Articles | Volume 5, issue 1
Wind Energ. Sci., 5, 391–411, 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: Wind Energy Science Conference 2019
30 Mar 2020
Research article | 30 Mar 2020
Comparing abnormalities in onshore and offshore vertical wind profiles
Mathias Møller et al.
No articles found.
Maciej Karczewski, Piotr Domagalski, Arnoldus van Wingerde, Bernhard Stoevesandt, Peter Jamieson, and Lars Roar Saetran
Wind Energ. Sci. Discuss.,
Revised manuscript not acceptedShort summary
The paper presents a concept of a multi-rotor system as a floating off-shore wind turbine. The results show that it may be an alternative to conventional wind turbines and even be cheaper in a long run, thus lowering the cost of energy to consumers. It may also solve technological barriers. The motivation for research was the idea of providing a technology vision for regions, where certain local supply chain can be employed to revitalize the shipyard industry while using renewable energy.
Franz Mühle, Jannik Schottler, Jan Bartl, Romain Futrzynski, Steve Evans, Luca Bernini, Paolo Schito, Martín Draper, Andrés Guggeri, Elektra Kleusberg, Dan S. Henningson, Michael Hölling, Joachim Peinke, Muyiwa S. Adaramola, and Lars Sætran
Wind Energ. Sci., 3, 883–903,
Jan Bartl, Franz Mühle, and Lars Sætran
Wind Energ. Sci., 3, 489–502,Short summary
Our experimental wind tunnel study on a pair of model wind turbines demonstrates a significant potential of turbine yaw angle control for the combined optimization of turbine power and rotor loads. Depending on the turbines' relative positions to the incoming wind, a combined power increase and individual rotor load reduction can be achieved by operating the turbine rotors slightly misaligned with the main wind direction (i.e., at a certain yaw angle).
Jan Bartl, Franz Mühle, Jannik Schottler, Lars Sætran, Joachim Peinke, Muyiwa Adaramola, and Michael Hölling
Wind Energ. Sci., 3, 329–343,Short summary
Wake steering by yawing a wind turbine offers great potential to increase the wind farm power production. A model scale experiment in a controlled wind tunnel environment has been performed to map the wake flow's complex velocity distribution for different inflow conditions. A non-uniform sheared inflow was observed to affect the wake flow only insignificantly. The level of turbulent velocity fluctuations in the inflow, however, influenced the wake's velocity distribution to a higher degree.
Jannik Schottler, Jan Bartl, Franz Mühle, Lars Sætran, Joachim Peinke, and Michael Hölling
Wind Energ. Sci., 3, 257–273,Short summary
In this work, the wake flows behind two different model wind turbines were investigated in wind tunnel experiments user laser Doppler anemometry. It was found that the width of the wake flow is significantly dependent on the quantities examined, becoming much wider when taking higher-order statistics into account. This effect is stable against yaw misalignment and thus affects not only wind farm layout optimizations but also the applicability of active wake steering methods.
Julie Krøgenes, Lovisa Brandrud, Richard Hann, Jan Bartl, Tania Bracchi, and Lars Sætran
Wind Energ. Sci. Discuss.,
Preprint withdrawnShort summary
Leading edge ice accretion causes significant performance degradation to wind power installations in cold climate areas. This study focuses on the effect of three typical ice shapes; rime ice, glaze ice and a mixed ice. Experiments were conducted in the low speed wind tunnel at NTNU and compared with ANSYS Fluent CFD analyses. Results show a reduction on lift and an increase in drag for all ice cases, most severely for the mixed ice with it's horn-like shape.
Jan Bartl and Lars Sætran
Wind Energ. Sci., 2, 55–76,Short summary
As wind turbines extract energy from the wind, a wind field of reduced wind speed and increased turbulence is left behind for the downstream turbines. For the exact calculation of the annual energy production and lifetime of wind turbines, it is therefore of great importance to be able to accurately calculate this turbulent wake flow for different wind conditions. This paper compares different computational modeling approaches with flow measurements on model turbines in a wind tunnel.
Related subject area
Wind and turbulenceWake properties and power output of very large wind farms for different meteorological conditions and turbine spacings: a large-eddy simulation case study for the German BightValidation of wind resource and energy production simulations for small wind turbines in the United StatesFour-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidarsCan reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain?The five main influencing factors for lidar errors in complex terrainMeso- to microscale modeling of atmospheric stability effects on wind turbine wake behavior in complex terrainValidation of a coupled atmospheric–aeroelastic model system for wind turbine power and load calculationsOptimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditionsDevelopment of a curled wake of a yawed wind turbine under turbulent and sheared inflowApplication of the Townsend–George theory for free shear flows to single and double wind turbine wakes – a wind tunnel studyOn the measurement of stability parameter over complex mountainous terrainField measurements of wake meandering at a utility-scale wind turbine with nacelle-mounted Doppler lidarsTurbulence statistics from three different nacelle lidarsThe 3 km Norwegian reanalysis (NORA3) – a validation of offshore wind resources in the North Sea and the Norwegian SeaOn turbulence models and lidar measurements for wind turbine controlLarge-eddy simulation of airborne wind energy farmsSeasonal effects in the long-term correction of short-term wind measurements using reanalysis dataOn the effects of inter-farm interactions at the offshore wind farm Alpha VentusSatellite-based estimation of roughness lengths and displacement heights for wind resource modellingEvaluation of the global-blockage effect on power performance through simulations and measurementsRANS modelling of a single wind turbine wake in the unstable surface layerThe smoother the better? A comparison of six post-processing methods to improve short-term offshore wind power forecasts in the Baltic SeaStatistical impact of wind-speed ramp events on turbines, via observations and coupled fluid-dynamic and aeroelastic simulationsProbabilistic estimation of the Dynamic Wake Meandering model parameters using SpinnerLidar-derived wake characteristicsDevelopment of an image processing method for wake meandering studies and its application on data sets from scanning wind lidar and large-eddy simulationRecovery processes in a large offshore wind farmExtreme wind shear events in US offshore wind energy areas and the role of induced stratificationWRF-simulated low-level jets over Iowa: characterization and sensitivity studiesCorrelations of power output fluctuations in an offshore wind farm using high-resolution SCADA dataNew methods to improve the vertical extrapolation of near-surface offshore wind speedsWind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievalsA pressure-driven atmospheric boundary layer model satisfying Rossby and Reynolds number similarityDesign and analysis of a wake model for spatially heterogeneous flowEvaluation of tilt control for wind-turbine arrays in the atmospheric boundary layerEvaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mastWind turbines in atmospheric flow: fluid–structure interaction simulations with hybrid turbulence modelingOffshore wind farm global blockage measured with scanning lidarUnderstanding and mitigating the impact of data gaps on offshore wind resource estimatesInvestigating the loads and performance of a model horizontal axis wind turbine under reproducible IEC extreme operational conditionsValidation of the dynamic wake meandering model with respect to loads and power productionMethod for airborne measurement of the spatial wind speed distribution above complex terrainAxial induction controller field test at Sedini wind farmWake redirection at higher axial inductionAn overview of wind-energy-production prediction bias, losses, and uncertaintiesUtilizing physics-based input features within a machine learning model to predict wind speed forecasting errorSet-point optimization in wind farms to mitigate effects of flow blockage induced by atmospheric gravity wavesField experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in ItalyComputational analysis of high-lift-generating airfoils for diffuser-augmented wind turbinesAeroelastic analysis of wind turbines under turbulent inflow conditionsParameterization of wind evolution using lidar
Oliver Maas and Siegfried Raasch
Wind Energ. Sci., 7, 715–739,Short summary
In the future there will be very large wind farm clusters in the German Bight. This study investigates how the wind field is affected by these very large wind farms and how much energy can be extracted by the wind turbines. Very large wind farms do not only reduce the wind speed but can also cause a change in wind direction or temperature. The extractable energy per wind turbine is much smaller for large wind farms than for small wind farms due to the reduced wind speed inside the wind farms.
