Assessing variability of wind speed: comparison and validation of 27 methodologies

• Published in: Wind Energy Science Vol. 3; no. 2; pp. 845 - 868
• Main Authors: Lee, Joseph C Y, Fields, M Jason, Lundquist, Julie K
• Format: Journal Article
• Language: English
• Published: Göttingen Copernicus GmbH 05-11-2018; Copernicus Publications
• Subjects: Spatial distribution; Variability; Wind farms; Wind power; Wind speed
• ISSN: 2366-7443; 2366-7451
• DOI: 10.5194/wes-3-845-2018

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.