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Wind turbines are often placed in complex terrains, where benefits from orography-related speed up can be capitalized. However, accurately modeling the wind resource over the extended areas covered by a typical wind farm is still challenging over a flat terrain, and over a complex terrain, the challenge can be even be greater. Here, a novel approach for wind resource modeling is proposed, where a linearized flow model is combined with a machine learning approach based on the k-nearest neighbor (k-NN) method. Model predictors include combinations of distance, vertical shear exponent, a measure of the terrain complexity and speedup. The method was tested by performing cross-validations on a complex site using the measurements of five tall meteorological towers. All versions of the k-NN approach yield significant improvements over the predictions obtained using the linearized model alone; they also outperform the predictions of non-linear flow models. The new method improves the capabilities of current wind resource modeling approaches, and it is easily implemented.
Pedro Quiroga-Novoa; Gabriel Cuevas-Figueroa; José Preciado; Rogier Floors; Alfredo Peña; Oliver Probst. Towards Better Wind Resource Modeling in Complex Terrain: A k-Nearest Neighbors Approach. Energies 2021, 14, 4364 .
AMA StylePedro Quiroga-Novoa, Gabriel Cuevas-Figueroa, José Preciado, Rogier Floors, Alfredo Peña, Oliver Probst. Towards Better Wind Resource Modeling in Complex Terrain: A k-Nearest Neighbors Approach. Energies. 2021; 14 (14):4364.
Chicago/Turabian StylePedro Quiroga-Novoa; Gabriel Cuevas-Figueroa; José Preciado; Rogier Floors; Alfredo Peña; Oliver Probst. 2021. "Towards Better Wind Resource Modeling in Complex Terrain: A k-Nearest Neighbors Approach." Energies 14, no. 14: 4364.
Mesoscale models, such as the Weather Research and Forecasting (WRF) model, are now commonly used to predict wind resources, and in recent years their outputs are being used as inputs to wake models for the prediction of the production of wind farms. Also, wind farm parametrizations have been implemented in the mesoscale models but their accuracy to reproduce wind speeds and turbulent kinetic energy fields within and around wind farms is yet unknown. This is partly because they have been evaluated against wind farm power measurements directly and, generally, a lack of high-quality observations of the wind field around large wind farms. Here, we evaluate the in-built wind farm parametrization of the WRF model, the so-called Fitch scheme that works together with the MYNN2 planetary boundary layer (PBL) scheme against large-eddy simulations (LES) of wakes using a generalized actuator disk model, which was also implemented within the same WRF version. After setting both types of simulations as similar as possible so that the inflow conditions are nearly identical, preliminary results show that the velocity deficits can differ up to 50% within the same area (determined by the resolution of the mesoscale run) where the turbine is placed. In contrast, within that same area, the turbine-generated TKE is nearly identical in both simulations. We also prepare an analysis of the sensitivity of the results to the inflow wind conditions, horizontal grid resolution of both the LES and the PBL run, number of turbines within the mesoscale grid cells, surface roughness, inversion strength, and boundary-layer height.
Alfredo Peña; Jeffrey Mirocha. Evaluation of the the wind farm wake parametrization with large-eddy simulations of wakes in WRF. 2021, 1 .
AMA StyleAlfredo Peña, Jeffrey Mirocha. Evaluation of the the wind farm wake parametrization with large-eddy simulations of wakes in WRF. . 2021; ():1.
Chicago/Turabian StyleAlfredo Peña; Jeffrey Mirocha. 2021. "Evaluation of the the wind farm wake parametrization with large-eddy simulations of wakes in WRF." , no. : 1.