Lindsay M. Sheridan, Caleb Phillips, Alice C. Orrell, Larry K. Berg, Heidi Tinnesand, Raj K. Rai, Sagi Zisman, Dmitry Duplyakin, and Julia E. Flaherty
Wind Energ. Sci., 7, 659–676,Short summary
The small wind community relies on simplified wind models and energy production simulation tools to obtain energy generation expectations. We gathered actual wind speed and turbine production data across the US to test the accuracy of models and tools for small wind turbines. This study provides small wind installers and owners with the error metrics and sources of error associated with using models and tools to make performance estimates, empowering them to adjust expectations accordingly.
Yiyin Chen, Feng Guo, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 7, 539–558,Short summary
Lidar-assisted control of wind turbines requires a wind field generator capable of simulating wind evolution. Out of this need, we extend the Veers method for 3D wind field generation to 4D and propose a two-step Cholesky decomposition approach. Based on this, we develop a 4D wind field generator – evoTurb – coupled with TurbSim and Mann turbulence generator. We further investigate the impacts of the spatial discretization in 4D wind fields on lidar simulations to provide practical suggestions.
Vincent Pronk, Nicola Bodini, Mike Optis, Julie K. Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, and Ethan Young
Wind Energ. Sci., 7, 487–504,Short summary
In this paper, we have assessed to which extent mesoscale numerical weather prediction models are more accurate than state-of-the-art reanalysis products in characterizing the wind resource at heights of interest for wind energy. The conclusions of our work will be of primary importance to the wind industry for recommending the best data sources for wind resource modeling.
Tobias Klaas-Witt and Stefan Emeis
Wind Energ. Sci., 7, 413–431,Short summary
Light detection and ranging (lidar) has become a valuable technology to assess the wind resource at hub height of modern wind turbines. However, because of their measurement principle, common lidars suffer from errors at orographically complex, i.e. hilly or mountainous, sites. This study analyses the impact of the five main influencing factors in a non-dimensional, model-based parameter study.
Adam S. Wise, James M. T. Neher, Robert S. Arthur, Jeffrey D. Mirocha, Julie K. Lundquist, and Fotini K. Chow
Wind Energ. Sci., 7, 367–386,Short summary
Wind turbine wake behavior in hilly terrain depends on various atmospheric conditions. We modeled a wind turbine located on top of a ridge in Portugal during typical nighttime and daytime atmospheric conditions and validated these model results with observational data. During nighttime conditions, the wake deflected downwards following the terrain. During daytime conditions, the wake deflected upwards. These results can provide insight into wind turbine siting and operation in hilly regions.
Sonja Krüger, Gerald Steinfeld, Martin Kraft, and Laura J. Lukassen
Wind Energ. Sci., 7, 323–344,Short summary
Detailed numerical simulations of turbines in atmospheric conditions are challenging with regard to their computational demand. We coupled an atmospheric flow model and a turbine model in order to deliver extensive details about the flow and the turbine response within reasonable computational time. A comparison to measurement data was performed and showed a very good agreement. The efficiency of the tool enables applications such as load calculation in wind farms or during low-level-jet events.
Michael F. Howland, Aditya S. Ghate, Jesús Bas Quesada, Juan José Pena Martínez, Wei Zhong, Felipe Palou Larrañaga, Sanjiva K. Lele, and John O. Dabiri
Wind Energ. Sci., 7, 345–365,Short summary
Wake steering control, in which turbines are intentionally misaligned with the incident wind, has demonstrated potential to increase wind farm energy. We investigate wake steering control methods in simulations of a wind farm operating in the terrestrial diurnal cycle. We develop a statistical wind direction forecast to improve wake steering in flows with time-varying states. Closed-loop wake steering control increases wind farm energy production, compared to baseline and open-loop control.
Paul Hulsman, Martin Wosnik, Vlaho Petrović, Michael Hölling, and Martin Kühn
Wind Energ. Sci., 7, 237–257,Short summary
Due to the possibility of mapping the wake fast at multiple locations with the WindScanner, a thorough understanding of the development of the wake is acquired at different inflow conditions and operational conditions. The lidar velocity data and the energy dissipation rate compared favourably with hot-wire data from previous experiments, lending credibility to the measurement technique and methodology used here. This will aid the process to further improve existing wake models.
