17:00 - 18:30 Condition-based decision support
This session will describe current and explore application of new methods and sensors for the condition monitoring of wind turbines. Laboratory and field-based technologies will be explored and their operational effectiveness and expected added value quantified.
- Analyse new methods for monitoring turbine health and performance
- Quantify the operational effectiveness of condition-based monitoring
- Explore new sensors for turbine health monitoring
- Quantify the value of prognostics
Lead Session Chair:
Simon Watson, Loughborough University, United Kingdom
Jannis Weinert (1) F Ursula Smolka (2) Bjoern Schuemann (2) Po Wen Cheng (3)
(1) Ramboll / Stuttgart Wind Energy University of Stuttgart, Hamburg, Germany (2) Ramboll, Hamburg, Germany (3) Stuttgart Wind Energy, University of Stuttgart, Stuttgart, Germany
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Jannis Weinert is an Energy Engineering graduate of the University of Stuttgart. In his studies he focused on hydro and wind energy. The presented research was undertaken in the framework of a Master’s thesis at Ramboll Offshore Wind. He gained further industrial research experience in an internship at Voith Hydro Ocean Current Technologies.
Jannis is now a PhD student at the Centre for Renewable Energy Systems Technology (CREST), Loughborough University participating in the EU funded "Advanced Wind Energy Systems Operation and Maintenance Expertise" (AWESOME) project. His research focuses on the development of wind turbine fault detection algorithms.