In wind resource assessments, which are critical to the pre-construction of wind farms, measurements by LiDARs or masts are a source of high-fidelity data, but are expensive and scarce in space and time, particularly for offshore sites. On the other hand, numerical simulations, using for example the Weather Research and Forecasting (WRF) model, generate temporally and spatially continuous data with relatively low-fidelity. A hybrid approach is proposed here to combine the merit of measurements and simulations for the assessment of offshore wind. Firstly a temporal data fusion using deep Multi Fidelity Gaussian Process Regression (MF-GPR) is performed to combine the intermittent measurement and the continuous simulation data at an onshore location. Then a spatial data fusion using a neural network with Non-linear Autoregression (NAR) and Non-linear Autoregression with external input (NARX) are conducted to project the wind from onshore to offshore. The numerical and measured wind speeds along the west coast of Denmark were used to evaluate the method. We show that the proposed data fusion technique using a gappy onshore measurement results in accurate offshore wind resource assessment within a 2% margin error.
Basem Elshafei; Alfredo Peña; Dong Xu; Jie Ren; Jake Badger; Felipe M. Pimenta; Donald Giddings; Xuerui Mao. A hybrid solution for offshore wind resource assessment from limited onshore measurements. Applied Energy 2021, 298, 117245 .
AMA StyleBasem Elshafei, Alfredo Peña, Dong Xu, Jie Ren, Jake Badger, Felipe M. Pimenta, Donald Giddings, Xuerui Mao. A hybrid solution for offshore wind resource assessment from limited onshore measurements. Applied Energy. 2021; 298 ():117245.
Chicago/Turabian StyleBasem Elshafei; Alfredo Peña; Dong Xu; Jie Ren; Jake Badger; Felipe M. Pimenta; Donald Giddings; Xuerui Mao. 2021. "A hybrid solution for offshore wind resource assessment from limited onshore measurements." Applied Energy 298, no. : 117245.
This study proposes two methodologies for improving the accuracy of wind turbine load assessment under wake conditions by combining nacelle-mounted lidar measurements with wake wind field reconstruction techniques. The first approach consists of incorporating wind measurements of the wake flow field, obtained from nacelle lidars, into random, homogeneous Gaussian turbulence fields generated using the Mann spectral tensor model. The second approach imposes wake deficit time series, which are derived by fitting a bivariate Gaussian shape function to lidar observations of the wake field, on the Mann turbulence fields. The two approaches are numerically evaluated using a virtual lidar simulator, which scans the wake flow fields generated with the dynamic wake meandering (DWM) model, i.e., the target fields. The lidar-reconstructed wake fields are then input into aeroelastic simulations of the DTU 10 MW wind turbine for carrying out the load validation analysis. The power and load time series, predicted with lidar-reconstructed fields, exhibit a high correlation with the corresponding target simulations, thus reducing the statistical uncertainty (realization-to-realization) inherent to engineering wake models such as the DWM model. We quantify a reduction in power and loads' statistical uncertainty by a factor of between 1.2 and 5, depending on the wind turbine component, when using lidar-reconstructed fields compared to the DWM model results. Finally, we show that the number of lidar-scanned points in the inflow and the size of the lidar probe volume are critical aspects for the accuracy of the reconstructed wake fields, power, and load predictions.
Davide Conti; Vasilis Pettas; Nikolay Dimitrov; Alfredo Peña. Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals. Wind Energy Science 2021, 6, 841 -866.
AMA StyleDavide Conti, Vasilis Pettas, Nikolay Dimitrov, Alfredo Peña. Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals. Wind Energy Science. 2021; 6 (3):841-866.
Chicago/Turabian StyleDavide Conti; Vasilis Pettas; Nikolay Dimitrov; Alfredo Peña. 2021. "Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals." Wind Energy Science 6, no. 3: 841-866.
It is well known that when eddies are small, the eddy fluxes can be directly related to the mean vertical gradients, the so-called flux-gradient relation, but such a relation becomes weaker the larger the coherent structures. Here, we show that this relation does not hold at heights relevant for wind energy applications. The flux–gradient relation assumes that the angle (
Pedro Santos; Alfredo Peña; Jakob Mann. Departure from Flux-Gradient Relation in the Planetary Boundary Layer. Atmosphere 2021, 12, 672 .