Ingrid Neunaber, Joachim Peinke, and Martin Obligado
Wind Energ. Sci., 7, 201–219,Short summary
Wind turbines are often clustered within wind farms. A consequence is that some wind turbines may be exposed to the wakes of other turbines, which reduces their lifetime due to the wake turbulence. Knowledge of the wake is thus important, and we carried out wind tunnel experiments to investigate the wakes. We show how models that describe wakes of bluff bodies can help to improve the understanding of wind turbine wakes and wind turbine wake models, particularly by including a virtual origin.
Elena Cantero, Javier Sanz, Fernando Borbón, Daniel Paredes, and Almudena García
Wind Energ. Sci., 7, 221–235,Short summary
The impact of atmospheric stability on wind energy is widely demonstrated, so we have to know how to characterise it. This work based on a meteorological mast located in a complex terrain compares and evaluates different instrument set-ups and methodologies for stability characterisation. The methods are examined considering their theoretical background, implementation complexity, instrumentation requirements and practical use in connection with wind energy applications.
Peter Brugger, Corey Markfort, and Fernando Porté-Agel
Wind Energ. Sci., 7, 185–199,Short summary
Wind turbines create a wake of reduced wind speeds downstream of the rotor. The wake does not necessarily have a straight, pencil-like shape but can meander similar to a smoke plume. We investigated this wake meandering and observed that the downstream transport velocity is slower than the wind speed contrary to previous assumptions and that the evolution of the atmospheric turbulence over time impacts wake meandering on distances typical for the turbine spacing in wind farms.
Wei Fu, Alfredo Peña, and Jakob Mann
Wind Energ. Sci. Discuss.,
Revised manuscript accepted for WESShort summary
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 2 and 4 beams, respectively, measure only the fluctuation in the along-wind direction.
Ida Marie Solbrekke, Asgeir Sorteberg, and Hilde Haakenstad
Wind Energ. Sci., 6, 1501–1519,Short summary
We validate new high-resolution data set (NORA3) for offshore wind power purposes for the North Sea and the Norwegian Sea. The aim of the validation is to ensure that NORA3 can act as a wind resource data set in the planning phase for future offshore wind power installations in the area of concern. The general conclusion of the validation is that NORA3 is well suited for wind power estimates but gives slightly conservative estimates of the offshore wind metrics.
Liang Dong, Wai Hou Lio, and Eric Simley
Wind Energ. Sci., 6, 1491–1500,Short summary
This paper suggests that the impacts of different turbulence models should be considered as uncertainties while evaluating the benefits of lidar-assisted control (LAC) in wind turbine design. The value creation of LAC, evaluated using the Kaimal turbulence model, will be diminished if the Mann turbulence model is used instead. In particular, the difference in coherence is more significant for larger rotors.
Thomas Haas, Jochem De Schutter, Moritz Diehl, and Johan Meyers
Wind Energ. Sci. Discuss.,
Revised manuscript accepted for WESShort summary
In this work, we study parks of large-scale airborne wind energy systems using a virtual flight simulator. The virtual flight simulator combines numerical techniques from flow simulation and kite control. Using advanced control algorithms, the systems can operate efficiently in the park despite turbulent flow conditions. For the three configurations considered in the study, we observe significant wake effects reducing the power yield of the parks.
Alexander Basse, Doron Callies, Anselm Grötzner, and Lukas Pauscher
Wind Energ. Sci., 6, 1473–1490,Short summary
This study investigates systematic, seasonal biases in the long-term correction of short-term wind measurements (< 1 year). Two popular measure–correlate–predict (MCP) methods yield remarkably different results. Six reanalysis data sets serve as long-term data. Besides experimental results, theoretical findings are presented which link the mechanics of the methods and the properties of the reanalysis data sets to the observations. Finally, recommendations for wind park planners are derived.
Vasilis Pettas, Matthias Kretschmer, Andrew Clifton, and Po Wen Cheng
Wind Energ. Sci., 6, 1455–1472,Short summary
This study aims to quantify the effect of inter-farm interactions based on long-term measurement data from the Alpha Ventus (AV) wind farm and the nearby FINO1 platform. AV was initially the only operating farm in the area, but in subsequent years several farms were built around it. This setup allows us to quantify the farm wake effects on the microclimate of AV and also on turbine loads and operational characteristics depending on the distance and size of the neighboring farms.
