bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wakes in and between very large offshore arrays
Authors: Pryor S.C. , Barthelmie R.J. , Shepherd T.J. , Hahmann A.N. , Garcia Santiago O.M. 
Published: June 2022

Abstract
Projected power output and wake extents are presented from new simulations with the Weather Research and Forecasting (WRF) model v4.2.2 for the large offshore wind energy lease areas along the U.S. east coast. These simulations assume nearly 2000 IEA 15 MW reference turbines are deployed with a spacing equal to the mean of smaller European offshore wind farms (7.7 rotor diameters). Results show marked differences across two wind farm parameterizations. Generally, the modified Fitch parameterization (wherein TKE generation by the rotor has been decreased) generates lower power production estimates, and more spatially extensive and deeper wind farm wakes than are manifest in output from the Explicit Wake Parameterization (EWP). For example, under conditions of moderate freestream wind speeds (∼ 4-10 ms−1 at hub-height) and turbulent kinetic energy (TKE ∼ 0.2 to 1 m2s−2), cumulative power output (summed over all 15 lease areas) is substantially greater (∼ 25% higher) in output from EWP than Fitch. These differences have real implications for power production and thus both expected revenues and grid integration. The cumulative power production and mean normalized wake extent also exhibit sensitivity to the order in which the overlapping inner domains are computed and the number of inner domains. This effect is smaller than differences from two wind farm parameterizations. Analyses focusing on the seven adjoining lease areas south of Massachusetts indicate differences in the two schemes are magnified over the largest offshore wind clusters (with expected installed capacity of > 10 GW and spatial extent of 3675 km2).
Large eddy simulation of an onshore wind farm under different operating regimes including topographic effects
Authors: Draper M , López B , Maiuri D , Decaro C , Campagnolo F 
Published: June 2022

AbstractHigh-fidelity simulations of actual wind farms with the Actuator Line Model, in a Large Eddy Simulation framework, have been performed in the past years, for both onshore and offshore sites. It has become the state of the art to simulate the wind flow through wind turbines and wind farms and it could be a powerful tool to assess the operation of actual wind farms and potential improvements. The objective of the present paper is two-fold: develop a high-fidelity numerical model of an onshore wind farm to be used to assess the influence of different environmental and aerodynamic conditions in its power performance and analyze, as case study, the effect of the topography in the wind flow and power production.
Effects of self-induced gravity waves on finite wind-farm operations using a large-eddy simulation framework
Authors: Lanzilao Luca , Meyers Johan 
Published: June 2022

Abstract
In the present study, we use large-eddy simulation (LES) to investigate how a capping inversion in combination with a stable free atmosphere influences the flow development and energy extraction in a large finite wind farm with a staggered and aligned layout. In the conventionally neutral boundary layer (CNBL), we find that gravity waves induce an unfavourable pressure gradient in the induction region of the farm which contributes to the upstream blockage, decreasing the available energy for first-row turbines. However, a favourable pressure gradient establishes through the farm in such conditions, which redistributes the energy and enhances wake recovery. These results are compared with a farm operating in the neutral boundary layer (NBL). Here, we find that only hydrodynamic effects induced by the turbines drag play a role, which cause minor pressure perturbations across the domain. For the selected atmospheric conditions, the power losses generated by the upstream blockage are balanced by the enhanced wake recovery promoted by the favourable pressure gradient throughout the farm. Consequently, the staggered farm efficiency in the CNBL is 8.8% higher than in the NBL. We note that this difference in efficiency is slightly enhanced by the 0.5? difference in wind direction at the location of the first-row turbines between the CNBL and NBL cases, which is caused by the presence of flow blockage. Since both simulations are forced with an equal turbulent velocity profile, the variation in performance is solely caused by the different vertical temperature profiles in the main domain. Finally, the staggered layout leads to a slightly stronger flow blockage than the aligned one when both farms operate in the CNBL.
Wind Farm Inflow Wind Simulation based on Mesoscale and Microscale Coupling
Authors: Zhang Zhaoyu , Bakhoday-Paskyabi Mostafa , Schito Paolo , Reuder Joachim , Zasso Alberto 
Published: June 2022

