Understanding Biases in Pre-Construction Estimates: Article No. 062009

Monte Lunacek, Michael Fields, Cheuk Yi Joseph Lee, John Meissner, Caleb Phillips, Ryan King, Anna Craig

Research output: Contribution to journalArticlepeer-review

6 Scopus Citations

Abstract

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
Number of pages9
JournalJournal of Physics: Conference Series
Volume1037
DOIs
StatePublished - 2018

NREL Publication Number

  • NREL/JA-2C00-71398

Keywords

  • energy generation
  • energy production
  • wind farm

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