12Regional wind integration studies in the United States require detailed wind power output 13 data at many locations to perform simulations of how the power system will operate 14 under high-penetration scenarios. The wind datasets that serve as inputs into the study 15 must realistically reflect the ramping characteristics, spatial and temporal correlations, 16and capacity factors of the simulated wind plants, as well as be time synchronized with 17 available load profiles. The Wind Integration National Dataset (WIND) Toolkit described 18in this article fulfills these requirements as the largest and most complete grid integration 19dataset publicly available to date. A meteorological dataset, wind power production time 20series, and simulated forecasts created using the Weather Research and Forecasting 21Model run on a 2-kilometer grid over the continental United States at a 5-minute 22resolution is now publicly available for more than 126,000 land-based and offshore wind 23 power production sites. State-of-the-art forecast accuracy was mimicked by reforecasting 24 the years 2007-2013 using industry-standard techniques. Our meteorological and power 25validation results show that the WIND Toolkit data is satisfactory for wind energy 26integration studies. Users are encouraged to validate according to their phenomena and 27 application of interest. 28 29 Keywords 30Grid integration, WRF, wind energy, integration data set, WIND Toolkit, numerical 31 simulations 32
This report, the 2016 Offshore Wind Energy Resource Assessment for the United States, was developed by the National Renewable Energy Laboratory (NREL), and updates a previous national resource assessment study (Schwartz et al. 2010), and refines and reaffirms that the available wind resource is sufficient for offshore wind to be a large-scale contributor to the nation's electric energy supply. Experience from other renewable technologies, such as landbased wind and solar energy, indicates that offshore wind site development will likely be highly selective. Therefore, the resource potential needs to significantly exceed the anticipated deployment to allow for siting flexibility. When developers and regulators have more siting options, projects can be built in the most economical and least conflicted areas. Therefore, an abundant wind resource is one of the essential building blocks that compose the value proposition for offshore wind. As such, the study shows that to implement the U.S. Department of Energy's (DOE's) Wind Vision 86-gigawatt (GW) offshore wind deployment scenario for 2050 (DOE 2015a), it would require the United States to use about 0.8% of the gross resource area or about 4.2% of the total technical resource area.
The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by the Weather Research and Forecasting model using seven sets of simulations with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights.Winds speeds at heights ranging from 10 to 160 m, wind shears, temperatures and surface turbulent fluxes from seven sets of hindcasts are evaluated against observations at Høvsøre, Denmark. The ability of these hindcast sets to simulate mean wind speeds, wind shear, and their time variability strongly depends on atmospheric static stability. Wind speed hindcasts using the Yonsei University PBL scheme compared best with observations during unstable atmospheric conditions, whereas the Asymmetric Convective Model version 2 PBL scheme did so during near-stable and neutral conditions, and the Mellor-Yamada-Janjic PBL scheme prevailed during stable and very stable conditions. The evaluation of the simulated wind speed errors and how these vary with height clearly indicates that for wind power forecasting and wind resource assessment, validation against 10 m wind speeds alone is not sufficient. Evaluation of wind shear in the WRF model C. Draxl et al.the overall power losses by a wind farm. Furthermore, when the output from mesoscale models is used for wind resource assessment, information about the wind profile across the rotor area will lead to more accurate resource estimates.Because the grid resolution in mesoscale numerical weather prediction (NWP) models is too large to explicitly resolve the processes responsible for small-scale fluxes in the planetary boundary layer (PBL), sub-grid-scale turbulent fluxes, which are mostly unknown, and vertical mixing are calculated by PBL parameterizations. 4 PBL parameterizations use the distribution of wind, temperature, and water vapor mixing ratio with height and the surface fluxes calculated from a land surface model (LSM) and/or surface layer scheme to determine, amongst many others, the time tendencies of wind, temperature and water vapor mixing ratio. The choice of PBL scheme thus plays a significant role in the evolution of the low-level wind structure and therefore can heavily impact the quality of the forecast winds.Many aspects of the mesoscale model determine the quality of the forecast PBL structure. In the Weather Research and Forecasting (WRF) model, surface momentum, heat and moisture fluxes are c...
The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.
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