Assessing Variability of Wind Speed: Comparison and Validation of 27 Methodologies

Cheuk Yi Joseph Lee, Michael Fields, Julie Lundquist

Research output: Contribution to journalArticlepeer-review

22 Scopus Citations

Abstract

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.
Original languageAmerican English
Pages (from-to)845-868
Number of pages24
JournalWind Energy Science
Volume3
Issue number2
DOIs
StatePublished - 2018

Bibliographical note

See NREL/JA-5000-72114 for article as published in Wind Energy Science Discussions

NREL Publication Number

  • NREL/JA-5000-72768

Keywords

  • inter-annual variability
  • statistics
  • uncertainty quantification
  • variability
  • wind resource assessment

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