Wind turbine power curves are calibrated by turbine manufacturers under requirements\nstipulated by the International Electrotechnical Commission to provide a functional mapping\nbetween the mean wind speed v and the mean turbine power output P. Wind plant operators\nemploy these power curves to estimate or forecast wind power generation under given wind\nconditions. However, it is general knowledge that wide variability exists in these mean calibration\nvalues. We first analyse how the standard deviation in wind speed ÃÆ?v affects the mean P and the\nstandard deviation ÃÆ?P of wind power. We find that the magnitude of wind power fluctuations scales\nas the square of the mean wind speed. Using data from three planetary locations, we find that\nthe wind speed standard deviation ÃÆ?v systematically varies with mean wind speed v, and in some\ninstances, follows a scaling of the form ÃÆ?v = C Ã?â?? vÃ?±; C being a constant and Ã?± a fractional power. We\nshow that, when applicable, this scaling form provides a minimal parameter description of the power\ncurve in terms of v alone. Wind data from different locations establishes that (in instances when this\nscaling exists) the exponent Ã?± varies with location, owing to the influence of local environmental\nconditions on wind speed variability. Since manufacturer-calibrated power curves cannot account\nfor variability influenced by local conditions, this variability translates to forecast uncertainty in\npower generation. We close with a proposal for operators to perform post-installation recalibration\nof their turbine power curves to account for the influence of local environmental factors on wind\nspeed variability in order to reduce the uncertainty of wind power forecasts. Understanding the\nrelationship between windââ?¬â?¢s speed and its variability is likely to lead to lower costs for the integration\nof wind power into the electric grid.
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