Preprints
https://doi.org/10.5194/wes-2021-111
https://doi.org/10.5194/wes-2021-111

  02 Nov 2021

02 Nov 2021

Review status: this preprint is currently under review for the journal WES.

Validation of Wind Resource and Energy Production Simulations for Small Wind Turbines in the United States

Lindsay M. Sheridan1, Caleb Phillips2, Alice C. Orrell1, Larry K. Berg1, Heidi Tinnesand2, Raj K. Rai1, Sagi Zisman2, Dmitry Duplyakin2, and Julia E. Flaherty1 Lindsay M. Sheridan et al.
  • 1Pacific Northwest National Laboratory, Richland, WA, USA
  • 2National Renewable Energy Laboratory, Golden, CO, USA

Abstract. Due to financial and temporal limitations, the small wind community relies upon simplified wind speed models and energy production simulation tools to assess site suitability and produce energy generation expectations. While efficient and user-friendly, these models and tools are subject to errors that have been insufficiently quantified at small wind turbine heights. This study leverages observations from meteorological towers and sodars across the United States to validate wind speed estimates from the Wind Integration National Dataset (WIND) Toolkit, the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), revealing average biases within ±0.5 m s−1 at small wind hub heights. Observations from small wind turbines across the United States provide references for validating energy production estimates from the System Advisor Model (SAM), Wind Report, and MyWindTurbine.com, which are seen to overestimate actual annual capacity factors by 2.5, 4.2, and 11.5 percentage points, respectively. In addition to quantifying the error metrics, this paper identifies sources of model and tool discrepancies, noting that interannual fluctuation in the wind resource, wind speed class, and loss assumptions produce more variability in estimates than different horizontal and vertical interpolation techniques. The results of this study provide small wind installers and owners with information about these challenges to consider when making performance estimates and thus possible adjustments accordingly. Looking to the future, recognizing these error metrics and sources of discrepancies provides model and tool researchers and developers with opportunities for product improvement that could positively impact small wind customer confidence and the ability to finance small wind projects.

Lindsay M. Sheridan et al.

Status: open (until 14 Dec 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on wes-2021-111', Michael Bergey, 12 Nov 2021 reply
    • AC1: 'Reply on CC1', Lindsay Sheridan, 15 Nov 2021 reply
  • RC1: 'Comment on wes-2021-111', Andreas Bechmann, 22 Nov 2021 reply
  • RC2: 'Comment on wes-2021-111', Tom Acker, 22 Nov 2021 reply

Lindsay M. Sheridan et al.

Lindsay M. Sheridan et al.

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Short summary
The small wind community relies on simplified wind models and energy production simulation tools to obtain energy generation expectations. We gathered actual wind speed and turbine production data across the U.S. to test the accuracy of models and tools for small wind turbines. This study provides small wind installers and owners with the error metrics and sources of error associated with using models and tools to make performance estimates, empowering them to adjust expectations accordingly.