Rogier Floors, Merete Badger, Ib Troen, Kenneth Grogan, and Finn-Hendrik Permien
Wind Energ. Sci., 6, 1379–1400,Short summary
Wind turbines are frequently placed in forests. We investigate the potential of using satellites to characterize the land surface for wind flow modelling. Maps of forest properties are generated from satellite data and converted to flow modelling maps. Validation is carried out at 10 sites. Using the novel satellite-based maps leads to lower errors of the power density than land cover databases, which demonstrates the value of using satellite-based land cover maps for flow modelling.
Alessandro Sebastiani, Alfredo Peña, Niels Troldborg, and Alexander Meyer Forsting
Wind Energ. Sci. Discuss.,
Revised manuscript accepted for WESShort summary
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 neighboring 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 neighboring wind turbines. Consequently, we also show how power performance testing might be biased when performed on a row of several wind turbines.
Mads Baungaard, Maarten Paul van der Laan, and Mark Kelly
Wind Energ. Sci. Discuss.,
Revised manuscript accepted for WESShort summary
A typical daytime atmosphere is modelled and used as input for a simulation of the flow around wind turbines. The flow directly behind the turbine is called the "wake" and it is very dependent on the atmospheric conditions. Therefore it is important to be able to simulate in various different atmospheric conditions, but at the same time it is desired to a have a simple model, so that the simulation can be executed fast; this is the purpose of the suggested model.
Christoffer Hallgren, Stefan Ivanell, Heiner Körnich, Ville Vakkari, and Erik Sahlée
Wind Energ. Sci., 6, 1205–1226,Short summary
As wind power becomes more popular, there is a growing demand for accurate power production forecasts. In this paper we investigated different methods to improve wind power forecasts for an offshore location in the Baltic Sea, using both simple and more advanced techniques. The performance of the methods is evaluated for different weather conditions. Smoothing the forecast was found to be the best method in general, but we recommend selecting which method to use based on the forecasted weather.
Mark Kelly, Søren Juhl Andersen, and Ásta Hannesdóttir
Wind Energ. Sci., 6, 1227–1245,Short summary
Via 11 years of measurements, we made a representative ensemble of wind ramps in terms of acceleration, mean speed, and shear. Constrained turbulence and large-eddy simulations were coupled to an aeroelastic model for each ensemble member. Ramp acceleration was found to dominate the maxima of thrust-associated loads, with a ramp-induced increase of 45 %–50 % plus ~ 3 % per 0.1 m/s2 of bulk ramp acceleration magnitude. The LES indicates that the ramps (and such loads) persist through the farm.
Davide Conti, Nikolay Dimitrov, Alfredo Peña, and Thomas Herges
Wind Energ. Sci., 6, 1117–1142,Short summary
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.
Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen
Wind Energ. Sci. Discuss.,
Revised manuscript accepted for WESShort summary
We described a new automated method to separate the wind turbine wake from the undisturbed flow. The method relies on the wind speed distribution in the measured wind field to select one specific threshold value and split the measurements into wake and background points. The purpose of the method is to reduce the amount of data required – the proposed algorithm does not need precise information on the wind speed or direction and can run on the image instead of the measured data.
Tanvi Gupta and Somnath Baidya Roy
Wind Energ. Sci., 6, 1089–1106,Short summary
Wind turbines extract momentum from atmospheric flow and convert that to electricity. This study explores recovery processes in wind farms that replenish the momentum so that wind farms can continue to function. Experiments with a numerical model show that momentum transport by turbulent eddies from above the wind turbines is the major contributor to recovery except for strong wind conditions and low wind turbine density, where horizontal advection can also play a major role.
Mithu Debnath, Paula Doubrawa, Mike Optis, Patrick Hawbecker, and Nicola Bodini
Wind Energ. Sci., 6, 1043–1059,Short summary
As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. We leverage a year of data of two floating lidars to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. We find that almost 100 independent long events occur throughout the year.