AMA StylePedro Santos, Alfredo Peña, Jakob Mann. Departure from Flux-Gradient Relation in the Planetary Boundary Layer. Atmosphere. 2021; 12 (6):672.
Chicago/Turabian StylePedro Santos; Alfredo Peña; Jakob Mann. 2021. "Departure from Flux-Gradient Relation in the Planetary Boundary Layer." Atmosphere 12, no. 6: 672.
We investigate the ability of the Weather Research and Forecasting model to perform large-eddy simulation of canonical flows. This is achieved through comparison of the simulation outputs with measurements from sonic anemometers on a 250 m meteorological mast located at Østerild, in northern Denmark. Østerild is on a flat and rough area, and for the predominant wind directions, the atmospheric flow can be considered to be close to homogeneous. The idealized simulated flows aim at representing atmospheric boundary layer turbulence under unstable, neutral, and stable stability conditions at the surface, which are statistically significant conditions observed at Østerild. We found that the resolved fields from the simulations appear to have the characteristics of the three stability regimes. Vertical profiles of observed mean wind speeds and direction are well reproduced by the simulations, with the largest differences under near-neutral conditions, where the effect of the subgrid-scale model is evident on the vertical wind shear close to the surface. Vertical profiles of observed eddy fluxes are also well reproduced by the simulations, with the largest differences for the three velocity component variances under stable stability conditions, although nearly always within the observed variability. With regards to turbulent kinetic energy, we find good agreement between observations and simulations at all vertical levels. Simulated and observed velocity spectra match very well and show very similar behavior with height and with atmospheric stability within the low-frequency interval; at the effective resolution, the simulated spectra show the typical drop-off of finite differences. Our findings demonstrate that these idealized simulations reproduce the characteristics of atmospheric stability regimes often observed at a high turbulent and flat site within a direction sector, where the air flows over nearly homogeneous land.
Alfredo Peña; Branko Kosović; Jeffrey D. Mirocha. Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mast. Wind Energy Science 2021, 6, 645 -661.
AMA StyleAlfredo Peña, Branko Kosović, Jeffrey D. Mirocha. Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mast. Wind Energy Science. 2021; 6 (3):645-661.
Chicago/Turabian StyleAlfredo Peña; Branko Kosović; Jeffrey D. Mirocha. 2021. "Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mast." Wind Energy Science 6, no. 3: 645-661.
Alfredo Peña; Jeffrey D. Mirocha. Comparison of large-eddy simulations of wakes with wind farm wake parametrizations using the Weather Research and Forecasting model. Journal of Physics: Conference Series 2021, 1934, 1 .
AMA StyleAlfredo Peña, Jeffrey D. Mirocha. Comparison of large-eddy simulations of wakes with wind farm wake parametrizations using the Weather Research and Forecasting model. Journal of Physics: Conference Series. 2021; 1934 (1):1.
Chicago/Turabian StyleAlfredo Peña; Jeffrey D. Mirocha. 2021. "Comparison of large-eddy simulations of wakes with wind farm wake parametrizations using the Weather Research and Forecasting model." Journal of Physics: Conference Series 1934, no. 1: 1.
An atmospheric hydraulic jump was observed over the Alaiz mountain range and Elorz valley near Pamplona, Spain from radial velocity retrievals performed with two scanning lidars during October 5 and 6, 2018. The jump occurred on the lee side of the mountain close to its base and the jump location was observed more than two kilometers further downstream of the mountain base inside the valley. Here, we simulate the two days using the multi‐scale modeling capabilities of the Weather Research and Forecasting model. We find that the model is able to reproduce the hydraulic jump in high detail matching qualitatively well the timing and main features observed by both the scanning lidars and meteorological instruments on masts deployed throughout the area. The simulation results shows that the jump starts at the beginning of the evening, right after the atmospheric conditions over the top of the Alaiz mountain become stable and the flow at the mountain top experiences a transition from subcritical to supercritical. The simulations also show that the jump lasts about 10 hours until it moves close to the mountain top; then lee‐wave activity dominates and lasts until late in the morning. The flow at the mountain top is only supercritical during the periods where the jump and the lee waves take place. The jump and lee‐wave regimes can be distinguished from the simulation results by analyzing the ratio of the depth‐average Brunt–Väisälä frequency to the depth‐average mean wind speed both upstream and downstream of the mountain top. This article is protected by copyright. All rights reserved.