Abstract
Inflow wind simulation is a critical issue that dominates the wind farm design regarding the actual wind environment. Different from traditional real measurement based wind simulation, this paper proposed a mesoscale and microscale coupling strategy, which applies the forecasting information from WRF model to the LES model based SOWFA. Firstly, an offline coupling strategy is implemented with the modular software interface between WRF and SOWFA. The wind speed, potential temperature and pressure data are converted from Geographic Coordinate to Cartesian coordinate that is a readable format to SOWFA. Then, the simulation domain is selected in daytime for neutral ABL condition at a 1km×1km region where the wind information from WRF is interpolated and averaged at center point with 100m height. Time-series ABL conditions are extracted from center point and force the SOWFA internal solver to simulate the same environment with predictive data. The mesoscale lacked information, turbulence, is generated by periodically running precursor with the surface roughness and boundary conditions. Finally, the comparison between WRF exacted data and SOWFA output verifies the coupling strategy. The result shows that the mesoscale and microscale coupling has high fidelity and accuracy simulation at stable ABL conditions and slow-changing wind environments. This work provides a low cost and reliable data source which allows the inflow wind simulation to have the predictive ability for actual wind.
Tuning of an engineering wind farm model using measurements from Large Eddy Simulations
Authors: Sood Ishaan , Meyers Johan 
Published: June 2022

Abstract
In this work, we develop a model tuning framework to calibrate analytical wind farm models by using virtual measurements from Large Eddy Simulations (LES). A Gaussian wake deficit model coupled with a recursive wake merging methodology is utilized to simulate different inflow conditions through a virtual wind farm, which has been previously used in a suite of LES to providing a reference wind farm database. Using velocity and power measurements from the reference database, a ridge regression based calibration is conducted for the wake model parameters. Without calibration, large errors up to 20% initially persisted between the analytical model and LES for the same inflow conditions, which were subsequently observed to reduce below 6% after model tuning. The tuned models were then used to analyze farm performance for cases with optimal wake steering set points, and it was observed that the predicted gains were in better accordance with LES results.
Hybrid use of an observer-based minute-scale power forecast and persistence
Authors: Theuer F , Schneemann J , van Dooren M F , von Bremen L , Kühn M 
Published: June 2022

Abstract
Lidar-based minute-scale wind power forecasts are valuable to support grid stability and electricity trading. Current methodologies are able to outperform the benchmark persistence only during transient situations and unstable stratification. So far, methods that extend lidar-based forecasts to observer-based forecasts by embedding turbine operational data are not able to outperform persistence during stable atmospheric conditions either. In this paper we therefore analyse the complementary use of an observer-based power forecast and persistence. To do so, we implemented two hybrid approaches: The first is based on a binary decision algorithm, while the second is weighting the two methods by minimizing a cost function. We evaluated 5-minute-ahead deterministic power forecasts of the hybrid and individual models at an offshore wind farm and found the weighting approach to be most skillful. Further, the data set was extended to represent the atmospheric conditions on site for an entire typical year. The weighting approach outperformed the binary decision algorithm for both the 5-minute sample forecasts and the one year-long data set. We discuss the advantages and disadvantages of the two hybrid models and conclude that the weighting approach is the better choice. Further, it can be concluded that also when evaluating the forecasts over a longer period, in this case one year, the additional use of observer-based forecasts is beneficial compared to solely relying on persistence.
Turbine-level clustering for improved short-term wind power forecasting
Authors: González Sopeña J M , Maury C , Pakrashi V , Ghosh B 
Published: June 2022

AbstractAt the present time, new types of data are collected at a turbine level, and can be used to enhance the skill of short-term wind power forecasts. In particular, high resolution measurements such as wind power and wind speed are gathered using SCADA systems. These data can be used to build turbine-tailored forecasting models, but at a higher computational cost to predict the production of the overall wind farm compared to a single farm-level model. Thus, we explore the potential of the DBSCAN clustering algorithm to group wind turbines and build forecasting models at a cluster-level to find a middle ground between forecasting accuracy and computational cost. The proposed approach is evaluated using SCADA data collected in two Irish wind farms.
Handling Individual Pitch Control within an Actuator Disk framework: verification against the Actuator Line method and application to wake interaction problems
Authors: Moens M. , Coquelet M. , Trigaux F. , Chatelain P. 
Published: June 2022

