Unravelling the wind flow over highly complex regions through computational modeling and two-dimensional lidar scanning

Palma, J. M. L. M.; Lopes, A. Silva; Gomes, Vitor M. C.; Rodrigues, C. Veiga; Menke, Robert; Vasiljević, Nikola; Mann, Jakob

doi:10.1088/1742-6596/1222/1/012006

Cited by 10 publications

(10 citation statements)

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“…Overall, the comparison aids the validation of the lidar measurements. However, the measurements cannot be compared to studies that were purely designed for a comparison of different measurement technologies as done, for example, by Pauscher et al (2016). Moreover, the correlation of reconstructed wind speeds in the present study shows that differences when comparing the lidar wind speeds to the projected or the horizontal sonic winds speeds are negligibly small.…”

Section: Comparison Of Mast and Lidar Measurementsmentioning

confidence: 69%

“…Moreover, the deployment of several lidars with scanning capabilities allows the assessment of wind conditions over large areas , which can give important insights into the spatial variability of flow over very complex terrain. Multi-lidars have been proven to have a high measurement accuracy in comparison studies with sonic anemometers (Pauscher et al, 2016). Moreover, many studies utilized the scanning capability to measure wind fields over large areas for wind energy purposes in assessing, for example, wind turbine wakes (Trujillo et al, 2011;Iungo et al, 2013;Bodini et al, 2017;Menke et al, 2018b), the inflow towards wind turbines (Mikkelsen et al, 2013;Simley et al, 2016;Mann et al, 2018), the influence of surface and terrain features on the flow (Lange et al, 2016;Mann et al, 2017), and atmospheric phenomena such as gravity waves (Palma et al, 2019).…”

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confidence: 99%

“…The relevance of such measurements is especially important for complex terrain sites where the uncertainty of current flow models is high (Bechmann et al, 2011). Potential sources of error are the characterization of the roughness resulting from different types of canopies (Wagner et al, 2019a), the characterization of the stratification in the atmosphere (Palma et al, 2019), the description of the terrain (Lange et al, 2017;Berg et al, 2018), and model resolution which may not capture all important flow phenomena in complex terrain. Therefore creating a good measurement data set of the flow over such terrain is imperative to improving the models.…”

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confidence: 99%

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Multi-lidar wind resource mapping in complex terrain

et al. 2020

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Abstract. Scanning Doppler lidars have great potential for reducing uncertainty of wind resource estimation in complex terrain. Due to their scanning capabilities, they can measure at multiple locations over large areas. We demonstrate this ability with dual-Doppler lidar measurements of flow over two parallel ridges. The data have been collected using two pairs of scanning lidars operated in a dual-Doppler mode during the Perdigão 2017 measurement campaign. There the scanning lidars mapped the flow 80 m above ground level along two ridges, which are considered favorable for wind turbine siting. The measurements are validated with sonic wind measurements at each ridge. By analyzing the collected data, we found that wind speeds are on average 10 % higher over the southwest ridge compared to the northeast ridge. At the southwest ridge, the data show, for approach flow normal to the ridge, a change of 20 % in wind speed along the ridge. Fine differences like these are difficult to reproduce with computational flow models, as we demonstrate by comparing the lidar measurements with Weather Research and Forecasting large-eddy simulation (WRF-LES) results. For the measurement period, we have simulated the flow over the site using WRF-LES to compare how well the model can capture wind resources along the ridges. We used two model configurations. In the first configuration, surface drag is based purely on aerodynamic roughness, whereas in the second configuration forest canopy drag is also considered. We found that simulated winds are underestimated in WRF-LES runs with forest drag due to an unrealistic forest distribution on the ridge tops. The correlation of simulated and observed winds is, however, improved when the forest parameterization is applied. WRF-LES results without forest drag overestimated the wind resources over the southwest and northeast ridges by 6.5 % and 4.5 %, respectively. Overall, this study demonstrates the ability of scanning lidars to map wind resources in complex terrain.