A. Peña; P. Santos. Lidar Observations and Numerical Simulations of an Atmospheric Hydraulic Jump and Mountain Waves. Journal of Geophysical Research: Atmospheres 2021, 126, 1 .
AMA StyleA. Peña, P. Santos. Lidar Observations and Numerical Simulations of an Atmospheric Hydraulic Jump and Mountain Waves. Journal of Geophysical Research: Atmospheres. 2021; 126 (4):1.
Chicago/Turabian StyleA. Peña; P. Santos. 2021. "Lidar Observations and Numerical Simulations of an Atmospheric Hydraulic Jump and Mountain Waves." Journal of Geophysical Research: Atmospheres 126, no. 4: 1.
In this first part of a two-part work, we study the calibration of the Dynamic Wake Meandering (DWM) model using high spatial and temporal resolution SpinnerLidar measurements of the wake field collected at the Scaled Wind Farm Technology (SWiFT) facility located in Lubbock, Texas, U.S.A. We derive two-dimensional wake flow characteristics including wake deficit, wake turbulence and wake meandering from the lidar observations under different atmospheric stability conditions, inflow wind speeds and downstream distances up to five rotor diameters. We then apply Bayesian inference to obtain a probabilistic calibration of the DWM model, where the resulting joint distribution of parameters allows both for model implementation and uncertainty assessment. We validate the resulting fully-resolved wake field predictions against the lidar measurements and discuss the most critical sources of uncertainty. The results indicate that the DWM model can accurately predict the mean wind velocity and turbulence fields in the far wake region beyond four rotor diameters, as long as properly-calibrated parameters are used and wake meandering time series are accurately replicated. We demonstrate that the current DWM-model parameters in the IEC standard lead to conservative wake deficit predictions. Finally, we provide practical recommendations for reliable calibration procedures.
Davide Conti; Nikolay Dimitrov; Alfredo Peña; Thomas Herges. Calibration and validation of the Dynamic Wake Meandering model Part I: Bayesian estimation of model parameters using SpinnerLidar-derived wake characteristics. 2021, 2021, 1 -39.
AMA StyleDavide Conti, Nikolay Dimitrov, Alfredo Peña, Thomas Herges. Calibration and validation of the Dynamic Wake Meandering model Part I: Bayesian estimation of model parameters using SpinnerLidar-derived wake characteristics. . 2021; 2021 ():1-39.
Chicago/Turabian StyleDavide Conti; Nikolay Dimitrov; Alfredo Peña; Thomas Herges. 2021. "Calibration and validation of the Dynamic Wake Meandering model Part I: Bayesian estimation of model parameters using SpinnerLidar-derived wake characteristics." 2021, no. : 1-39.
We investigate the ability of the Weather Research and Forecasting model to perform large-eddy simulation of canonical flows. This is achieved through comparison of the simulation outputs with measurements from sonic anemometers on a 250-m meteorological mast located at Østerild, in northern Denmark. Østerild is on a flat and rough area, and for the predominant wind directions, the atmospheric flow can be considered to be close to homogeneous. The idealized simulated flows aim at representing atmospheric boundary layer turbulence under unstable, neutral, and stable stability conditions at the surface, which are statistically significant conditions observed at Østerild. We found that the resolved fields from the simulations appear to have the characteristics of the three stability regimes. Vertical profiles of observed mean wind speeds and direction are well reproduced by the simulations with the largest differences under near-neutral conditions, where the effect of the subgrid-scale model is evident on the vertical wind shear close to the surface. Vertical profiles of observed eddy fluxes are also well reproduced by the simulations with the largest differences for the three velocity component variances under stable stability conditions, although nearly always within the observed variability. With regards to turbulent kinetic energy, we find good agreement between observations and simulations at all vertical levels. Simulated and observed velocity spectra match very well, and show very similar behavior with height and with atmospheric stability within the low frequency interval; at the effective resolution, the simulated spectra show the typical drop-off of finite differences. Our findings demonstrate that these idealized simulations reproduce the characteristics of atmospheric stability regimes often observed at a high turbulent and flat site within a direction sector, where the air flows over nearly homogeneous land.
