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Incorporation of the Rotor-Equivalent Wind Speed into the Weather Research and Forecasting Model’s Wind Farm Parameterization

Journal Article · · Monthly Weather Review
 [1];  [2];  [3];  [4]
  1. Univ. of Colorado, Boulder, CO (United States). Dept. of Atmospheric and Oceanic Sciences, and the Cooperative Inst. for Research in Environmental Sciences
  2. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences, Global Systems Division
  3. Univ. of Colorado, Boulder, CO (United States). Dept. of Atmospheric and Oceanic Sciences
  4. Vibrant Clean Energy, Boulder (Colorado)
+ Show Author Affiliations
Wind power installations have been increasing in recent years. Because wind turbines can influence local wind speeds, temperatures, and surface fluxes, weather forecasting models should consider their effects. Wind farm parameterizations do currently exist for numerical weather prediction models. They generally consider two turbine impacts: elevated drag in the region of the wind turbine rotor disk and increased turbulent kinetic energy production. The wind farm parameterization available in the Weather Research and Forecasting (WRF) Model calculates this drag and TKE as a function of hub-height wind speed. However, recent work has suggested that integrating momentum over the entire rotor disk [via a rotor-equivalent wind speed (REWS)] is more appropriate, especially for cases with high wind shear. In this study, we implement the REWS in the WRF wind farm parameterization and evaluate its impacts in an idealized environment, with varying amounts of wind speed shear and wind directional veer. Specifically, we evaluate three separate cases: neutral stability with low wind shear, high stability with high wind shear, and high stability with nonlinear wind shear. For most situations, use of the REWS with the wind farm parameterization has marginal impacts on model forecasts. However, for scenarios with highly nonlinear wind shear, the REWS can significantly affect results.
Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
National Science Foundation (NSF)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1507679
Report Number(s):
NREL/JA--5000-73673
Journal Information:
Monthly Weather Review, Journal Name: Monthly Weather Review Journal Issue: 3 Vol. 147; ISSN 0027-0644
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (5)

The future of forecasting for renewable energy journal September 2019
Modified Power Curves for Prediction of Power Output of Wind Farms journal May 2019
An Induction Curve Model for Prediction of Power Output of Wind Turbines in Complex Conditions journal February 2020
Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1) journal January 2020
Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1) text January 2020

Figures / Tables (12)

FIG. 1(p. 5)figure FIG. 1
FIG. 2(p. 5)figure FIG. 2
TABLE 1(p. 7)table TABLE 1
FIG. 3(p. 8)figure FIG. 3
TABLE 2(p. 9)table TABLE 2
FIG. 4(p. 10)figure FIG. 4
FIG. 5(p. 11)figure FIG. 5
FIG. 6(p. 11)figure FIG. 6
FIG. 7(p. 12)figure FIG. 7
FIG. 8(p. 13)figure FIG. 8
FIG. A1(p. 14)figure FIG. A1
FIG. A3(p. 16)figure FIG. A3

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Related Subjects

17 WIND ENERGY
atmosphere
mesoscale forecasting
numerical weather prediction/forecasting
parameterization
renewable energy
wind effects