Extreme wind fluctuations: joint statistics, extreme turbulence, and impact on wind turbine loads
More accurate aeroelastic wind-turbine load simulations using detailed inflow information
Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm
Low-level jets over the North Sea based on ERA5 and observations: together they do better
Brief communication: Wind inflow observation from load harmonics – wind tunnel validation of the rotationally symmetric formulation
Micro-scale model comparison (benchmark) at the moderately complex forested site Ryningsnäs
Experimental validation of a ducted wind turbine design strategy
Near-wake analysis of actuator line method immersed in turbulent flow using large-eddy simulations
Assessing variability of wind speed: comparison and validation of 27 methodologies
Do wind turbines pose roll hazards to light aircraft?
Analysis of control-oriented wake modeling tools using lidar field results
Does the wind turbine wake follow the topography? A multi-lidar study in complex terrain
Interannual variability of wind climates and wind turbine annual energy production
Large-eddy simulation sensitivities to variations of configuration and forcing parameters in canonical boundary-layer flows for wind energy applications
From standard wind measurements to spectral characterization: turbulence length scale and distribution
From lidar scans to roughness maps for wind resource modelling in forested areas
Investigating the impact of atmospheric stability on thunderstorm outflow winds and turbulence
Ingrid Neunaber and Caroline Braud
Wind Energ. Sci., 5, 759–773, https://doi.org/10.5194/wes-5-759-2020, https://doi.org/10.5194/wes-5-759-2020, 2020
Short summary
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Motivated by the need for wind turbine rotor blade tests in flows with atmospheric-like properties like gusts, we present a new setup to generate strong, rapid, turbulent gusts in a wind tunnel. The setup consists of a rotating bar that cuts through the inlet of the wind tunnel which generates the gust, and it is called
the chopper. In this work, the flow generated by the chopper is characterized, and we show how the gust and its turbulence evolve downstream.
Felix Kelberlau and Jakob Mann
Wind Energ. Sci., 5, 519–541, https://doi.org/10.5194/wes-5-519-2020, https://doi.org/10.5194/wes-5-519-2020, 2020
Short summary
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Wind speeds can be measured remotely from the ground with lidars. Their estimates are accurate for mean speeds, but turbulence leads to measurement errors. We predict these errors using computer-generated data and compare lidar measurements with data from a meteorological mast. The comparison shows that deviations depend on wind direction, measurement height, and wind conditions. Our method to reduce the measurement error is successful when the wind is aligned with one of the lidar beams.
Nicola Bodini and Mike Optis
Wind Energ. Sci., 5, 489–501, https://doi.org/10.5194/wes-5-489-2020, https://doi.org/10.5194/wes-5-489-2020, 2020
Short summary
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An accurate assessment of the wind resource at hub height is necessary for an efficient and bankable wind farm project. Conventional techniques for wind speed vertical extrapolation include a power law and a logarithmic law. Here, we propose a round-robin validation to assess the benefits that a machine-learning-based approach can provide in vertically extrapolating wind speed at a location different from the training site – the most practically useful application for the wind energy industry.
James B. Duncan Jr., Brian D. Hirth, and John L. Schroeder
Wind Energ. Sci., 5, 469–488, https://doi.org/10.5194/wes-5-469-2020, https://doi.org/10.5194/wes-5-469-2020, 2020
Short summary
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Results highlight some of the complexities associated with executing and analyzing wind plant control at full scale using brief experimental control periods. Some difficulties include (1) the ability to accurately implement the desired control changes on smaller timescales, (2) identifying reliable data sources and methods to quantify these control changes, and (3) attributing variations in wake structure to turbine control changes rather than a response to the underlying atmospheric conditions.