Alfredo Peña; Branko Kosović; Jeffrey D. Mirocha. Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250-m meteorological mast. 2021, 2021, 1 -25.
AMA StyleAlfredo Peña, Branko Kosović, Jeffrey D. Mirocha. Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250-m meteorological mast. . 2021; 2021 ():1-25.
Chicago/Turabian StyleAlfredo Peña; Branko Kosović; Jeffrey D. Mirocha. 2021. "Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250-m meteorological mast." 2021, no. : 1-25.
Vertical wind shears could have a significant effect on the energy produced by a wind turbine and on its loads. Although the development of several wind farms has been planned on the East Coast of the United States, there are no studies that characterize the vertical wind shear over this area. This study focuses on characterizing wind shears in the marine boundary layer in Southern New England and along the East Coast of the United States. The analysis looks at the statistical distribution of vertical wind shear values and at their associated meteorological conditions. The analysis relies on remote‐sensing wind measurements and other meteorological data recorded at the Woods Hole Oceanographic Institution Air–Sea Interaction Tower located 3 km to the South of Martha's Vineyard, together with buoy measurements and ERA5 reanalysis data. This work shows that large vertical wind shear values (>0.05 m/s/m) calculated using wind measurements at 60 and 53 m were often observed (≈25.3% of all the valid wind profiles analyzed) for South‐Westerly winds within a range of positive bulk Richardson numbers 0–0.1. These large‐shear values are the result of the presence of a strong high‐pressure system (Bermuda‐Azores High) over the North Atlantic basin and low pressures over land, which result in warm Southerly winds flowing over the cold waters of the Labrador current. The power density computed considering the vertical wind shear by means of the rotor equivalent wind speed is 5.5% smaller than that considering wind speed measurements at 110 m only.
Dager Borvarán; Alfredo Peña; Rémi Gandoin. Characterization of offshore vertical wind shear conditions in Southern New England. Wind Energy 2020, 24, 465 -480.
AMA StyleDager Borvarán, Alfredo Peña, Rémi Gandoin. Characterization of offshore vertical wind shear conditions in Southern New England. Wind Energy. 2020; 24 (5):465-480.
Chicago/Turabian StyleDager Borvarán; Alfredo Peña; Rémi Gandoin. 2020. "Characterization of offshore vertical wind shear conditions in Southern New England." Wind Energy 24, no. 5: 465-480.
It is well known that when eddies are small, the eddy fluxes can be directly related to the mean vertical gradients, the so-called K-theory, but such relation becomes weaker the larger the coherent structures. Here, we show that this relation does not hold at heights relevant for wind energy applications. The relation implies that the angle (β) between the vector of vertical flux of horizontal momentum and the vector of the mean vertical gradient of horizontal velocity is zero, i.e., the vectors are aligned. This is not what we observe from measurements performed both offshore and onshore. We quantify the misalignment of β using measurements from a long-range Doppler profiling lidar and large-eddy simulations. We also use mesoscale model output from the New European Wind Atlas project to compare with the lidar-observed vertical profiles of wind speed, wind direction, momentum fluxes, and the angle between the horizontal velocity vector and the momentum flux vector up to 500 m both offshore and onshore, hence covering the rotor areas of modern wind turbines and beyond. The results show that within the range 100–500 m, β = −18° offshore and β = 12° onshore, on average. However, the large-eddy simulations show β ≈ 0°, partly confirming previous modeling results. We illustrate that mesoscale model output matches the observed mean wind speed and momentum fluxes well, but that this model output has significant deviations with the observations when looking at the turning of the wind.