Abstract
The present study aims at assessing the Actuator Disk (AD) method supplemented with an Individual Pitch Control (IPC) strategy, at a resolution appropriate for the Large Eddy Simulation of large wind farms. The IPC scheme is based on a state-of-the art individual pitch control, generalized to be applied to an AD approach. This procedure also requires an accurate recovery of the flapwise bending moment on each blade, which is not trivial for a disk-type model. In order to compute flapwise moments on each blade, blade trajectories are reproduced through the disk and the AD aerodynamic forces are interpolated onto these virtual blades at each time step. We verify the AD model with IPC in simulations of an isolated wind turbine, for different wind speeds and turbulence intensities, and in a configuration with two rotors. We compare the AD statistics with those obtained using an Actuator Line (AL) method. The comparison done in terms of equivalent moment shows that the AD and AL simulations produce very similar results.
Effectiveness of dynamic induction control strategies on the wake of a wind turbine
Authors: Montenegro Montero M , Arcari V , Cacciola S , Croce A 
Published: June 2022

Abstract
Dynamic Induction Control (DIC) has been recently proposed as means for enhancing wake recovery and, in turn, for increasing the overall produced power. A faster wake recovery is triggered by a Periodic Collective Motion (PCM), following a single sine function (S-PCM), or by a combination of Gaussian functions (G-PCM). Both techniques are associated with power gains in simple two- or three-turbine farms, but entail an increase in machine loading. A technique named the Helix approach generates a dynamic induction through a thrust that varies in direction but not in magnitude, reducing the tower loading. This work aims to analyse the impact of bluff bodies, such as nacelle and tower on the performances of PCD techniques, and to quantify the DIC impact on the loads. A 5 MW reference wind turbine is used for the model, implemented in OpenFAST and SOWFA to perform large-eddy simulations (LES). The results obtained at a distance of 3D downstream, show less evidence of the bluff bodies using the PCM than the baseline, as an effect of the increased in-wake mixing. In a two-turbine wind farm with a separation of 3D between turbines, this effect leads to an increment in the overall power output of the farm, despite the presence of the tower and nacelle. The blockage itself does not seem to hamper the effectiveness of DIC. In both cases, DIC is responsible for an increment of about 7% in the overall power output.
Active power control of wind farms: an instantaneous approach on waked conditions
Authors: Gonzalez Silva Jean , Matthijs Doekemeijer Bart , Ferrari Riccardo , Wingerden Jan-Willem van 
Published: June 2022

Abstract
This paper presents a closed-loop controller for wind farms to provide active power control services using a high-fidelity computational fluid dynamics based wind plant simulator. The proposed design enhances power tracking stability and allows for simple understanding, where each turbine is considered as a pure time-delay system. The paper investigates the control performance with different nominal power distributions in a fully waked condition and limited power availability. Results demonstrate the improvement in power production obtained by closing the control loop, compared to greedy operation. Additionally, power tracking capabilities are enhanced with a nominal power distribution favored by axial-induction, as well as the occurrence of turbine saturation and the distribution of loads.
Wind turbine power performance characterization through aeroelastic simulations and virtual nacelle lidar measurements
Authors: Sebastiani Alessandro , Peña Alfredo , Troldborg Niels 
Published: June 2022

Abstract
The power performance of a wind turbine depends on several characteristics of the inflow, such as wind speed, turbulence and wind shear. Additionally, wind turbine control strategies affect the power performance of the wind turbines; under certain conditions one might want to, e.g., intentionally misalign the turbine with respect to the main wind direction. Here, we evaluate whether the accuracy in power performance evaluation can be improved by using multi-dimensional power curves in the form of multivariate polynomial regressions, which define the power output as function of wind speed, turbulence and yaw misalignment. The analysis is conducted on a dataset of virtual power performance measurements, which is generated through aeroelastic simulations combined with a simulator of nacelle lidar measurements. Results show that the multi-dimensional power curves can provide higher accuracy than those derived using the IEC standard for power curve measurements; the error in power prediction is nearly halved compared to that using the IEC standard power curve method. Additionally, we show that nacelle lidar measurements increase the accuracy of the multi-dimensional power curves when compared to using mast-based anemometer measurements.
Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling
Authors: Jayaraman Balaji , Quon Eliot , Li Jing , Chatterjee Tanmoy 
Published: June 2022

Abstract
This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.
Evaluation of a Wind Field Parametrisation Methodology for Lidar-Measured Wind Turbine Inflow
Authors: van Dooren M F , Kühn M 
Published: June 2022

