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CEIC-10-03

"Generating Wind Time Series as a Hybrid of Measured and Simulated Data"
Stephen Rose and Jay Apt

Abstract:
Certain applications, such as analyzing the effect of a wind farm on grid frequency regulation, require several years of wind power data measured at intervals of a few seconds. This paper develops a method to generate long non-stationary wind speed time series sampled at high rates by combining measured and simulated data. Measured wind speed data, typically 10 - 15 minute averages, captures the non-stationary characteristics of wind speed variation: diurnal variations, the passing of weather fronts, and seasonal variations. Simulated wind speed data, generated from spectral models, "fills in" the gaps between the empirical data. The wind speed time series generated with this method agree very well with measured time series, both qualitatively and quantitatively. The power output of a wind turbine simulated with wind data generated by this method demonstrates energy production, ramp rates, and reserve requirements that closely match the power output of a turbine simulated turbine with measured wind data.

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