Pedro Santos; Alfredo Peña; Jakob Mann. Departure from K-theory in the planetary boundary layer. 2020, 2020, 1 -18.
AMA StylePedro Santos, Alfredo Peña, Jakob Mann. Departure from K-theory in the planetary boundary layer. . 2020; 2020 ():1-18.
Chicago/Turabian StylePedro Santos; Alfredo Peña; Jakob Mann. 2020. "Departure from K-theory in the planetary boundary layer." 2020, no. : 1-18.
This study proposes two methodologies for improving the accuracy of wind turbine load assessment under wake conditions by combining nacelle-mounted lidar measurements with wake wind field reconstruction techniques. The first approach consists in incorporating wind measurements of the wake flow field, obtained from nacelle lidars, into random, homogeneous Gaussian turbulence fields generated using the Mann spectral tensor model. The second approach imposes wake deficit time-series, which are derived by fitting a bivariate Gaussian shape function on lidar observations of the wake field, on the Mann turbulence fields. The two approaches are numerically evaluated using a virtual lidar simulator, which scans the wake flow fields generated with the Dynamic Wake Meandering (DWM) model. The lidar-reconstructed wake fields are input to aeroelastic simulations of the DTU 10 MW wind turbine and the resulting load predictions are compared with loads obtained with the target (no lidar-based) DWM simulated fields. The accuracy of load predictions is estimated across a variety of lidar beam configurations, probe volume sizes, and atmospheric turbulence conditions. The results indicate that the 10-min power and fatigue load statistics, predicted with lidar-reconstructed fields, are comparable with results obtained with the DWM simulations. Furthermore, the simulated power and load time-series exhibit a high level of correlation with the target observations, thus decreasing the statistical uncertainty (realization-to-realization) by a factor between 1.2 and 5, compared to results obtained with the baseline, which is DWM simulated fields with different random seeds. Finally, we show that the spatial resolutions of the lidar's scanning strategies as well as the size of the probe volume are critical aspects for the accuracy of the reconstructed wake fields and load predictions.
Davide Conti; Vasilis Pettas; Nikolay Dimitrov; Alfredo Peña. Wind turbine load validation in wakes using field reconstruction techniques and nacelle lidar wind retrievals. 2020, 2020, 1 -33.
AMA StyleDavide Conti, Vasilis Pettas, Nikolay Dimitrov, Alfredo Peña. Wind turbine load validation in wakes using field reconstruction techniques and nacelle lidar wind retrievals. . 2020; 2020 ():1-33.
Chicago/Turabian StyleDavide Conti; Vasilis Pettas; Nikolay Dimitrov; Alfredo Peña. 2020. "Wind turbine load validation in wakes using field reconstruction techniques and nacelle lidar wind retrievals." 2020, no. : 1-33.
Alfredo Peña; Andrea N. Hahmann. Evaluating planetary boundary-layer schemes and large-eddy simulations with measurements from a 250-m meteorological mast. Journal of Physics: Conference Series 2020, 1618, 1 .
AMA StyleAlfredo Peña, Andrea N. Hahmann. Evaluating planetary boundary-layer schemes and large-eddy simulations with measurements from a 250-m meteorological mast. Journal of Physics: Conference Series. 2020; 1618 ():1.
Chicago/Turabian StyleAlfredo Peña; Andrea N. Hahmann. 2020. "Evaluating planetary boundary-layer schemes and large-eddy simulations with measurements from a 250-m meteorological mast." Journal of Physics: Conference Series 1618, no. : 1.
Pedro Santos; Alfredo Peña; Jakob Mann. Flux-gradient relation and atmospheric wind profiles — an exploration using WRF and lidars. Journal of Physics: Conference Series 2020, 1618, 1 .
AMA StylePedro Santos, Alfredo Peña, Jakob Mann. Flux-gradient relation and atmospheric wind profiles — an exploration using WRF and lidars. Journal of Physics: Conference Series. 2020; 1618 ():1.
