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Volume 10, issue 11 | Copyright
Geosci. Model Dev., 10, 4229-4244, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model evaluation paper 23 Nov 2017

Model evaluation paper | 23 Nov 2017

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Joseph C. Y. Lee1,2 and Julie K. Lundquist1,2 Joseph C. Y. Lee and Julie K. Lundquist
  • 1Department of Atmospheric and Oceanic Sciences, University of Colorado, UCB 311, Boulder, CO 80309, USA
  • 2National Renewable Energy Laboratory, Golden, CO, USA

Abstract. Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

Publications Copernicus
Short summary
We evaluate the wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model, a powerful tool to simulate wind farms and their meteorological impacts numerically. In our case study, the WFP simulations with fine vertical grid resolution are skilful in matching the observed winds and the actual power productions. Moreover, the WFP tends to underestimate power in windy conditions. We also illustrate that the modeled wind speed is a critical determinant to improve the WFP.
We evaluate the wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF)...