Rolf-Erik Keck and Niklas Sondell
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-62, https://doi.org/10.5194/wes-2020-62, 2020
Revised manuscript accepted for WES
Short summary
Short summary
A method for performing numerical wind resource assessments in the absence of on-site measurements is presented and validated against field measurements. Numerical wind resource assessment is at least two orders of magnitude faster and less expensive than using conventional site measurements. This enables analysis of a larger number of projects and thereby increase the chances of discovering the best available sites. The uncertainty in mean wind speed predictions is found to be about 4 %.
Jonas Kazda and Jakob Mann
Wind Energ. Sci., 5, 439–450, https://doi.org/10.5194/wes-5-439-2020, https://doi.org/10.5194/wes-5-439-2020, 2020
Short summary
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This work presents the first analytical solution for the quantification of the spatial variance of the second-order moment of correlated wind speeds. The spatial variance is defined as random differences in the sample variance of wind speed between different points in space. The approach is successfully verified using simulation and field data. The impact of the spatial variance on wind farm control, the verification of wind turbine performance and sensor verification are then investigated.
Mathias Møller, Piotr Domagalski, and Lars Roar Sætran
Wind Energ. Sci., 5, 391–411, https://doi.org/10.5194/wes-5-391-2020, https://doi.org/10.5194/wes-5-391-2020, 2020
Short summary
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This work has analyzed historical data of 10 min averaged wind speed measurements to investigate the accuracy of the commonly used equations for describing the wind velocity as a function of the height above ground. The results of analyzing data from a wide range of sites show that the common equations do not sufficiently describe certain physical phenomena, especially at offshore and coastal locations. The results imply that there is a need for more advanced models.
Charlotte B. Hasager, Andrea N. Hahmann, Tobias Ahsbahs, Ioanna Karagali, Tija Sile, Merete Badger, and Jakob Mann
Wind Energ. Sci., 5, 375–390, https://doi.org/10.5194/wes-5-375-2020, https://doi.org/10.5194/wes-5-375-2020, 2020
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Europe's offshore wind resource mapping is part of the New European Wind Atlas (NEWA) international consortium effort. This study presents the results of analysis of synthetic aperture radar (SAR) ocean wind maps based on Envisat and Sentinel-1 with a brief description of the wind retrieval process and Advanced Scatterometer (ASCAT) ocean wind maps. Furthermore, the Weather Research and Forecasting (WRF) offshore wind atlas of NEWA is presented.
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
Short summary
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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.
Paul Hulsman, Søren Juhl Andersen, and Tuhfe Göçmen
Wind Energ. Sci., 5, 309–329, https://doi.org/10.5194/wes-5-309-2020, https://doi.org/10.5194/wes-5-309-2020, 2020
Short summary
Short summary
We aim to develop fast and reliable surrogate models for yaw-based wind farm control. The surrogates, based on polynomial chaos expansion, are built using high-fidelity flow simulations combined with aeroelastic simulations of the turbine performance and loads. Optimization results performed using two Vestas V27 turbines in a row for a specific atmospheric condition suggest that a power gain of almost 3 % ± 1 % can be achieved at close spacing by yawing the upstream turbine more than 15°.
Erik Quaeghebeur and Michiel B. Zaaijer
Wind Energ. Sci., 5, 285–308, https://doi.org/10.5194/wes-5-285-2020, https://doi.org/10.5194/wes-5-285-2020, 2020
Short summary
Short summary
Meteorological and oceanic datasets are fundamental to the modeling of offshore wind farms. Data quality issues in one such dataset led us to conduct a study to establish whether such issues are more generally present in these datasets. The answer is yes and users should be aware of this. We therefore also investigated how such issues can be avoided. The result is a set of techniques and recommendations for dataset producers, leading to substantial quality improvements with limited extra effort.
Davide Conti, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-8, https://doi.org/10.5194/wes-2020-8, 2020
Revised manuscript accepted for WES
Short summary
Short summary
We propose a method for carrying out wind turbine load validation in wake conditions using measurements from forward-looking nacelle lidars. The uncertainty and bias of aero-elastic load and power predictions are 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.
