Abstract

Wind turbine power curves are calibrated by turbine manufacturers under requirements stipulated by the International Electrotechnical Commission to provide a functional mapping between the mean wind speed v ¯ and the mean turbine power output P ¯ . Wind plant operators employ these power curves to estimate or forecast wind power generation under given wind conditions. However, it is general knowledge that wide variability exists in these mean calibration values. We first analyse how the standard deviation in wind speed σ v affects the mean P ¯ and the standard deviation σ P of wind power. We find that the magnitude of wind power fluctuations scales as the square of the mean wind speed. Using data from three planetary locations, we find that the wind speed standard deviation σ v systematically varies with mean wind speed v ¯ , and in some instances, follows a scaling of the form σ v = C × v ¯ α ; C being a constant and α a fractional power. We show that, when applicable, this scaling form provides a minimal parameter description of the power curve in terms of v ¯ alone. Wind data from different locations establishes that (in instances when this scaling exists) the exponent α varies with location, owing to the influence of local environmental conditions on wind speed variability. Since manufacturer-calibrated power curves cannot account for variability influenced by local conditions, this variability translates to forecast uncertainty in power generation. We close with a proposal for operators to perform post-installation recalibration of their turbine power curves to account for the influence of local environmental factors on wind speed variability in order to reduce the uncertainty of wind power forecasts. Understanding the relationship between wind’s speed and its variability is likely to lead to lower costs for the integration of wind power into the electric grid.

Highlights

  • The wind turbine power curve relates the speed of wind blowing past a turbine to the power generated by the turbine

  • The power curves are supplied to operators by turbine manufacturers, who calibrate them under standards specified by the International Electrotechnical Commission (IEC) [3]

  • Our analysis of wind data obtained from three different planetary locations (Table 1) reveals that in instances when the above scaling form is satisfied, the power-law exponent α varies with geographic location, and must reflect local environmental factors not captured by manufacturer-supplied calibration power curves

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Summary

Introduction

The wind turbine power curve relates the speed of wind blowing past a turbine to the power generated by the turbine. Our analysis of wind data obtained from three different planetary locations (Table 1) reveals that in instances when the above scaling form is satisfied, the power-law exponent α varies with geographic location, and must reflect local environmental factors not captured by manufacturer-supplied calibration power curves. When these calibration power curves are applied to forecast wind power, wind speed variability transforms into power forecast uncertainty. We conclude with a proposal that wind plant operators should recalibrate turbine power curves at the plant location to properly account for variability arising from local environmental factors This will help to reduce the uncertainty of wind power forecasts. Understanding the source of variability and utilising it appropriately brings tangible benefits to the global renewable energy community

Influence of Wind Speed Variability on Wind Power
Results and Discussion
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