Articles | Volume 3, issue 1
https://doi.org/10.5194/wes-3-371-2018
https://doi.org/10.5194/wes-3-371-2018
Research article
 | 
14 Jun 2018
Research article |  | 14 Jun 2018

Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing

Rochelle P. Worsnop, Michael Scheuerer, Thomas M. Hamill, and Julie K. Lundquist

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Cited articles

A2E: WFIP2 Wind Forecast Improvement Project 2, available from: https://a2e.energy.gov/projects/wfip2, last access: 30 October 2017. 
Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C. R., Smirnova, T. G., Olson, J. B., James, E. P., Dowell, D. C., Grell, G. A., Lin, H., Peckham, S. E., Smith, T. L., Moninger, W. R., Kenyon, J. S., and Manikin, G. S.: A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh, Mon. Weather Rev., 144, 1669–1694, https://doi.org/10.1175/MWR-D-15-0242.1, 2015. 
Bianco, L., Djalalova, I. V., Wilczak, J. M., Cline, J., Calvert, S., Konopleva-Akish, E., Finley, C., and Freedman, J.: A Wind Energy Ramp Tool and Metric for Measuring the Skill of Numerical Weather Prediction Models, Weather Forecast., 31, 1137–1156, https://doi.org/10.1175/WAF-D-15-0144.1, 2016. 
Bossavy, A., Girard, R., and Kariniotakis, G.: Forecasting ramps of wind power production with numerical weather prediction ensembles, Wind Energy, 16, 51–63, https://doi.org/10.1002/we.526, 2013. 
Bremnes, J. B.: A comparison of a few statistical models for making quantile wind power forecasts, Wind Energy, 9, 3–11, https://doi.org/10.1002/we.182, 2006. 
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This paper uses four statistical methods to generate probabilistic wind speed and power ramp forecasts from the High Resolution Rapid Refresh model. The results show that these methods can provide necessary uncertainty information of power ramp forecasts. These probabilistic forecasts can aid in decisions regarding power production and grid integration of wind power.
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