Joseph C. Y. Lee, Peter Stuart, Andrew Clifton, M. Jason Fields, Jordan Perr-Sauer, Lindy Williams, Lee Cameron, Taylor Geer, and Paul Housley
Wind Energ. Sci., 5, 199–223, https://doi.org/10.5194/wes-5-199-2020, https://doi.org/10.5194/wes-5-199-2020, 2020
Short summary
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This work summarizes the results of the intelligence-sharing initiative of the Power Curve Working Group. Participants in this share exercise applied a handful of selected power curve modeling correction methods on their power performance test data, and they submitted the results for the coauthors to analyze. In this paper, we describe the share exercise, explain the analysis methodologies, and perform statistical tests to evaluate the correction methods in various inflow conditions.
Christian Behnken, Matthias Wächter, and Joachim Peinke
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-5, https://doi.org/10.5194/wes-2020-5, 2020
Revised manuscript accepted for WES
Short summary
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We extend the common characterisation and modelling of wind time series with respect to higher order statistics. We present an approach which enables to get hold of the general multipoint statistics of wind times series measured. This work is an important step in a more comprehensive description of wind including also extreme events. Important is that we show how stochastic equations can be derived form measured wind data which can be used to model long time series.
Alain Schubiger, Sarah Barber, and Henrik Nordborg
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-106, https://doi.org/10.5194/wes-2019-106, 2020
Revised manuscript under review for WES
Short summary
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In this study, a LES simulation using the LBM framework Palabos was implemented to calculate the wind field over the complex terrain of the Bolund Hill.
The results were compared to RANS and DES simulations using ANSYS Fluent and field measurements. The computational costs of these three models were compared and it has been shown that LBM, even in this not-yet fully optimised set-up of the simulation, can perform 5 times faster than DES and lead to reasonably accurate results.
Yasir Shkara, Martin Cardaun, Ralf Schelenz, and Georg Jacobs
Wind Energ. Sci., 5, 141–154, https://doi.org/10.5194/wes-5-141-2020, https://doi.org/10.5194/wes-5-141-2020, 2020
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A computational fluid dynamics (CFD) solver is coupled with a structure solver to predict the dynamic response of a horizontal axis wind turbine structure. CFD provides much more accurate and more realistic aerodynamic loads that cannot be achieved by traditional methods such as blade element momentum theory. As a result, the aeroelastic response of the wind turbine structure, taking into account blade–tower interactions, is described in more detail.
Mark Schelbergen, Peter C. Kalverla, Roland Schmehl, and Simon J. Watson
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-108, https://doi.org/10.5194/wes-2019-108, 2020
Preprint under review for WES
Short summary
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We have presented a new methodology to identify a set of characteristic wind profile shapes using clustering for estimating site specific airborne wind resource. The wind resource representation is used for fast AEP calculations for pumping AWE systems. This is necessary because the validity of conventional wind profile parametrisations, such as the logarithmic profile, is limited for the full height range in which these systems operate.
Niranjan S. Ghaisas, Aditya S. Ghate, and Sanjiva K. Lele
Wind Energ. Sci., 5, 51–72, https://doi.org/10.5194/wes-5-51-2020, https://doi.org/10.5194/wes-5-51-2020, 2020
Short summary
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Wakes of a multi-rotor wind turbine configuration are evaluated using numerical simulations. Compared to equivalent conventional single-rotor turbine wakes, multi-rotor turbine wakes are found to recover faster and generate less turbulence; thus, multi-rotor turbine wind farms are more efficient, with smaller wake losses. The benefits of multi-rotor wind farms over conventional wind farms are sensitive to tip spacing, thrust coefficient and turbine spacing.
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
Short summary
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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.
