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Subseasonal-to-Seasonal Forecasting for Wind Turbine Maintenance Scheduling.

Authors :
Tawn, Rosemary
Browell, Jethro
McMillan, David
Source :
Wind (2674-032X); Jun2022, Vol. 2 Issue 2, p260-287, 28p
Publication Year :
2022

Abstract

Certain wind turbine maintenance tasks require specialist equipment, such as a large crane for heavy lift operations. Equipment hire often has a lead time of several weeks but equipment use is restricted by future weather conditions through wind speed safety limits, necessitating an assessment of future weather conditions. This paper sets out a methodology for producing subseasonal-to-seasonal (up to 6 weeks ahead) forecasts that are site- and task-specific. Forecasts are shown to improve on climatology at all sites, with fair skill out to six weeks for both variability and weather window forecasts. For the case of crane hire, a cost-loss model identifies the range of electricity prices where the hiring decision is sensitive to the forecasts. While there is little difference in the hiring decision made by the proposed forecasts and the climatology benchmark at most electricity prices, the repair cost per turbine is reduced at lower electricity prices. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2674032X
Volume :
2
Issue :
2
Database :
Complementary Index
Journal :
Wind (2674-032X)
Publication Type :
Academic Journal
Accession number :
157822604
Full Text :
https://doi.org/10.3390/wind2020015