Sessions
Reducing operational costs onshore
When: Wednesday, 24 November 2021, 10:45 - 12:15
Where: Auditorium A11
Session description
Operations and maintenance (O&M) costs still represent a significant fraction of the overall levelized cost of energy (LCoE) from wind turbines. Better estimates of loads and remaining useful lifetime (RUL) can facilitate longer component lifetimes and further reduce LCoE. To reduce O&M costs and make more informed choices requires well-placed measurements, smart use of data and improved turbine models.
This session will:
• Explore the use of artificial intelligence to make use of turbine data to predict RUL and make informed O&M decisions.
• Investigate the use of both wind turbine Supervisory Control and Data Acquisition (SCADA) and higher frequency Condition Monitoring System (CMS) data for predictive maintenance.
• Present sensor solutions for monitoring potential faults and predicting possible failure.
• Unpick the hype around ‘digital twins’ and show what they can actually do in practice.
Session chair
Simon Watson
Professor of Wind Energy Systems and Director of DUWIND, TU Delft
Presentations
Investigation of the Measurability of Selected Damage to Supporting Structures of Wind Turbines
Johannes Rupfle
Research Associate, Technical University of Munich
Estimation of rotor and main bearing loads using artificial neural networks
Amin Loriemi
Scientific Assistant, Chair for Wind Power Drives
Practical applications of digital twins: case studies from the real world
Edoardo Cicirello
Wind Domain Expert at GreenPowerMonitor, a DNV company, DNV
AI-based condition monitoring and predictive maintenance framework for wind turbines
Janine Maron
Analyst, WinJi AG
Deep Learning-based predictive maintenance for improving wind turbines reliability
Federica Bertoni
Digital Data Scientist, Falck Renewables SpA
Service Optimization of Wind Turbine Drive Trains - a fast track from CMS IoT signals to service solutions
Mihail Ivanov
Product Manager Digitalisation, ZF Wind Power
Eating though yaw motors to deliver fatter performance
Chris Hansford
Senior Engineer, DNV