Anis A. Ayati, Konstantinos Steiros, Mark A. Miller, Subrahmanyam Duvvuri, and Marcus Hultmark
Wind Energ. Sci., 4, 653–662, https://doi.org/10.5194/wes-4-653-2019, https://doi.org/10.5194/wes-4-653-2019, 2019
Short summary
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This work presents an improvement to a popular algorithm used in the prediction of the power of vertical axis wind turbines. While, until now, the algorithm was considered valid only for low rotor speeds and a small number of blades, our improvement makes it valid for any configuration. The predictions of the improved algorithm were found to be of considerable accuracy, when validated with measurements of a small model turbine acquired in a compressed air wind tunnel.
Patrick Murphy, Julie K. Lundquist, and Paul Fleming
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-86, https://doi.org/10.5194/wes-2019-86, 2019
Revised manuscript accepted for WES
Short summary
Short summary
We present and evaluate an improved method for predicting wind turbine power production based on measurements of the wind speed and direction profile across the rotor disk for a wind turbine in complex terrain. By comparing predictions to actual power production from a utility-scale wind turbine, we show this method is more accurate than methods based on hub-height wind speed or surface-based atmospheric characterization.
Robert Menke, Nikola Vasiljević, Johannes Wagner, Steven P. Oncley, and Jakob Mann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-85, https://doi.org/10.5194/wes-2019-85, 2019
Revised manuscript accepted for WES
Short summary
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The estimation of wind resources in complex terrain is challenging as the wind conditions change significantly over short distances, different to flat terrain where spatial changes are small. We demonstrate in this work that wind lidars can remotely map wind resources over large areas. This will have implications for the planning of wind energy projects and ultimately reduce uncertainties of wind resource estimations in complex terrain making such areas more interesting for future development.
Arslan Salim Dar, Jacob Berg, Niels Troldborg, and Edward G. Patton
Wind Energ. Sci., 4, 633–644, https://doi.org/10.5194/wes-4-633-2019, https://doi.org/10.5194/wes-4-633-2019, 2019
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We have performed computer simulations of turbulent air over hills with wind turbines located on the hill tops. Behind the wind turbines the wind speed is reduced and the air is even more turbulent. Together we call these features for the wind turbine wake. We find that the wake has a self-similar shape. This means that its shape is only a function of the reduced wind speed found in the wake and the width of the wake and hence not of the complexity and shape of the hills.
Siamak Akbarzadeh, Hassan Kassem, Renko Buhr, Gerald Steinfeld, and Bernhard Stoevesandt
Wind Energ. Sci., 4, 619–632, https://doi.org/10.5194/wes-4-619-2019, https://doi.org/10.5194/wes-4-619-2019, 2019
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The numerical flow simulation solvers are extensively used for site assessment in the wind energy industry. However, due to the complexity of flow regimes, it is essential to calibrate the important parameters of such algorithms with measurement data. In this paper, we present a computationally cheap (adjoint) solver that can be coupled with any standard gradient-based optimizer to calibrate the inflow boundary of a CFD solver using the wind speed measurements from the interior of a domain.
Carl Michael Schwarz, Sebastian Ehrich, and Joachim Peinke
Wind Energ. Sci., 4, 581–594, https://doi.org/10.5194/wes-4-581-2019, https://doi.org/10.5194/wes-4-581-2019, 2019
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This work is dedicated to the non-Gaussian statistics of wind velocity jumps and their effect on wind turbines, more specifically on fatigue loads. Wind velocity jumps are commonly simplified to behave in a Gaussian manner. This study discusses how to compare non-Gaussian to Gaussian wind fields properly and shows that the non-Gaussianity in fact can make a difference with respect to fatigue loads. Additionally, we highlight the dependence of our findings on the wind field's coherence.