Jeanie A. Aird, Rebecca J. Barthelmie, Tristan J. Shepherd, and Sara C. Pryor
Wind Energ. Sci., 6, 1015–1030,Short summary
Low-level jets (LLJs) are pronounced maxima in wind speed profiles affecting wind turbine performance and longevity. We present a climatology of LLJs over Iowa using output from the Weather Research and Forecasting (WRF) model and determine the rotor plane conditions when they occur. LLJ characteristics are highly sensitive to the identification criteria applied, and different (unique) LLJs are extracted with each criterion. LLJ characteristics also vary with different model output resolution.
Janna Kristina Seifert, Martin Kraft, Martin Kühn, and Laura J. Lukassen
Wind Energ. Sci., 6, 997–1014,Short summary
Fluctuations in the power output of wind turbines are one of the major challenges in the integration and utilisation of wind energy. By analysing the power output fluctuations of wind turbine pairs in an offshore wind farm, we show that their correlation depends on their location within the wind farm and their inflow. The main outcome is that these correlation dependencies can be characterised by statistics of the power output of the wind turbines and sorted by a clustering algorithm.
Mike Optis, Nicola Bodini, Mithu Debnath, and Paula Doubrawa
Wind Energ. Sci., 6, 935–948,Short summary
Offshore wind turbines are huge, with rotor blades soon to extend up to nearly 300 m. Accurate modeling of winds across these heights is crucial for accurate estimates of energy production. However, we lack sufficient observations at these heights but have plenty of near-surface observations. Here we show that a basic machine-learning model can provide very accurate estimates of winds in this area, and much better than conventional techniques.
Davide Conti, Vasilis Pettas, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci., 6, 841–866,Short summary
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.
Maarten Paul van der Laan, Mark Kelly, and Mads Baungaard
Wind Energ. Sci., 6, 777–790,Short summary
Wind farms operate in the atmospheric boundary layer, and their performance is strongly dependent on the atmospheric conditions. We propose a simple model of the atmospheric boundary layer that can be used as an inflow model for wind farm simulations for isolating a number of atmospheric effects – namely, the change in wind direction with height and atmospheric boundary layer depth. In addition, the simple model is shown to be consistent with two similarity theories.
Alayna Farrell, Jennifer King, Caroline Draxl, Rafael Mudafort, Nicholas Hamilton, Christopher J. Bay, Paul Fleming, and Eric Simley
Wind Energ. Sci., 6, 737–758,Short summary
Most current wind turbine wake models struggle to accurately simulate spatially variant wind conditions at a low computational cost. In this paper, we present an adaptation of NREL's FLOw Redirection and Induction in Steady State (FLORIS) wake model, which calculates wake losses in a heterogeneous flow field using local weather measurement inputs. Two validation studies are presented where the adapted model consistently outperforms previous versions of FLORIS that simulated uniform flow only.
Wind Energ. Sci., 6, 663–675,Short summary
We deal with wake redirection, which is a promising approach designed to mitigate turbine–wake interactions which have a negative impact on the performance and lifetime of wind farms. We show that substantial power gains can be obtained by tilting the rotors of spanwise-periodic wind-turbine arrays in the atmospheric boundary layer (ABL). Optimal relative rotor sizes and spanwise spacings exist, which maximize the global power extracted from the wind.
Alfredo Peña, Branko Kosović, and Jeffrey D. Mirocha
Wind Energ. Sci., 6, 645–661,Short summary
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.
Christian Grinderslev, Niels Nørmark Sørensen, Sergio González Horcas, Niels Troldborg, and Frederik Zahle
Wind Energ. Sci., 6, 627–643,Short summary
This study investigates aero-elasticity of wind turbines present in the turbulent and chaotic wind flow of the lower atmosphere, using fluid–structure interaction simulations. This method combines structural response computations with high-fidelity modeling of the turbulent wind flow, using a novel turbulence model which combines the capabilities of large-eddy simulations for atmospheric flows with improved delayed detached eddy simulations for the separated flow near the rotor.
