Extrapolation of Wind Speed Data for Wind Energy Applications

Environmental concerns and rising fossil fuel prices have prompted rapid development in the renewable energy sector. Wind energy, in particular, has become increasingly popular in the United States. However, the building of large, utility-scale wind farms requires knowledge of the wind speed climatology at hub height (typically 80–100 m). As most wind speed measurements are taken at 10 m above ground level, efforts are being made to relate 10-m wind speed measurements to approximate hub-height wind speeds.

In this work, several common extrapolation methods are evaluated using cup anemometer data from the Oklahoma Mesonet and the Oklahoma Wind Power Initiative's tall tower sites. Linear regression is used to fit a first-order polynomial (i.e., straight line) and a power law to observed wind speeds at 10 and 80 m. Monin-Obukhov similarity theory is used to produce wind speed profiles up to 80 m based on 10-m wind speed and stability measurements. Since similarity theory is only applicable in the surface layer, an extension of mixing-length theory is also explored as an alternative to similarity theory above the surface layer.

Results indicate that the extrapolation methods fit the wind speed data fairly well in neutral and unstable atmospheric regimes, but produce inaccurate results for stable regimes. The inaccuracy of the extrapolation methods for stable regimes is likely related to the highly sheared wind speed profiles and intermittent turbulence that are common in the stable boundary layer.