Markus Sommerfeld, Martin Dörenkämper, Gerald Steinfeld, and Curran Crawford
Wind Energ. Sci., 4, 563–580, https://doi.org/10.5194/wes-4-563-2019, https://doi.org/10.5194/wes-4-563-2019, 2019
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Airborne wind energy systems aim to operate at altitudes above conventional wind turbines where reliable high-resolution wind data are scarce. Wind measurements and computational simulations both have advantages and disadvantages when assessing the wind resource at such heights. This article investigates whether assimilating measurements into the model generates a more accurate wind data set up to 1100 m. These wind data sets are used to estimate optimal AWES operating altitudes and power.
Louis de Montera, Tiny Remmers, Cian Desmond, and Ross O'Connell
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-49, https://doi.org/10.5194/wes-2019-49, 2019
Preprint under review for WES
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This paper provides a validation of satellite acquired wind speed measurements (Sentinel-1 Synthetic Aperture Radar Level 2 OCN) against four weather buoys and three coastal stations located around Ireland. It is shown that such satellite measurements provide a accurate assessment of long term wind resource characteristics for both coastal and far from shore locations. This work was conducted in order to allow the use of satellite data in the planning of offshore wind farms in Ireland.
Daniel Vassallo, Raghavendra Krishnamurthy, and Harindra J. S. Fernando
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-58, https://doi.org/10.5194/wes-2019-58, 2019
Revised manuscript accepted for WES
Short summary
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Model error and uncertainty is a challenge in the wind energy industry, potentially leading to mischaracterization of millions of dollars' worth of wind resource. This paper combines meteorological knowledge with machine learning techniques, specifically artificial neural networks (ANNs), to better extrapolate wind speeds. It is found that ANNs can reduce power law extrapolation error by up to 52 % while simultaneously reducing uncertainty. A test case is shown to help decipher the ANN results.
Jan Wohland, Nour Eddine Omrani, Noel Keenlyside, and Dirk Witthaut
Wind Energ. Sci., 4, 515–526, https://doi.org/10.5194/wes-4-515-2019, https://doi.org/10.5194/wes-4-515-2019, 2019
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Wind park planning and power system design require robust wind resource information. While most assessments are restricted to the last four decades, we use centennial reanalyses to study wind energy generation variability in Germany. We find that statistically significant multi-decadal variability exists. These long-term effects must be considered when planning future highly renewable power systems. Otherwise, there is a risk of inefficient system design and ill-informed investments.
Moritz Mauz, Alexander Rautenberg, Andreas Platis, Marion Cormier, and Jens Bange
Wind Energ. Sci., 4, 451–463, https://doi.org/10.5194/wes-4-451-2019, https://doi.org/10.5194/wes-4-451-2019, 2019
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UAS systems provide in situ measurements of turbulence and wind conditions. In the presented paper, the tip vortex generated by wind energy converters (WECs) is measured by a fixed-wing UAS and compared to an analytical model as well as a literature value. The results show good agreement. The presented method is a basis for future measurement campaigns to compare UAS measurements with numerical simulations of WEC wakes.
Dominique P. Held and Jakob Mann
Wind Energ. Sci., 4, 421–438, https://doi.org/10.5194/wes-4-421-2019, https://doi.org/10.5194/wes-4-421-2019, 2019
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In this study a model of the coherence between turbine- and lidar-estimated rotor-effective wind speed (REWS) is presented. The model is compared against experimental data from two field tests using two- and four-beam nacelle-mounted lidar systems on a test turbine. The proposed model agrees better with the field data than previously used models. Also, it was shown that the advection speed can be estimated by the REWS measured by the lidar.
Dominique P. Held and Jakob Mann
Wind Energ. Sci., 4, 407–420, https://doi.org/10.5194/wes-4-407-2019, https://doi.org/10.5194/wes-4-407-2019, 2019
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In this study the capabilities of detecting wakes in the inflow of turbines by nacelle-mounted lidars are investigated. It is shown that higher turbulence levels can be measured within a wake by estimating the Doppler spectrum width. In an experimental setup all half- and full-wake situations have been identified. A correction method for the influence of the wake on the lidar system has also been proposed..
