Projects per year
Neural networks were used to investigate if any relationship existed between maximum daily gust speed, average daily wind speed and temperature and wind turbine failure modes. Using five years of weather station data a typical site characteristic was determined using the neural network. This was then compared to a characteristic produced using only weather data for days when failures occurred. These failure and normal characteristics were then compared to determine if any relationships existed. It was found that in some sub-assemblies the failure trends differed to the normal conditions trend, suggesting that there may be relationships.
|Publication status||Published - Sep 2012|
|Event||IET International Conference on Sustainable Power Generation and Supply - Hangzhou, China|
Duration: 8 Sep 2012 → 9 Sep 2012
|Conference||IET International Conference on Sustainable Power Generation and Supply|
|Abbreviated title||SUPERGEN 2012|
|Period||8/09/12 → 9/09/12|
- wind turbines
- asset management
- SAP data
- wind turbine failure modes
- neural networks
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- 1 Finished
Effect of Seasonal Weather and Site Conditions on Wind Turbine Failures
Wilson, G., McMillan, D. & Blundell, K.
30/09/11 → 30/09/14
Project: Internally funded project