Skill of the WRF Model's Wind Speed, Direction, and Shear Forecasts for an Iowa Wind Farm

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Sunday, 4 January 2015
Meghan J. Mitchell, NCAR, Boulder, CO; and E. S. Takle and R. A. Walton

Wind energy has become one of the leading alternative energy sources to reduce dependence on fossil fuels that contribute to climate change. Changes in wind direction can contribute to changes in power output of a wind farm due to wake-turbine interactions. Forecasting wind direction changes can improve forecasts of wind farm power output. The WRF (Weather Research and Forecasting) model is widely used within the meteorology community for forecasting. Wind direction observations from two meteorological towers at an Iowa wind farm were compared to WRF model output to determine the WRF model's skill in forecasting wind direction, speed, and shear for this wind farm. Cases were selected based on when the two towers agreed and when the farm was producing substantial power: wind speeds were above 6 m s-1 and under 20 m s-1. The WRF model was run for two 48-hour cases and compared forecasted wind direction with observations from the towers. Model skill was assessed through computations of mean absolute error, and biases were calculated to assess systematic behavior of the model. The mean wind speed and direction biases were 1.01 m s-1 and 9 degrees for Case 1 and the 0.53 m s-1 and 17 degrees for Case 2 when averaged over all heights. Since these biases were relatively small, the model proved skillful in forecasting wind speed and direction , however biases in the wind shear were found to be larger. Further case studies are needed to better quantify these results. These results will inform future research to determine which turbines may experience power reduction due to wakes within the wind farm. These results may also be useful for determining more efficient wind farm design and layout and for taking wind direction into account in wind farm power forecasts.