Ásta Hannesdóttir and Mark Kelly
Wind Energ. Sci., 4, 385–396, https://doi.org/10.5194/wes-4-385-2019, https://doi.org/10.5194/wes-4-385-2019, 2019
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The wind turbine safety standard includes a coherent gust model with a wind speed increase and direction change of 10 s. With the increasing rotor size of modern wind turbines this model is criticized for being uniform across these large rotors. In this study we investigate measurements of coherent gusts with a ramp-like increase in wind speed. We define a new method for ramp detection and characterization and compare it with the coherent gust model from the wind turbine safety standard.
Ásta Hannesdóttir, Mark Kelly, and Nikolay Dimitrov
Wind Energ. Sci., 4, 325–342, https://doi.org/10.5194/wes-4-325-2019, https://doi.org/10.5194/wes-4-325-2019, 2019
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We investigate large wind speed fluctuations from a 10-year period at the Danish coastal site Høvsøre. The most extreme fluctuations are not turbulent but due to larger-scale weather phenomena. We find how these fluctuations impact wind turbines using simulations. The results are then compared to an extreme turbulence model described in the wind turbine safety standards, and it is found that the loads on the different turbine components are not the same as what the standard describes.
Mads Mølgaard Pedersen, Torben Juul Larsen, Helge Aagaard Madsen, and Gunner Christian Larsen
Wind Energ. Sci., 4, 303–323, https://doi.org/10.5194/wes-4-303-2019, https://doi.org/10.5194/wes-4-303-2019, 2019
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In this paper, detailed inflow information extracted from measurements is used to improve the accuracy of simulated wind turbine fatigue loads. Inflow information from nearby met masts is utilised as well as information from a blade-mounted flow sensor in combination with a method to compensate for the disturbance to the flow caused by the presence of the wind turbine.
Thomas Duc, Olivier Coupiac, Nicolas Girard, Gregor Giebel, and Tuhfe Göçmen
Wind Energ. Sci., 4, 287–302, https://doi.org/10.5194/wes-4-287-2019, https://doi.org/10.5194/wes-4-287-2019, 2019
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Wind turbine wake recovery is very sensitive to ambient atmospheric conditions. This paper presents a way of including a local turbulence intensity estimation from SCADA into the Jensen wake model to improve its accuracy. This new model procedure is used to optimize power production of an operating wind farm and shows that some gains can be expected even if uncertainties remain high. These optimized settings are to be implemented in a field test campaign in the scope of the SMARTEOLE project.
Peter C. Kalverla, James B. Duncan Jr., Gert-Jan Steeneveld, and Albert A. M. Holtslag
Wind Energ. Sci., 4, 193–209, https://doi.org/10.5194/wes-4-193-2019, https://doi.org/10.5194/wes-4-193-2019, 2019
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A common assumption in the design of wind turbines and wind farms is that the wind field is quite uniform. This assumption is violated during so-called low-level jet events, when there is a distinct peak in the wind speed. Low-level jets modify loads on the turbines and also affect power production. To understand their impact and facilitate better planning and design, we present a detailed climatology of these events over the North Sea, based on offshore measurements and meteorological models.
Marta Bertelè, Carlo L. Bottasso, and Stefano Cacciola
Wind Energ. Sci., 4, 89–97, https://doi.org/10.5194/wes-4-89-2019, https://doi.org/10.5194/wes-4-89-2019, 2019
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This paper describes a new formulation for estimating the wind
inflow at the rotor disk, based on measurements of the blade loads.
The new method improves on previous formulations by exploiting the
rotational symmetry of the problem. Experimental results obtained
with an aeroelastically scaled model in a boundary layer wind
tunnel are used for validating the proposed approach.
