Generating wind time series as a hybrid of measured and simulated data

Stephen Rose, Jay Apt

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Certain applications, such as analysing the effect of a wind farm on grid frequency regulation, require several years of wind power data measured at intervals of a few seconds. We have developed a method to generate days to years of non-stationary wind speed time series sampled at high rates by combining measured and simulated data. Measured wind speed data, typically 10-15 min averages, capture 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, add realistic turbulence 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.

Original languageEnglish (US)
Pages (from-to)699-715
Number of pages17
JournalWind Energy
Volume15
Issue number5
DOIs
StatePublished - Jul 2012

Keywords

  • non-stationary simulation
  • power fluctuation
  • wind speed time series

Fingerprint Dive into the research topics of 'Generating wind time series as a hybrid of measured and simulated data'. Together they form a unique fingerprint.

Cite this