Chicago/Turabian StylePedro Santos; Alfredo Peña; Jakob Mann. 2020. "Flux-gradient relation and atmospheric wind profiles — an exploration using WRF and lidars." Journal of Physics: Conference Series 1618, no. : 1.
Davide Conti; Nikolay Krasimirov Dimitrov; Alfredo Peña; Thomas Herges. Wind turbine wake characterization using the SpinnerLidar measurements. Journal of Physics: Conference Series 2020, 1618, 1 .
AMA StyleDavide Conti, Nikolay Krasimirov Dimitrov, Alfredo Peña, Thomas Herges. Wind turbine wake characterization using the SpinnerLidar measurements. Journal of Physics: Conference Series. 2020; 1618 ():1.
Chicago/Turabian StyleDavide Conti; Nikolay Krasimirov Dimitrov; Alfredo Peña; Thomas Herges. 2020. "Wind turbine wake characterization using the SpinnerLidar measurements." Journal of Physics: Conference Series 1618, no. : 1.
An atmospheric hydraulic jump was observed over the Alaiz mountain range and Elorz valley near Pamplona, Spain from radial velocity retrievals performed with two scanning lidars during October 5 and 6, 2018. The jump occurred on the lee side of the mountain range and moved more than two kilometers further downstream the mountain base inside the valley. Here, we simulate the two days using the multi-scale modeling capabilities of the Weather Research and Forecasting model. We find that the model is able to reproduce the hydraulic jump at Alaiz in high detail matching qualitatively well the timing and main features observed by both the scanning lidars and meteorological instruments on a series of masts deployed throughout the area. The simulation results shows that the jump starts at the beginning of the evening, right after the atmospheric conditions over the top of the Alaiz mountain become stable and the flow at the mountain top experiences a transition from subcritical to supercritical. The simulations also show that the jump lasts about 10 hours until it moves close to the mountain top; then lee-wave activity is mainly portrayed and lasts until late in the morning. The flow is only supercritical during the periods where the jump and the lee waves take place. The jump and lee-wave regimes can be distinguished from the simulation results by computing the ratio of the upstream depth-average Brunt--Väisälä frequency to the depth-average mean wind speed.
Alfredo Peña; Pedro Santos. Lidar observations and numerical simulations of an atmospheric hydraulic jump and mountain waves. 2020, 1 .
AMA StyleAlfredo Peña, Pedro Santos. Lidar observations and numerical simulations of an atmospheric hydraulic jump and mountain waves. . 2020; ():1.
Chicago/Turabian StyleAlfredo Peña; Pedro Santos. 2020. "Lidar observations and numerical simulations of an atmospheric hydraulic jump and mountain waves." , no. : 1.
We propose a method for carrying out wind turbine load validation in wake conditions using measurements from forward-looking nacelle lidars. Two lidars, a pulsed- and a continuous-wave system, were installed on the nacelle of a 2.3 MW wind turbine operating in free-, partial-, and full-wake conditions. The turbine is placed within a straight row of turbines with a spacing of 5.2 rotor diameters, and wake disturbances are present for two opposite wind direction sectors. The wake flow fields are described by lidar-estimated wind field characteristics, which are commonly used as inputs for load simulations, without employing wake deficit models. These include mean wind speed, turbulence intensity, vertical and horizontal shear, yaw error, and turbulence-spectra parameters. We assess the uncertainty of lidar-based load predictions against wind turbine on-board sensors in wake conditions and compare it with the uncertainty of lidar-based load predictions against sensor data in free wind. Compared to the free-wind case, the simulations in wake conditions lead to increased relative errors (4 %–11 %). It is demonstrated that the mean wind speed, turbulence intensity, and turbulence length scale have a significant impact on the predictions. Finally, the experiences from this study indicate that characterizing turbulence inside the wake as well as defining a wind deficit model are the most challenging aspects of lidar-based load validation in wake conditions.