Stefan Ivanell, Johan Arnqvist, Matias Avila, Dalibor Cavar, Roberto Aurelio Chavez-Arroyo, Hugo Olivares-Espinosa, Carlos Peralta, Jamal Adib, and Björn Witha
Wind Energ. Sci., 3, 929–946, https://doi.org/10.5194/wes-3-929-2018, https://doi.org/10.5194/wes-3-929-2018, 2018
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This article describes a study in which modellers were challenged to compute the wind at a forested site with moderately complex topography. The target was to match the measured wind profile at one exact location for three directions. The input to the models consisted of detailed information on forest densities and ground height. Overall, the article gives an overview of how well different types of models are able to capture the flow physics at a moderately complex forested site.
Benjamin Kanya and Kenneth D. Visser
Wind Energ. Sci., 3, 919–928, https://doi.org/10.5194/wes-3-919-2018, https://doi.org/10.5194/wes-3-919-2018, 2018
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The energy capture of a wind turbine can be improved by completely surrounding it with an airfoil-shaped duct. This paper describes a new modeling strategy used to design an experimental 2.5 m ducted turbine, tested at the University of Waterloo wind turbine test facility. The wind tunnel data validated the predicted performance, indicating that the ducted turbine produced more than twice the power output of a conventional turbine design of the same size. Design implications are also discussed.
Jörn Nathan, Christian Masson, and Louis Dufresne
Wind Energ. Sci., 3, 905–917, https://doi.org/10.5194/wes-3-905-2018, https://doi.org/10.5194/wes-3-905-2018, 2018
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The interaction between wind turbines through their wakes is an important aspect of the conception and operation of a wind farm. Wakes are characterized by an elevated turbulence level and a noticeable velocity deficit which causes a decrease
in energy output and fatigue on downstream turbines. In order to gain a better understanding of this phenomenon, this work uses large-eddy simulations together with an actuator line model and different ambient turbulences.
Joseph C. Y. Lee, M. Jason Fields, and Julie K. Lundquist
Wind Energ. Sci., 3, 845–868, https://doi.org/10.5194/wes-3-845-2018, https://doi.org/10.5194/wes-3-845-2018, 2018
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To find the ideal way to quantify long-term wind-speed variability, we compare 27 metrics using 37 years of wind and energy data. We conclude that the robust coefficient of variation can effectively assess and correlate wind-speed and energy-production variabilities. We derive adequate results via monthly mean data, whereas uncertainty arises in interannual variability calculations. We find that reliable estimates of wind-speed variability require 10 ± 3 years of monthly mean wind data.
Jessica M. Tomaszewski, Julie K. Lundquist, Matthew J. Churchfield, and Patrick J. Moriarty
Wind Energ. Sci., 3, 833–843, https://doi.org/10.5194/wes-3-833-2018, https://doi.org/10.5194/wes-3-833-2018, 2018
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Wind energy development has increased rapidly in rural locations of the United States, areas that also serve general aviation airports. The spinning rotor of a wind turbine creates an area of increased turbulence, and we question if this turbulent air could pose rolling hazards for light aircraft flying behind turbines. We analyze high-resolution simulations of wind flowing past a turbine to quantify the rolling risk and find that wind turbines pose no significant roll hazards to light aircraft.
Jennifer Annoni, Paul Fleming, Andrew Scholbrock, Jason Roadman, Scott Dana, Christiane Adcock, Fernando Porte-Agel, Steffen Raach, Florian Haizmann, and David Schlipf
Wind Energ. Sci., 3, 819–831, https://doi.org/10.5194/wes-3-819-2018, https://doi.org/10.5194/wes-3-819-2018, 2018
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This paper addresses the modeling aspect of wind farm control. To implement successful wind farm controls, a suitable model has to be used that captures the relevant physics. This paper addresses three different wake models that can be used for controls and compares these models with lidar field data from a utility-scale turbine.
