DocumentCode
647889
Title
Wave height forecasting to improve off-shore access and maintenance scheduling
Author
Dinwoodie, Iain ; Catterson, V.M. ; McMillan, David
Author_Institution
Inst. for Energy & Environ., Univ. of Strathclyde, Glasgow, UK
fYear
2013
fDate
21-25 July 2013
Firstpage
1
Lastpage
5
Abstract
This paper presents research into modelling and predicting wave heights based on historical data. Wave height is one of the key criteria for allowing access to off-shore wind turbines for maintenance. Better tools for predicting wave height will allow more accurate identification of suitable “weather windows” in which access vessels can be dispatched to site. This in turn improves the ability to schedule maintenance, reducing costs related to vessel dispatch and recall due to unexpected wave patterns. The paper outlines the data available for wave height modelling. Through data mining, different modelling approaches are identified and compared. The advantages and disadvantages of each approach, and their accuracies for a given site implementation, are discussed.
Keywords
data mining; geophysics computing; maintenance engineering; ocean waves; oceanographic techniques; offshore installations; wind turbines; access vessels; costs reducing; data mining; maintenance scheduling; off-shore access; off-shore wind turbines; wave height forecasting; wave height modelling; Artificial neural networks; Data models; Maintenance engineering; Mathematical model; Predictive models; Training; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location
Vancouver, BC
ISSN
1944-9925
Type
conf
DOI
10.1109/PESMG.2013.6672438
Filename
6672438
Link To Document