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

Cheuk Yi Joseph Lee, Michael Fields, Julie Lundquist

Research output: Contribution to journalArticle

Abstract

Because wind resources vary from year to year, the inter-monthly and inter-annual variability (IAV) of wind speed is a key component of the overall uncertainty in the wind resource assessment process thereby causing challenges to 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 generations, 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 90% statistical confidence. This paper also provides guidance on the spatial distribution of wind-speed RCoV.
Original languageAmerican English
Number of pages50
JournalWind Energy Science Discussions
DOIs
StatePublished - 2018

Bibliographical note

See NREL/JA-5000-72768 for article as published in Wind Energy Science

NREL Publication Number

  • NREL/JA-5000-72114

Keywords

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

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