Jörge Schneemann, Frauke Theuer, Andreas Rott, Martin Dörenkämper, and Martin Kühn
Wind Energ. Sci., 6, 521–538,Short summary
A wind farm can reduce the wind speed in front of it just by its presence and thus also slightly impact the available power. In our study we investigate this so-called global-blockage effect, measuring the inflow of a large offshore wind farm with a laser-based remote sensing method up to several kilometres in front of the farm. Our results show global blockage under a certain atmospheric condition and operational state of the wind farm; during other conditions it is not visible in our data.
Julia Gottschall and Martin Dörenkämper
Wind Energ. Sci., 6, 505–520,
Kamran Shirzadeh, Horia Hangan, Curran Crawford, and Pooyan Hashemi Tari
Wind Energ. Sci., 6, 477–489,Short summary
Wind energy systems work coherently in atmospheric flows which are gusty. This causes highly variable power productions and high fatigue loads on the system, which together hold back further growth of the wind energy market. This study demonstrates an alternative experimental procedure to investigate some extreme wind condition effects on wind turbines based on the IEC standard. This experiment can be improved upon and used to develop new control concepts, mitigating the effect of gusts.
Inga Reinwardt, Levin Schilling, Dirk Steudel, Nikolay Dimitrov, Peter Dalhoff, and Michael Breuer
Wind Energ. Sci., 6, 441–460,Short summary
This analysis validates the DWM model based on loads and power production measured at an onshore wind farm. Special focus is given to the performance of a version of the DWM model that was previously recalibrated with a lidar system at the site. The results of the recalibrated wake model agree very well with the measurements. Furthermore, lidar measurements of the wind speed deficit and the wake meandering are incorporated in the DWM model definition in order to decrease the uncertainties.
Christian Ingenhorst, Georg Jacobs, Laura Stößel, Ralf Schelenz, and Björn Juretzki
Wind Energ. Sci., 6, 427–440,Short summary
Wind farm sites in complex terrain are subject to local wind phenomena, which are difficult to quantify but have a huge impact on a wind turbine's annual energy production. Therefore, a wind sensor was applied on an unmanned aerial vehicle and validated against stationary wind sensors with good agreement. A measurement over complex terrain showed local deviations from the mean wind speed of approx. ± 30 %, indicating the importance of an extensive site evaluation to reduce investment risk.
Ervin Bossanyi and Renzo Ruisi
Wind Energ. Sci., 6, 389–408,Short summary
This paper describes the design and field testing of a controller for reducing wake interactions on a wind farm. Reducing the power of some turbines weakens their wakes, allowing other turbines to produce more power so that the total wind farm power may increase. There have been doubts that this is feasible, but these field tests on a full-scale wind farm indicate that this goal has been achieved, also providing convincing validation of the model used for designing the controller.
Wind Energ. Sci., 6, 377–388,Short summary
In this study wake redirection and axial-induction control are combined to mitigate turbine–wake interactions, which have a negative impact on the performance and lifetime of wind farms. The results confirm that substantial power gains are obtained when overinduction is combined with tilt control. More importantly, the approach is extended to the case of yaw control, showing that large power gain enhancements are obtained by means of static overinductive yaw control.
Joseph C. Y. Lee and M. Jason Fields
Wind Energ. Sci., 6, 311–365,Short summary
This review paper evaluates the energy prediction bias in the wind resource assessment process, and the overprediction bias is decreasing over time. We examine the estimated and observed losses and uncertainties in energy production from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 standard. The considerable uncertainties call for further improvements in the prediction methodologies and more observations for validation.
Daniel Vassallo, Raghavendra Krishnamurthy, and Harindra J. S. Fernando
Wind Energ. Sci., 6, 295–309,Short summary
Machine learning is quickly becoming a commonly used technique for wind speed and power forecasting and is especially useful when combined with other forecasting techniques. This study utilizes a popular machine learning algorithm, random forest, in an attempt to predict the forecasting error of a statistical forecasting model. Various atmospheric characteristics are used as random forest inputs in an effort to discern the most useful atmospheric information for this purpose.
