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The power law is often used in wind power assessments [4] [5] where wind speeds at the height of a turbine ( 50 metres) must be estimated from near surface wind observations (~10 metres), or where wind speed data at various heights must be adjusted to a standard height [6] prior to use.
Knaff and Zehr (2007) came up with the following formula to relate wind and pressure, taking into account movement, size, and latitude: [5] = (/) + ′ Where V srm is the max wind speed corrected for storm speed, phi is the latitude, and S is the size parameter. [5]
Global map of wind speed at 100 meters on land and around coasts. [12] Distribution of wind speed (red) and energy (blue) for all of 2002 at the Lee Ranch facility in Colorado. The histogram shows measured data, while the curve is the Rayleigh model distribution for the same average wind speed. Global map of wind power density potential [13]
The power coefficient [9] C P (= P/P wind) is the dimensionless ratio of the extractable power P to the kinetic power P wind available in the undistributed stream. [ citation needed ] It has a maximum value C P max = 16/27 = 0.593 (or 59.3%; however, coefficients of performance are usually expressed as a decimal, not a percentage).
The log wind profile is generally considered to be a more reliable estimator of mean wind speed than the wind profile power law in the lowest 10–20 m of the planetary boundary layer. Between 20 m and 100 m both methods can produce reasonable predictions of mean wind speed in neutral atmospheric conditions.
The fastest wind speed not related to tornadoes ever recorded was during the passage of Tropical Cyclone Olivia on 10 April 1996: an automatic weather station on Barrow Island, Australia, registered a maximum wind gust of 113.3 m/s (408 km/h; 253 mph; 220.2 kn; 372 ft/s) [6] [7] The wind gust was evaluated by the WMO Evaluation Panel, who found ...
Wind turbine power coefficient Distribution of wind speed (red) and energy generated (blue). The histogram shows measured data, while the curve is the Rayleigh model distribution for the same average wind speed. Distribution of wind speed (blue) and energy generated (yellow).
Because wind is variable year to year, and power produced is related to the cube of windspeed, short-term (< 5 years) onsite measurements can result in highly inaccurate energy estimates. Therefore, wind speed data from nearby longer term weather stations (usually located at airports) are used to adjust the onsite data.