Abstract
There are different methods for the reconstruction of wind fields from lidar measurements, either expressing the wind condition as a set of global parameters, or by 2D or 3D wind vector reconstruction. In this work, we propose a four-parameter wind field parametrisation model as a further development of the three-parameter model introduced by Kapp and Kühn (2014, 2017), which includes a rotor-equivalent wind speed, the horizontal inclination angle of the wind with respect to the measurement plane, a wind shear exponent and a turbulence parameter. In our approach, the turbulence parameter is based on the spatial variations with respect to the rotor-equivalent wind speed over the measurement plane. The model is evaluated by applying it on a spatially and temporally highly resolved SpinnerLidar data set, measured from the nacelle of a wind turbine situated in flat terrain, with a met mast data set for comparison. First results show a good correlation for the rotor-equivalent wind speed and the horizontal inclination, however, a poor fit of the exponential shear. The turbulence parameter follows a physically different definition than the common definition of turbulence intensity, however, the analysis shows that they are weakly correlated with each other. Overall, the model shows potential, but must be further evaluated, e.g. with additional data or simulated lidar measurements within an LES wind field.
Experimental study of mean and turbulent velocity fields in the wake of a twin-rotor vertical axis wind turbine
Authors: van der Deijl W. , Obligado M. , Sicot C. , Barre S. 
Published: June 2022

Abstract
The wake of a twin-rotor vertical axis wind turbine (VAWT) was measured experimentally in a wind tunnel using particle image velocimetry. Only the horizontal centre plane was measured, showing that there is no wake recovery in this central plane. The wake deficit in this plane actually increases up to x = 5.5D, independent of tip-speed-ratio. The wake of a VAWT is, therefore, not homogeneous but three-dimensional. Which also means that the aspect ratio of a VAWT is an important parameter if one wants to optimise for wake recovery. In addition, the shed vortices at the edge of the wake do not play a role in the wake recovery. They do not enhance the recovery, nor do they shield the wake from re-energising. A reason for this is that their persistence strongly depends on tip-speed-ratio yet them breaking down has no effect on the wake recovery. Furthermore, the turbulence intensity levels at the edge of the wake are relatively low and often lower than the centre part of the wake. Hence, the dominant process of wake recovery of a VAWT must be happening in the vertical plane, which is in correspondence with previous research.
Tailoring wind turbine wake models to incoming free-stream turbulence
Authors: Gambuzza Stefano , Ganapathisubramani Bharathram 
Published: June 2022

Abstract
Analytical wake models describe the main wake statistics using a reduced number of parameters: for instance, the Gaussian wake model relies on the single parameter k
∗ to predict the mean wake velocity. However, the robustness of these models to different inflows has been seldom tested and the effects of ambient turbulence on these coefficients are reported only in a limited number of studies.
With this objective, we measured the wake generated by a model-scale wind turbine operating in a wind tunnel at a ReD
⋍ 105 under different ambient conditions, with turbulence intensities between 3% and 12% and integral time scales between 1/10 and 10 times the convective time-scale. The wake generated by the turbine has been measured by means of planar PIV in a region spanning between 1.25 and 8.75 rotor diameters downstream of the turbine.
The results show that a description of the turbine wake with the single parameter k
∗ is not sufficient to obtain accurate predictions, while the quality of the wake estimations can be dramatically improved by introducing a virtual origin x
0. Analysis of the higher-order wake statistics shows how the former can be related to the intensity of the Reynolds shear stress in the wake, and the latter to the erratic motion of the tip-vortices.
An approach and discussion of a simulation based measurement uncertainty estimation for a floating lidar system
Authors: Bischoff Oliver , Wolken-Möhlmann Gerrit , Cheng Po Wen 
Published: June 2022

Abstract
In recent years, floating lidar systems (FLS) have been used in increasing numbers for project planning and design of offshore wind farm projects. To assess the quality of the measured data or the wind resources, an exact knowledge of the measurement uncertainty of the FLS is important. However, this is difficult because there is usually no reference measurement system at the offshore sites where FLSs are to be used to assess wind resources. In order to estimate the quality of the measurements or the measurement uncertainty for a site without a reference measurement system, in this case only measurement uncertainties from measurement campaigns or trial campaigns that have already been carried out can be used. However, the respective wind and wave conditions differ from location to location. In this respect, a direct transfer of the measurement uncertainty from one measurement location to another location is again subject to a certain uncertainty.
In this paper, we explore the possibilities of a different, simulation-based, approach. First, we discuss which parts of the measurement uncertainty of the FLS can be investigated in the context of simulations. Additionally, we present a workflow for the simulation of an FLS for different wind and wave conditions and an approach to determine and compare the simulated bin-averaged deviations for these conditions with real measurement data. Finally, we show a comparison of the simulated uncertainties with measurement uncertainties determined during a six-month measurement campaign of an FLS against an offshore measurement mast and a fixed reference lidar and give an outlook on possible further use cases of this simulation-based methodology.