A refined wind farm parameterization for the weather research and forecasting model

Chunlei Wu, Kun Luo, Qiang Wang and Jianren Fan

Applied Energy, 2022, vol. 306, issue PB, No S0306261921013684

Abstract: In the original wind farm parameterization of the Weather Research and Forecasting model, the standard constant air density is a source of errors in power output estimation, and the hub-height wind speed is inappropriate to represent the wind speed through the whole rotor area. To overcome these issues, a refined model incorporating variable air density is developed, and the hub-height wind speed is replaced with the rotor equivalent wind speed (REWS) in this study. To keep consistency, the power coefficients corresponding to the REWS under variable air density conditions are modified. The influences of atmospheric stability are investigated to evaluate the performance of wind power estimation between the original and the current refined models. The refined wind farm parameterization has few impacts on the flow field, however, the average power generation becomes more scattered and is notably decreased by nearly 7% due to the reduced variable air density. Meanwhile, the REWS slightly increases the power estimation by around 1.1%. Both REWS and variable air density can decrease the estimation uncertainty of the average power induced by complex atmospheric stability. Moreover, atmospheric stability plays a more significant role in power outputs, and the refined model can capture a stronger correlation between the atmospheric condition and wind power generation.

Keywords: Wind power estimation; WRF; Wind farm parameterization; Rotor equivalent wind speed; Air density; Atmospheric stability (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.apenergy.2021.118082

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