Accessibility navigation

Determining the bounds of skilful forecast range for probabilistic prediction of system-wide wind power generation

Cannon, D., Brayshaw, D. ORCID:, Methven, J. ORCID: and Drew, D. (2017) Determining the bounds of skilful forecast range for probabilistic prediction of system-wide wind power generation. Meteorologische Zeitschrift, 26 (3). pp. 239-252. ISSN 0941-2948

Text (Open Access) - Published Version
· Available under License Creative Commons Attribution Non-commercial.
· Please see our End User Agreement before downloading.

[img] Text - Accepted Version
· Restricted to Repository staff only


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1127/metz/2016/0751


State-of-the-art wind power forecasts beyond a few hours ahead rely on global numerical weather prediction models to forecast the future large-scale atmospheric state. Often they provide initial and boundary conditions for nested high resolution simulations. In this paper, both upper and lower bounds on forecast range are identified within which global ensemble forecasts provide skilful information for system-wide wind power applications. The power system of Great Britain (GB) is used as an example because independent verifying data is available from National Grid. An upper bound on forecast range is associated with the limit of predictability, beyond which forecasts have no more skill than predictions based on climatological statistics. A lower bound is defined at the lead time beyond which the “resolved” uncertainty associated with estimating the future large-scale atmospheric state is larger than the “unresolved” uncertainty associated with estimating the system-wide wind power response to a given large-scale state. The bounds of skilful forecast range are quantified for three leading global forecast systems. The upper bound defined by forecasts of GB-total wind power generation at a specific point in time are found to be 6-8 days. The lower bound is found to be 1.4-2.4 days. Both bounds depend on the global forecast system and vary seasonally. In addition, forecasts of the probability of an extreme power ramp event were found to possess a shorter limit of predictability (4.5-5.5 days). The upper bound to useful forecast range can only be extended by improving the global forecast system (outside the control of most users) or by changing the metric used in the probability forecast. Improved downscaling and microscale modelling of the wind farm response may act to decrease the lower bound to useful forecast range. The potential gain from such improvements have diminishing returns beyond the short-range (out to around 2 days).

Item Type:Article
Divisions:Interdisciplinary Research Centres (IDRCs) > Walker Institute
Interdisciplinary centres and themes > Energy Research
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:45951
Publisher:Gebrueder Borntraeger Verlagsbuchhandlung


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation