Because wind resources vary from year to year, the
intermonthly and interannual variability (IAV) of wind speed is a key
component of the overall uncertainty in the wind resource assessment
process, thereby creating challenges for wind farm operators and owners. We
present a critical assessment of several common approaches for calculating
variability by applying each of the methods to the same 37-year monthly
wind-speed and energy-production time series to highlight the differences
between these methods. We then assess the accuracy of the variability
calculations by correlating the wind-speed variability estimates to the
variabilities of actual wind farm energy production. We recommend the robust
coefficient of variation (RCoV) for systematically estimating variability,
and we underscore its advantages as well as the importance of using a
statistically robust and resistant method. Using normalized spread metrics,
including RCoV, high variability of monthly mean wind speeds at a location
effectively denotes strong fluctuations of monthly total energy generation,
and vice versa. Meanwhile, the wind-speed IAVs computed with annual-mean
data fail to adequately represent energy-production IAVs of wind farms.
Finally, we find that estimates of energy-generation variability require 10±3 years of monthly mean wind-speed records to achieve a 90 %
statistical confidence. This paper also provides guidance on the spatial
distribution of wind-speed RCoV.</p
