A comprehensive statistical analysis for residuals of wind speed and direction from numerical weather prediction for wind energy

Hao Chen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
5 Downloads (Pure)

Abstract

Wind data are vital for the research in renewable energy research. Their quality from numerical weather prediction significantly influences the wind energy models. This paper utilizes a comprehensive statistical analysis for analyzing predictive errors, named residuals of wind speed and direction modeled by numerical weather prediction models. The analysis, taken an Arctic wind site as an example, effectively integrates statistical inference, probabilistic modeling, and hypothesis tests. It is proven that the residuals still contain important meteorological information. The introduced statistical analysis may be used to replenish residuals and explore complex intrinsic properties of numerical weather wind models and contributions to wind energy modeling.

Original languageEnglish
Pages (from-to)618-626
Number of pages9
JournalEnergy Reports
Volume8
Issue numberSuppl. 9
DOIs
Publication statusPublished - Nov 2022
Externally publishedYes

Keywords

  • Hypothesis test
  • Numerical weather prediction
  • Residual analysis
  • Statistical modeling
  • Wind energy

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