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Is it always windy somewhere? Occurrence of low-wind-power events over large areas

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  • Handschy, Mark A.
  • Rose, Stephen
  • Apt, Jay

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.

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  • Handschy, Mark A. & Rose, Stephen & Apt, Jay, 2017. "Is it always windy somewhere? Occurrence of low-wind-power events over large areas," Renewable Energy, Elsevier, vol. 101(C), pages 1124-1130.
    • Handle: RePEc:eee:renene:v:101:y:2017:i:c:p:1124-1130
    DOI: 10.1016/j.renene.2016.10.004
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    References listed on IDEAS

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    1. Dowds, Jonathan & Hines, Paul & Ryan, Todd & Buchanan, William & Kirby, Elizabeth & Apt, Jay & Jaramillo, Paulina, 2015. "A review of large-scale wind integration studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 768-794.
    2. Rose, Stephen & Apt, Jay, 2016. "Quantifying sources of uncertainty in reanalysis derived wind speed," Renewable Energy, Elsevier, vol. 94(C), pages 157-165.
    3. Huang, Junling & Lu, Xi & McElroy, Michael B., 2014. "Meteorologically defined limits to reduction in the variability of outputs from a coupled wind farm system in the Central US," Renewable Energy, Elsevier, vol. 62(C), pages 331-340.
    4. Milligan, Michael & Porter, Kevin, 2006. "The Capacity Value of Wind in the United States: Methods and Implementation," The Electricity Journal, Elsevier, vol. 19(2), pages 91-99, March.
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