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Section: Comparison Of Mast and Lidar Measurementsmentioning

confidence: 69%

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confidence: 99%

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confidence: 99%

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Multi-lidar wind resource mapping in complex terrain

et al. 2020

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“…A set of experimental data (30 minutes averaged) on 4 May 2017, 22:09-22:39 UTM is also included, for guidance only; because computational results do not consider, for instance, surface cover heterogeneity or stratification, discrepancies are expected when compared with experimental data. This was the day and the time when the assumption of conditions of both stationarity and neutral flow in Perdigão could be made, according respectively with Carvalho (2019) and Palma et al (2019), and therefore approach the steady-state regime and neutral atmospheric conditions of the computational runs.…”

Section: Flow Modellingmentioning

confidence: 99%

The digital terrain model in the computational modelling of the flow over the Perdigão site: the appropriate grid size

Palma¹,

Silva²,

Gomes³

et al. 2020

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Abstract. The digital terrain model (DTM), the representation of Earth's surface at regularly spaced intervals, is the first input in the computational modelling of atmospheric flows. The ability of computational meshes based on high (2 m, airborne laser scanning), medium (10 m, military maps) and low (30 m, shuttle mission, SRTM) resolution DTMs to replicate the Perdigão experiment site was appraised in two ways: by their ability to replicate the two main terrain attributes, elevation and slope, and by their effect on the wind flow computational results. The effect on the flow modelling was evaluated by comparing the wind speed, wind direction and turbulent kinetic energy by VENTOS®/2 at three locations, representative of the wind flow in the region. It was found that the SRTM was not an accurate representation of the Perdigão site. A 40 m mesh based on the highest resolution data, yielded at five reference points an elevation error of less than 1.4 m and an RMSE of less than 2.5 m, compared to 5.0 m, in the case of military maps and 7.6 m in the case of SRTM. Mesh refinement beyond 40 m yielded no or insignificant changes on the flow field variables, wind speed, wind direction and turbulent kinetic energy. At least 40 m horizontal resolution – threshold resolution –, and based on topography available from aerial survey, is recommended in computational modelling of the flow over Perdigão.

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“…In the RUNE campaign [8], the dual setup provided detailed information with regards to the effect of the land and the sea-to-land change of roughness on the wind. In the Perdigão campaign [17,18], multi-lidar systems were used to study the wake after a solitary wind turbine on a ridge [19][20][21], and trapped lee-waves after two ridges under stable conditions and the observations were compared to results from numerical modelling [22,23]. Menke et al [24] used three pairs of scanning lidars in the same experiment to characterize how recirculation after the ridges depends on atmospheric stability and position in the landscape.…”

Section: Introductionmentioning

confidence: 99%

Turbulence Measurements with Dual-Doppler Scanning Lidars

Peña

Mann

2019

Remote Sensing

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Velocity-component variances can be directly computed from lidar measurements using information of the second-order statistics within the lidar probe volume. Specifically, by using the Doppler radial velocity spectrum, one can estimate the unfiltered radial velocity variance. This information is not always available in current lidar campaigns. The velocity-component variances can also be indirectly computed from the reconstructed velocities but they are biased compared to those computed from, e.g., sonic anemometers. Here we show, for the first time, how to estimate such biases for a multi-lidar system and we demonstrate, also for the first time, their dependence on the turbulence characteristics and the lidar beam scanning geometry relative to the wind direction. For a dual-Doppler lidar system, we also show that the indirect method has an advantage compared to the direct one for commonly-used scanning configurations due to the singularity of the system. We demonstrate that our estimates of the radial velocity and velocity-component biases are accurate by analysis of measurements performed over a flat site using a dual-Doppler lidar system, where both lidars stared over a volume close to a sonic anemometer at a height of 100 m. We also show that mapping these biases over a spatial domain helps to plan meteorological campaigns, where multi-lidar systems can potentially be used. Particularly, such maps help the multi-point mapping of wind resources and conditions, which improve the tools needed for wind turbine siting.

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Unravelling the wind flow over highly complex regions through computational modeling and two-dimensional lidar scanning

Cited by 10 publications

References 11 publications

Multi-lidar wind resource mapping in complex terrain

Multi-lidar wind resource mapping in complex terrain

The digital terrain model in the computational modelling of the flow over the Perdigão site: the appropriate grid size

Turbulence Measurements with Dual-Doppler Scanning Lidars

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