Quantifying wind plant blockage under stable atmospheric conditions

Gomez, Miguel Sanchez; Lundquist, Julie K.; Mirocha, Jeffrey D.; Arthur, Robert S.; Muñoz‐Esparza, Domingo

doi:10.5194/wes-2021-57

“…The stable-boundary-layer simulation closely follows the configuration of Sanchez Gomez et al (2021). The surface condition for the stable case is driven with a cooling rate, rather than a negative heat flux (Basu et al, 2007).…”

Section: Idealized Atmospheric Boundary Layer Simulations Of Varying ...mentioning

confidence: 81%

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

Robey

¹

,

Lundquist

²

2022

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Abstract. Wind lidars are widespread and important tools in atmospheric observations. An intrinsic part of lidar measurement error is due to atmospheric variability in the remote-sensing scan volume. This study describes and quantifies the distribution of measurement error due to turbulence in varying atmospheric stability. While the lidar error model is general, we demonstrate the approach using large ensembles of virtual WindCube V2 lidar performing a profiling Doppler-beam-swinging scan in quasi-stationary large-eddy simulations (LESs) of convective and stable boundary layers. Error trends vary with the stability regime, time averaging of results, and observation height. A systematic analysis of the observation error explains dominant mechanisms and supports the findings of the empirical results. Treating the error under a random variable framework allows for informed predictions about the effect of different configurations or conditions on lidar performance. Convective conditions are most prone to large errors (up to 1.5 m s−1 in 1 Hz wind speed in strong convection), driven by the large vertical velocity variances in convective conditions and the high elevation angle of the scanning beams (62∘). Range-gate weighting induces a negative bias into the horizontal wind speeds near the surface shear layer (−0.2 m s−1 in the stable test case). Errors in the horizontal wind speed and direction computed from the wind components are sensitive to the background wind speed but have negligible dependence on the relative orientation of the instrument. Especially during low winds and in the presence of large errors in the horizontal velocity estimates, the reported wind speed is subject to a systematic positive bias (up to 0.4 m s−1 in 1 Hz measurements in strong convection). Vector time-averaged measurements can improve the behavior of the error distributions (reducing the 10 min wind speed error standard deviation to <0.3 m s−1 and the bias to <0.1 m s−1 in strong convection) with a predictable effectiveness related to the number of decorrelated samples in the time window. Hybrid schemes weighting the 10 min scalar- and vector-averaged lidar measurements are shown to be effective at reducing the wind speed biases compared to cup measurements in most of the simulated conditions, with time averages longer than 10 min recommended for best use in some unstable conditions. The approach in decomposing the error mechanisms with the help of the LES flow field could be extended to more complex measurement scenarios and scans.

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“…We briefly digress from the discussion on wakes to note that upwind blockage (Schneemann et al, 2021;Sanchez Gomez et al, 2021) can be observed in these idealized simulations and tangential flow accelerations, similar to the speed-ups seen by Nygaard and Hansen (2016), can be observed adjacent to the wakes. Blockage is strongest in the stable conditions, where 0.125-0.250 m s −1 deficits extend 5 km-7 km upwind of the plant.…”

Section: Hub-height Wind Speed Deficitsmentioning

confidence: 84%

The Sensitivity of the Fitch Wind Farm Parameterization to a Three-Dimensional Planetary Boundary Layer Scheme

Rybchuk

¹

,

Juliano

²

,

Lundquist

³

et al. 2021

Preprint

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Abstract. Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds can significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, until now, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. First, we simulate a wind plant in a pseudo-steady state under idealized stable, neutral, and unstable conditions with two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, MYNN consistently predicts internal wakes that are 0.25–1.5 m s−1 stronger than internal 3DPBL wakes. However, because MYNN predicts stronger inflow winds than the 3DPBL, MYNN predicts average capacity factors that are as large as 13 percentage points higher than with the 3DPBL, depending on the stability. To extend this sensitivity study, we conduct a month-long case study with both PBL schemes centered on the Vineyard Wind 1 lease area in the mid-Atlantic United States. Under stable and unstable conditions averaged across the month, MYNN again predicts stronger internal waking—by about 0.25 m s−1. However, again due to stronger plant inflow wind speeds in MYNN, the 3DPBL generates 4.7 %–7.8 % less power than MYNN in August 2020, depending on the turbine build-out scenario. Differences between PBL schemes can be even larger for individual instances in time. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.

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“…We briefly digress from the discussion on wakes to discuss two effects that are secondary to the primary analysis of this study: upwind blockage and flow acceleration. Upwind blockage (Schneemann et al, 2021;Sanchez Gomez et al, 2021) occurs in some of the idealized simulations. Blockage is strongest in the stable conditions, where 0.5 m s −1 deficits extend 5-10 km upwind of the plant.…”

Section: Hub-height Wind Speed Deficitsmentioning

confidence: 99%

The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

Rybchuk

¹

,

Juliano

²

,

Lundquist

³

et al. 2022

View full text Add to dashboard Cite

Abstract. Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds often significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, as of the Weather Research and Forecasting model v4.3.3, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. We simulate a wind plant in pseudo-steady states under idealized stable, neutral, and unstable conditions with matching hub-height wind speeds using two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, average hub-height wind speed losses within the plant differ between PBL schemes by between −0.20 and 0.22 m s−1, and correspondingly, capacity factors range between 39.5 %–53.8 %. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.

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Quantifying wind plant blockage under stable atmospheric conditions

Cited by 6 publications

References 22 publications

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

The Sensitivity of the Fitch Wind Farm Parameterization to a Three-Dimensional Planetary Boundary Layer Scheme

The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

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