Davide Conti; Nikolay Krasimirov Dimitrov; Alfredo Peña. Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements. Wind Energy Science 2020, 5, 1129 -1154.
AMA StyleDavide Conti, Nikolay Krasimirov Dimitrov, Alfredo Peña. Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements. Wind Energy Science. 2020; 5 (3):1129-1154.
Chicago/Turabian StyleDavide Conti; Nikolay Krasimirov Dimitrov; Alfredo Peña. 2020. "Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements." Wind Energy Science 5, no. 3: 1129-1154.
The Wind Power Density (WPD) is widely used for wind resource characterization. However, there is a significant level of uncertainty associated with its estimation. Here, we analyze the effect of sampling frequencies, averaging periods, and the length of time series on the WPD estimation. We perform this analysis using four approaches. First, we analytically evaluate the impact of assuming that the WPD can simply be computed from the cube of the mean wind speed. Second, the wind speed time series from two meteorological stations are used to assess the effect of sampling and averaging on the WPD. Third, we use numerical weather prediction model outputs and observational data to demonstrate that the error in the WPD estimate is also dependent on the length of the time series. Finally, artificial time series are generated to control the characteristics of the wind speed distribution, and we analyze the sensitivity of the WPD to variations of these characteristics. The WPD estimation error is expressed mathematically using a numerical-data-driven model. This numerical-data-driven model can then be used to predict the WPD estimation errors at other sites. We demonstrate that substantial errors can be introduced by choosing too short time series. Furthermore, averaging leads to an underestimation of the WPD. The error introduced by sampling is strongly site-dependent.
Markus Gross; Vanesa Magar; Alfredo Peña. The Effect of Averaging, Sampling, and Time Series Length on Wind Power Density Estimations. Sustainability 2020, 12, 3431 .
AMA StyleMarkus Gross, Vanesa Magar, Alfredo Peña. The Effect of Averaging, Sampling, and Time Series Length on Wind Power Density Estimations. Sustainability. 2020; 12 (8):3431.
Chicago/Turabian StyleMarkus Gross; Vanesa Magar; Alfredo Peña. 2020. "The Effect of Averaging, Sampling, and Time Series Length on Wind Power Density Estimations." Sustainability 12, no. 8: 3431.
The design of wind turbines and wind farms can be improved by increasing the accuracy of the inflow models representing the atmospheric boundary layer. In this work we employ one-dimensional Reynolds-averaged Navier–Stokes (RANS) simulations of the idealized atmospheric boundary layer (ABL), using turbulence closures with a length-scale limiter. These models can represent the mean effects of surface roughness, Coriolis force, limited ABL depth, and neutral and stable atmospheric conditions using four input parameters: the roughness length, the Coriolis parameter, a maximum turbulence length, and the geostrophic wind speed. We find a new model-based Rossby similarity, which reduces the four input parameters to two Rossby numbers with different length scales. In addition, we extend the limited-length-scale turbulence models to treat the mean effect of unstable stratification in steady-state simulations. The original and extended turbulence models are compared with historical measurements of meteorological quantities and profiles of the atmospheric boundary layer for different atmospheric stabilities.
Maarten Paul Van Der Laan; Mark Kelly; Rogier Floors; Alfredo Peña. Rossby number similarity of an atmospheric RANS model using limited-length-scale turbulence closures extended to unstable stratification. Wind Energy Science 2020, 5, 355 -374.
AMA StyleMaarten Paul Van Der Laan, Mark Kelly, Rogier Floors, Alfredo Peña. Rossby number similarity of an atmospheric RANS model using limited-length-scale turbulence closures extended to unstable stratification. Wind Energy Science. 2020; 5 (1):355-374.
Chicago/Turabian StyleMaarten Paul Van Der Laan; Mark Kelly; Rogier Floors; Alfredo Peña. 2020. "Rossby number similarity of an atmospheric RANS model using limited-length-scale turbulence closures extended to unstable stratification." Wind Energy Science 5, no. 1: 355-374.