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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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This overview evaluates the energy prediction bias in the wind resource assessment process, and the overprediction bias is decreasing over time. We examine the estimated and observed losses and uncertainties in energy production from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 standard. The considerable uncertainties calls for further improvements on the prediction methodologies and more observations for validation.
Preprints
https://doi.org/10.5194/wes-2020-85
https://doi.org/10.5194/wes-2020-85

  10 Jul 2020

10 Jul 2020

Review status: a revised version of this preprint was accepted for the journal WES and is expected to appear here in due course.

An Overview of Wind Energy Production Prediction Bias, Losses, and Uncertainties

Joseph C. Y. Lee and M. Jason Fields Joseph C. Y. Lee and M. Jason Fields
  • National Wind Technology Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA

Abstract. The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the industry is recording near-zero average energy prediction bias. Herein, we present an overview of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including the improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight the opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty, and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary on how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the manuscript.

Joseph C. Y. Lee and M. Jason Fields

 
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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Joseph C. Y. Lee and M. Jason Fields

Joseph C. Y. Lee and M. Jason Fields

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Latest update: 27 Jan 2021
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Short summary
This overview evaluates the energy prediction bias in the wind resource assessment process, and the overprediction bias is decreasing over time. We examine the estimated and observed losses and uncertainties in energy production from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 standard. The considerable uncertainties calls for further improvements on the prediction methodologies and more observations for validation.
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