Luca Lanzilao and Johan Meyers
Wind Energ. Sci., 6, 247–271,Short summary
This research paper investigates the potential of thrust set-point optimization in large wind farms for mitigating gravity-wave-induced blockage effects for the first time, with the aim of increasing the wind-farm energy extraction. The optimization tool is applied to almost 2000 different atmospheric states. Overall, power gains above 4 % are observed for 77 % of the cases.
Bart M. Doekemeijer, Stefan Kern, Sivateja Maturu, Stoyan Kanev, Bastian Salbert, Johannes Schreiber, Filippo Campagnolo, Carlo L. Bottasso, Simone Schuler, Friedrich Wilts, Thomas Neumann, Giancarlo Potenza, Fabio Calabretta, Federico Fioretti, and Jan-Willem van Wingerden
Wind Energ. Sci., 6, 159–176,Short summary
This article presents the results of a field experiment investigating wake steering on an onshore wind farm. The measurements show that wake steering leads to increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions. The results suggest that further research is necessary before wake steering will consistently lead to energy gains in wind farms.
Aniruddha Deepak Paranjape, Anhad Singh Bajaj, Shaheen Thimmaiah Palanganda, Radha Parikh, Raahil Nayak, and Jayakrishnan Radhakrishnan
Wind Energ. Sci., 6, 149–157,Short summary
This project is a comparative study that takes into consideration various airfoils from the Selig, NACA, and Eppler families and models them as diffusers of the wind turbine. The efficiency of the diffuser-augmented wind turbine can be enhanced by optimizing the geometry of the diffuser shape. Their subsequent performance trends were then analyzed, and the lower-performing airfoils were systematically eliminated to leave us with an optimum design.
Giorgia Guma, Galih Bangga, Thorsten Lutz, and Ewald Krämer
Wind Energ. Sci., 6, 93–110,Short summary
With the increase in installed wind capacity, the rotor diameter of wind turbines is becoming larger and larger, and therefore it is necessary to take aeroelasticity into consideration. At the same time, wind turbines are in reality subjected to atmospheric inflow leading to high wind instabilities and fluctuations. Within this work, a high-fidelity chain is used to analyze the effects of both by the use of models of the same turbine with increasing complexity and technical details.
Yiyin Chen, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 6, 61–91,Short summary
Wind evolution is currently of high interest, mainly due to the development of lidar-assisted wind turbine control (LAC). Moreover, 4D stochastic wind field simulations can be made possible by integrating wind evolution into 3D simulations to provide a more realistic simulation environment for LAC. Motivated by these factors, we investigate the potential of Gaussian process regression in the parameterization of a two-parameter wind evolution model using data of two nacelle-mounted lidars.
FINO1: FINO1: Research platform in the North Sea, available at: https://www.fino1.de/en/, last access: 1 June 2019. a
FINO2: FINO2: Research platform in the Baltic Sea, available at: https://www.fino2.de/en/, last access: 1 June 2019. a
FINO3: FINO3: Research platform in the North Sea, available at: https://www.fino3.de/en/, last access: 1 June 2019. a
Petersen, E. L., Mortensen, N. G., Landberg, L., Højstrup, J., and Frank, H. P.: Wind power meteorology. Part I: climate and turbulence, Wind Energy, 1, 2–22, https://doi.org/10.1002/(SICI)1099-1824(199809)1:1<2::AID-WE15>3.0.CO;2-Y, 1998. a
Riedel, V., Durante, F., Neumann, T., and Strack, M.: The First Year of Measurements on the FINO1 Platform in the North Sea – Evaluation and Analysis of the Wind Profile and Assessment of the Statistical Long-Term Mean Value, DEWI Mag., 26, 37–48, 2005. a
Svensson, N., Bergstrom, H., Sahlée, E., and Rutgersson, A.: Stable atmospheric conditions over the Baltic Sea: Model evaluation and climatology, Boreal Environ. Res., 21, 387–404, 2016. a
WindEurope: Wind energy in Europe in 2018, 1, available at: https://windeurope.org/wp-content/uploads/files/about-wind/statistics/WindEurope-Annual-Statistics-2018.pdf, last access: 17 May 2019. a
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.
This work has analyzed historical data of 10 min averaged wind speed measurements to investigate...