Abstract
Language | English |
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Number of pages | 9 |
Publication status | Published - 30 Sep 2013 |
Event | ESREL 2013 - Amsterdam, Netherlands Duration: 30 Sep 2013 → … |
Conference
Conference | ESREL 2013 |
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Country | Netherlands |
City | Amsterdam |
Period | 30/09/13 → … |
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Keywords
- wind turbine reliability
- wind turbine failure modes
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Modeling the effects of seasonal weather and site conditions on wind turbine failure modes. / Wilson, Graeme; McMillan, David.
2013. Paper presented at ESREL 2013, Amsterdam, Netherlands.Research output: Contribution to conference › Paper
TY - CONF
T1 - Modeling the effects of seasonal weather and site conditions on wind turbine failure modes
AU - Wilson, Graeme
AU - McMillan, David
PY - 2013/9/30
Y1 - 2013/9/30
N2 - It is important that the impact of the offshore environment on wind turbine reliability is reduced significantly due to the importance of offshore wind deployment to global energy targets. Future development may otherwise be compromised by unsustainable operation and maintenance (O&M) costs. This paper aims to improve the accuracy of offshore O&M models by accounting for any relationship between certain weather characteristics and wind turbine failure modes. This is done using maintenance data from a UK onshore wind farm and weather data from a weather station located nearby. Non-parametric Mixture Models are estimated from the data and they are used to calculate a more accurate, weather dependent, failure rate which will be used in future research for Markov Chain Monte Carlo Simulation. This research will be of particular interest to wind turbine operators and manufacturers
AB - It is important that the impact of the offshore environment on wind turbine reliability is reduced significantly due to the importance of offshore wind deployment to global energy targets. Future development may otherwise be compromised by unsustainable operation and maintenance (O&M) costs. This paper aims to improve the accuracy of offshore O&M models by accounting for any relationship between certain weather characteristics and wind turbine failure modes. This is done using maintenance data from a UK onshore wind farm and weather data from a weather station located nearby. Non-parametric Mixture Models are estimated from the data and they are used to calculate a more accurate, weather dependent, failure rate which will be used in future research for Markov Chain Monte Carlo Simulation. This research will be of particular interest to wind turbine operators and manufacturers
KW - wind turbine reliability
KW - wind turbine failure modes
UR - http://www.esrel2013.nl/
M3 - Paper
ER -