Full Content is available to subscribers

Subscribe/Learn More  >

Long-Term Wind Speed Forecasting Based on Seasonal Trends

[+] Author Affiliations
Petros P. Kritharas, Simon J. Watson

Loughborough University, Loughborough, Leicestershire, UK

Paper No. ES2009-90053, pp. 897-904; 8 pages
  • ASME 2009 3rd International Conference on Energy Sustainability collocated with the Heat Transfer and InterPACK09 Conferences
  • ASME 2009 3rd International Conference on Energy Sustainability, Volume 2
  • San Francisco, California, USA, July 19–23, 2009
  • Conference Sponsors: Advanced Energy Systems Division and Solar Energy Division
  • ISBN: 978-0-7918-4890-6 | eISBN: 978-0-7918-3851-8
  • Copyright © 2009 by ASME


Over the last three decades, significant research has been carried out in the field of wind power forecasting with operational tools, however, making their presence noticeable in the last 15 years. So far, most of the work done has focused on short term forecasting of wind conditions. This is mainly due to the operational need for trading electricity a few days or a few hours ahead of gate closure due to the daily fluctuating nature of the demand and the finite response time of generation plant. However, System Operators (SOs), generators and suppliers have a need for longer term predictions of the power traded in order to maximize financial profits, schedule maintenance, etc. This paper presents a time series analysis of historical observations of wind speed in order to project future wind speed trends. The results suggest that the seasonal trend in wind speeds is the most important factor but that there is some monthly autocorrelation in the data which can improve forecasts. The approach proposed for forecasting wind speeds a month ahead may be deemed useful to suppliers for purchasing base load in advance and to SOs for power systems maintenance scheduling up to a month ahead.

Copyright © 2009 by ASME
Topics: Wind velocity



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In