Uncertainty Quantification in the Analyses of Operational Wind Power Plant Performance

Anna Craig, Michael Optis, Michael Fields, Patrick Moriarty

Research output: Contribution to journalArticlepeer-review

12 Scopus Citations


In the present work, we examine the variation introduced in the evaluation of an operating plant's wind power production as a result of the choices analysts make in the processing of the operational data. For this study, an idealized power production for individual turbines over an operational period was predicted by fitting power curves to the turbine production data collected during expected operation (that is, without curtailment or availability losses). A set of 240 possible methods were developed for (a) defining what data represented expected operation and (b) modeling the power curve. The spread in the idealized power production as predicted by the different methods was on average almost 3% for the 100 turbines considered. Such significant variation places a lower bound on the precision with which analysts may employ such data as benchmarks for calibration of their energy estimation processes and limits the potential for identification of refinements to the energy estimation models for improved accuracy.

Original languageAmerican English
Article numberArticle No. 052021
Number of pages10
JournalJournal of Physics: Conference Series
Issue number5
StatePublished - 19 Jun 2018
Event7th Science of Making Torque from Wind, TORQUE 2018 - Milan, Italy
Duration: 20 Jun 201822 Jun 2018

Bibliographical note

Publisher Copyright:
© Published under licence by IOP Publishing Ltd.

NREL Publication Number

  • NREL/JA-5000-71397


  • operational data analysis
  • uncertainty quantification


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