Short-term variations in wind power: Some quantile-type models for probabilistic forecasting
Article first published online: 19 JUL 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Volume 14, Issue 2, pages 255–269, March 2011
How to Cite
Pritchard, G. (2011), Short-term variations in wind power: Some quantile-type models for probabilistic forecasting. Wind Energ., 14: 255–269. doi: 10.1002/we.416
- Issue published online: 14 MAR 2011
- Article first published online: 19 JUL 2010
- Manuscript Accepted: 11 JUN 2010
- Manuscript Revised: 9 JUN 2010
- Manuscript Received: 14 DEC 2009
- wind power forecasting;
- quantile regression
We discuss some ways of formulating quantile-type models for forecasting variations in wind power in the short term (within a few hours). Such models predict quantiles of the conditional distribution of the wind power available at some future time using information presently available. A natural reference for models of this kind is a ‘probabilistic-persistence’ quantile forecast whose only input is the present wind power. Using data from some New Zealand wind farms, we find that more complex quantile models can readily improve on probabilistic persistence in resolution but not in sharpness. The most valuable model inputs, apart from the present power, are found to be real-time air pressure measurements and a power total-variation indicator. Copyright © 2010 John Wiley & Sons, Ltd.