Is it always windy somewhere? Occurrence of low-wind-power events over large areas. (February 2017)

• Record Type: Journal Article
• Authors: Handschy, Mark A.; Rose, Stephen; Apt, Jay
• Is Part Of: Renewable energy. Volume 101(2017)
• Page Start: 1124
• Page End: 1130
• Publication Date: 2017-02
• Subjects: Wind power -- Wind variability -- Large deviation theory -- Effective load carrying capacity (ELCC) -- Geographic diversity; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2016.10.004
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: The incidence of widespread low-wind conditions is important to the reliability and economics of electric grids with large amounts of wind power. In order to investigate a future in which wind plants are geographically widespread but interconnected, we examine how frequently low generation levels occur for wind power aggregated from distant, weakly-correlated wind generators. We simulate the wind power using anemometer data from nine tall-tower sites spanning the contiguous United States. The number of low-power hours per year declines exponentially with the number of sites being aggregated. Hours with power levels below 5% of total capacity, for example, drop by a factor of about 60, from 2140 h/y for the median single site to 36 h/y for the generation aggregated from all nine sites; the standard deviation drops by a factor of 3. The systematic dependence of generation-level probability distribution "tails" on both number and power threshold is well described by the theory of Large Deviations. Combining this theory for tail behavior with the normal distribution for behavior near the mean allows us to estimate, without the use of any adjustable parameters, the entire generation duration curve as a function of the number of essentially independent sites in the array. Highlights: Few prior explanations of low-wind-power probability vs. number of sites. Low-power probability shrinks exponentially with number of independent sites. Large Deviations Theory explains exponential dependence. Geographic-diversity smoothing effects duration-curve tails more than center.