Understanding Biases in Pre-Construction Estimates

Monte Lunacek, M. Jason Fields, Anna Craig, Joseph C.Y. Lee, John Meissner, Caleb Philips, Shuangwen Sheng, Ryan King

Research output: Contribution to journalArticlepeer-review

6 Scopus Citations


The pre-construction energy generation of a wind farm (P50) is difficult to estimate and evaluate. This paper presents a methodology to measure the accuracy of the p50 prediction, which we call the Historical Validation Survey (HVS), for several wind farms in the continental United States. Our results indicate that there is a bias between predicted and measured energy, even when controlling for factors like grid curtailment and resource variability. We also find that our results depend on the assumptions we make during analysis, which we quantify with a sensitivity analysis. This method allows the estimation of uncertainty we have in our findings. When we account for reasonable ranges of model assumptions, we find that, in the most optimistic case, there is still a bulk -5.5% bias when estimating pre-construction energy generation. When controlling for grid curtailment this number reduces to a range of -3.5 to -4.5%.

Original languageAmerican English
Article numberArticle No. 062009
Number of pages9
JournalJournal of Physics: Conference Series
Issue number6
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-2C00-71398


  • energy generation
  • energy production
  • wind farm


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