Interconnecting 4 Texas Wind Turbines Reduced Variability Of Single Turbine's Output 87%


 "Fraction of a Kolmogorov spectrum of different time scales as a function of the number of interconnected wind plants. Interconnecting four or five wind plants achieves the majority of the reduction of wind power's variability." Image credit:Draft paper; The Variability of Interconnected Wind Plants (pdf)

Warren Katzenstein, Emily Fertig, and Jay Apt of the Carnegie Mellon Electricity Industry Center have released the first draft of a research paper which presents "the first frequency-dependent analyses of the geographic smoothing of wind power's variability, analyzing the interconnected measured output of 20 wind plants in Texas."

This is a seminal work for two reasons: it establishes that numerous, far-flung turbines need not be interconnected to overcome wind power variability on a regional scale; and, because it presents an optimistic outlook for low annual wind power variability, based on national scale averages. Specifically "severity of wind drought years is estimated to be about half that observed nationally for hydroelectric power." Full abstract presented below.TITLE: The Variability of Interconnected Wind Plants
AUTHOR: Warren Katzenstein, Emily Fertig, Jay Apt

ABSTRACT: We present the first frequency-dependent analyses of the geographic smoothing of wind power's variability, analyzing the interconnected measured output of 20 wind plants in Texas. Reductions in variability occur at frequencies corresponding to times shorter than ~24 hours and are quantified by measuring the departure from a Kolmogorov spectrum. At a frequency of 2.8x10-4 Hz (corresponding to 1 hour), an 87% reduction of the variability of a single wind plant is obtained by interconnecting 4 wind plants. Interconnecting the remaining 16 wind plants produces only an additional 8% reduction. At a frequency of 4.6x10-5 Hz (6 hours), interconnecting 6 wind plants produces a 68% reduction in variability and interconnecting the remaining 14 wind plants produces only an additional 8% reduction. We use step-change analyses and correlation coefficients to compare our results with previous studies, finding that wind power ramps up faster than it ramps down for each of the step change intervals analyzed and that correlation between the power output of wind plants 200 km away is half that of co-located wind plants. To examine variability at very low frequencies, we estimate yearly wind energy production in the Great Plains region of the United States from automated wind observations at airports covering 36 years. The estimated wind power has significant inter-annual variability and the severity of wind drought years is estimated to be about half that observed nationally for hydroelectric power.

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