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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This study investigates the behaviour of wind turbine wakes in complex terrain. Using six scanning lidars, we measured the wake of a single turbine at the Perdigão site in Portugal in 2015. Our findings show that wake propagation is highly dependent on the atmospheric stability, which is mostly ignored in flow simulation used for wind farm layout design. The wake is lifted up during unstable atmospheric conditions and follows the terrain downwards during stable conditions.
Sara C. Pryor, Tristan J. Shepherd, and Rebecca J. Barthelmie
Wind Energ. Sci., 3, 651–665, https://doi.org/10.5194/wes-3-651-2018, https://doi.org/10.5194/wes-3-651-2018, 2018
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The interannual variability (IAV) of annual energy production (AEP) from wind turbines due to IAV in wind speeds from proposed wind farms plays a key role in dictating project financing but is only poorly constrained. This study provides improved quantification of IAV over eastern N. America using purpose-performed long-term numerical simulations. It may be appropriate to reduce the IAV applied to preconstruction AEP estimates, which would decrease the cost of capital for wind farm developments.
Jeffrey D. Mirocha, Matthew J. Churchfield, Domingo Muñoz-Esparza, Raj K. Rai, Yan Feng, Branko Kosović, Sue Ellen Haupt, Barbara Brown, Brandon L. Ennis, Caroline Draxl, Javier Sanz Rodrigo, William J. Shaw, Larry K. Berg, Patrick J. Moriarty, Rodman R. Linn, Veerabhadra R. Kotamarthi, Ramesh Balakrishnan, Joel W. Cline, Michael C. Robinson, and Shreyas Ananthan
Wind Energ. Sci., 3, 589–613, https://doi.org/10.5194/wes-3-589-2018, https://doi.org/10.5194/wes-3-589-2018, 2018
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This paper validates the use of idealized large-eddy simulations with periodic lateral boundary conditions to provide boundary-layer flow quantities of interest for wind energy applications. Sensitivities to model formulation, forcing parameter values, and grid configurations were also examined, both to ascertain the robustness of the technique and to characterize inherent uncertainties, as required for the evaluation of more general wind plant flow simulation approaches under development.
Mark Kelly
Wind Energ. Sci., 3, 533–543, https://doi.org/10.5194/wes-3-533-2018, https://doi.org/10.5194/wes-3-533-2018, 2018
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This paper shows how a definitive part of the commonly used Mann (1994) atmospheric turbulence model (its so-called eddy lifetime) implies that the model parameters can be directly related to typical measurements in wind energy projects. Most importantly, the characteristic turbulence length scale is found in terms of commonly measured (10 min mean) quantities (shear and standard deviation of wind speed); this estimator is found to give useful results, over different sites and flow regimes.
Rogier Floors, Peter Enevoldsen, Neil Davis, Johan Arnqvist, and Ebba Dellwik
Wind Energ. Sci., 3, 353–370, https://doi.org/10.5194/wes-3-353-2018, https://doi.org/10.5194/wes-3-353-2018, 2018
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Applying erroneous boundary conditions (surface roughness) for wind flow modelling can have a large impact on the estimated performance of wind turbines, particularly in forested areas. Traditionally the estimation of the surface roughness is based on a subjective process that requires assigning a value to each land use class in the vicinity of the wind farm. Here we propose a new method which converts lidar scans from a plane into maps that can be used for wind flow modelling.
Patrick Hawbecker, Sukanta Basu, and Lance Manuel
Wind Energ. Sci., 3, 203–219, https://doi.org/10.5194/wes-3-203-2018, https://doi.org/10.5194/wes-3-203-2018, 2018
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This study presents a measurement campaign, which consists of two nacelle-mounted lidar systems in a densely packed onshore wind farm. The aim of the campaign is to validate and improve wake models for load and power estimations in wind farms. Based on the findings from the measurements, the formulation of the wake degradation in the dynamic wake meandering model has been adjusted, so that the recalibrated model coincides very well with the measurements and thereby reduces the uncertainties.
This study presents a measurement campaign, which consists of two nacelle-mounted lidar systems...
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