• Energy Research

Abstract. Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-the-art NWP model – the Weather Research and Forecasting (WRF) Model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-term Ensemble Dataset (WTK-LED) to those observed by lidars at a site in Oklahoma, United States, and in a United States Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (∼-1ms-1) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a limited negative bias (∼-0.5ms-1) offshore and a slight positive bias (∼+0.5ms-1) at the land-based site. On the other hand, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED's higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle. At the land-based site, this is partially caused by wind plant wake effects not being accurately captured by WTK-LED.

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.

Abstract. Wind energy is anticipated to play a central role in enabling a rapid transition from fossil fuels to a system based largely on renewable power. For wind power to fulfill its expected role as the backbone—providing nearly half of the electrical energy—of a renewable-based, carbon-neutral energy system, critical challenges around design, development, and deployment of land and offshore technologies must be addressed. During the past three years, the wind research community has invested significant effort toward understanding the nature and implications of these challenges and identifying associated gaps. The outcomes of these efforts are summarized in a series of ten articles, some under review by Wind Energy Science (WES) and others planned for submission during the coming months. This letter explains the genesis, significance, and impacts of these efforts.

Presentation at the Wake Conference, Visby, 1 June 2017. The associated paper can be found at: http://iopscience.iop.org/article/10.1088/1742-6596/854/1/012037 Abstract We present results of the GABLS3 model intercomparison benchmark revisited for wind energy applications. The case consists of a diurnal cycle, measured at the 200-m tall Cabauw tower in the Netherlands, including a nocturnal low-level jet. The benchmark includes a sensitivity analysis of WRF simulations using two input meteorological databases and five planetary boundary-layer schemes. A reference set of mesoscale tendencies is used to drive microscale simulations using RANS k-ε and LES turbulence models. The validation is based on rotor-based quantities of interest. Cycle-integrated mean absolute errors are used to quantify model performance. The results of the benchmark are used to discuss input uncertainties from mesoscale modelling, different meso-micro coupling strategies (online vs offline) and consistency between RANS and LES codes when dealing with boundary-layer mean flow quantities. Overall, all the microscale simulations produce a consistent coupling with mesoscale forcings.

Wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of these changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σu, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σu, while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.

Abstract The ascent of stably stratified air over a mountain barrier can trigger the generation of mountain waves. Mountain waves occur frequently over the Columbia River Gorge in western North America and can impact wind power generation over the area. Therefore, predicting the details of mountain waves events (e.g., dominant wavelength, timing, and duration) can be very valuable for the wind energy community. In this study, the ability of the Weather Research and Forecasting (WRF) model to simulate mountain waves and their impact on hub-height wind speed is investigated. Our results suggest that the WRF model has moderate skill in simulating observed mountain wave. Further, given WRF predictions of wavelength range and wave period, the Fast Fourier Transform can calculate the simulated mountain wave impact on hub-height wind speed. The resulting wind speeds agree well with SoDAR observations in terms of both magnitude and pattern. Finally, for the simulated cases, WRF consistently predicts impacts of significant mountain wave events about an hour earlier than the actual observations. The sensitivities as well as uncertainties associated with our methodology are discussed in detail.

Abstract. Scanning lidars enable the collection of spatially distributed measurements of turbine wakes and the estimation of wake properties such as magnitude, extent, and trajectory. Lidar-based characterizations, however, may be subject to distortions due to the observational system. Distortions can arise from the resolution of the measurement points across the wake, the projection of the winds onto the beam, averaging along the beam probe volume, and intervening evolution of the flow over the scan duration. Using a large-eddy simulation and simulated measurements with a virtual lidar model, we assess how scanning lidar systems may influence the properties of the retrieved wake using a case study from the Perdigão campaign. We consider three lidars performing range-height indicator sweeps in complex terrain, based on the deployments of lidars from the Danish Technical University (DTU) and German Aerospace Center (DLR) at the Perdigão site. The unwaked flow, measured by the DTU lidar, is well-captured by the lidar, even without combining data into a multi-lidar retrieval. The two DLR lidars measure a waked transect from different downwind vantage points. In the region of the wake, the observation system reacts to the smaller spatial and temporal variations of the winds, allowing more significant observation distortions to arise. While the measurements largely capture the wake structure and trajectory over its 4–5 D extent, limited spatial resolution of measurement points and volume averaging lead to a quicker loss of the two lobes in the near wake, smearing of the vertical bounds of the wake (< 30 m), wake center displacements up to 10 m, and dampening of the maximum velocity deficit by up to a third. The virtual lidar tool, coupled with simulations, provides a means for assessing measurement capabilities in advance of measurement campaigns.

Abstract The validity of omitting stability considerations when simulating transport and dispersion in the urban environment is explored using observations from the Joint Urban 2003 field experiment and computational fluid dynamics simulations of that experiment. Four releases of sulfur hexafluoride, during two daytime and two nighttime intensive observing periods (IOPs), are simulated using the building-resolving computational fluid dynamics model called the Finite Element Model in 3-Dimensions and Massively Parallelized (FEM3MP) to solve the Reynolds-averaged Navier–Stokes equations with two options of turbulence parameterizations. One option omits stability effects but has a superior turbulence parameterization using a nonlinear eddy viscosity (NEV) approach, and the other considers buoyancy effects with a simple linear eddy viscosity approach for turbulence parameterization. Model performance metrics are calculated by comparison with observed winds and tracer data in the downtown area and with observed winds and turbulence kinetic energy (TKE) profiles at a location immediately downwind of the central business district in the area labeled as the urban shadow. Model predictions of winds, concentrations, profiles of wind speed, wind direction, and friction velocity are generally consistent with and compare reasonably well to the field observations. Simulations using the NEV turbulence parameterization generally exhibit better agreement with observations. To explore further the assumption of a neutrally stable atmosphere within the urban area, TKE budget profiles slightly downwind of the urban wake region in the urban shadow are examined. Dissipation and shear production are the largest terms that may be calculated directly. The advection of TKE is calculated as a residual; as would be expected downwind of an urban area, the advection of TKE produced within the urban area is a very large term. Buoyancy effects may be neglected in favor of advection, shear production, and dissipation. For three of the IOPs, buoyancy production may be neglected entirely; for one IOP, buoyancy production contributes approximately 25% of the total TKE at this location. For both nighttime releases, the contribution of buoyancy to the total TKE budget is always negligible though positive. Results from the simulations provide estimates of the average TKE values in the upwind, downtown, downtown shadow, and urban wake zones of the computational domain. These values suggest that building-induced turbulence can cause the average turbulence intensity in the urban area to increase by as much as 7 times average upwind values, explaining the minimal role of buoyant forcing in the downtown region. The downtown shadow exhibits an exponential decay in average TKE, whereas the distant downwind wake region approaches the average upwind values. For long-duration releases in downtown and downtown shadow areas, the assumption of neutral stability is valid because building-induced turbulence dominates the budget. However, farther downwind in the urban wake region, which is found to be approximately 1500 m beyond the perimeter of downtown Oklahoma City, Oklahoma, the levels of building-induced turbulence greatly subside, and therefore the assumption of neutral stability is less valid.