Using Quantile Regression to Extend an Existing Wind Power Forecasting System with Probabilistic Forecasts
- Authors:
- DOI:
- 10.1002/we.180
- Abstract:
- For operational planning it is important to provide information about the situation-dependent uncertainty of a wind power forecast. Factors which influence the uncertainty of a wind power forecast include the predictability of the actual meteorological situation, the level of the predicted wind speed (due to the non-linearity of the power curve) and the forecast horizon. With respect to the predictability of the actual meteorological situation a number of explanatory variables are considered, some inspired by the literature. The article contains an overview of related work within the field. An existing wind power forecasting system (Zephyr/WPPT) is considered and it is shown how analysis of the forecast error can be used to build a model of the quantiles of the forecast error. Only explanatory variables or indices which are predictable are considered, whereby the model obtained can be used for providing situation-dependent information regarding the uncertainty. Finally, the article contains directions enabling the reader to replicate the methods and thereby extend other forecast systems with situation-dependent information on uncertainty. Copyright © 2005 John Wiley & Sons, Ltd.
- Type:
- Conference paper
- Language:
- English
- Published in:
- Wind Energy, 2006, Vol 9, Issue 1-2, p. 95-108
- Keywords:
- Wind power forecasting; Uncertainty; Quantile regression; Additive model
- Main Research Area:
- Science/technology
- Publication Status:
- Published
- Review type:
- Peer Review
- Conference:
- European Wind Energy Conference & Exhibition 2004
- Submission year:
- 2006
- Scientific Level:
- Scientific
- ID:
- 8758750
