08:30
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Registration And Refreshments
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09:00
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Chair’s Opening Remarks
Thomas Pump,
Head Of Asset Information Systems,
E.ON
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Using Data To Reach The Full Potential Of Your Wind Farm
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09:15
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Keynote Address: Using Data To Improve O&M Efficiency And Drive Down The LCOE
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What has moved on with data capabilities?
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Utilising automation and smart systems to reduce the number of times you send employees offshore
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Planning operational activities based on weather forecasting
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Driving down costs without eroding the certainty in level of results
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How to increase the life of a turbine and decrease maintenance required for less OPEX expenditure
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How can you demonstrate return on investment for data initiatives?
Jeff Bryan,
Market Analysis Manager,
Natural Power
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09:45
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The 1st Open Data Windfarm : “La Haute Borne”
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Strategically making digitalisation a major focus area in the transformation for greater efficiency
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Why ENGIE decided to make public the data of the “La Haute Borne” wind farm and what is it all about?
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Bringing together a community for improved wind turbine operation and developing wind farm services
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Capitalizing on the increasingly large amount of data available
Nicolas Girard,
Head Of R&D & Technical Support,
ENGIE Green
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10:15
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Applying Operational And Event Data To Understand The Turbine’s Performance And Reliability Behaviour
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Why data is needed to describe continuous condition of wind turbines
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Identifying abnormal behaviour to assess and improve performance
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Enabling predictive maintenance by association analyses
Stefan Faulstich,
Reliability Analyst,
Fraunhofer IWES
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10:45
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Morning Refreshments And Networking
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11:15
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Case Study: Improving Wind Farm Data Quality, Performance Diagnostics And Issue Resolution
Tim Naylor,
Director,
Envision
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Forecasting Failure And Performance Degredation With Better Measurement Tools And Analysis
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11:45
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Creating Opportunities For LCOE Reduction By Employing Data, Reliability, And Innovative Tools In Wind Turbine Electrical Components
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Why electrical components in wind turbines are important for LCOE reduction?
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What kind of data is required for degradation performance and reliability assessment of electrical components?
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What are the state-of-the-art tools for design of electrical components to fulfill a specific reliability target?
Huai Wang,
Associate Professor,
Aalborg University
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12:15
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The Future Of LiDAR On Operational Wind Farms: OWA Power Curve Tests With LiDAR – Evaluating Nacelle And Floating LiDAR To Validate Power Curves
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A look at analysis of wind turbine performance tests using LiDAR in a number of use cases – nacelle based, TP based and floating.
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An overview of the process and the lessons learned.
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Analysis of the uncertainty with LiDAR relative to traditional cup anemometry.
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Recommendations and best practices for undertaking power performance tests with LiDAR.
Michael
Stephenson,
Offshore Wind Associate,
Carbon Trust
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12:45
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Networking Lunch
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13:45
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Measurement And Optimisation Of Blade Angle Deviations And Quantification Of Subsequent Performance Improvements
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How to measure blade angle deviations pros/cons of different systems on the market
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Development of a calculation method to quantify the performance improvements after correction of the blade angles
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Impact of blade angle misalignments on the measured wind speed on top of the nacelle
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Is the performance correlation with neighbouring turbines a reasonable approach to quantify the improvement?
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Verification of the developed calculation method using a LiDAR for the complete characterization of the incoming wind field
Dr Thomas Burchhart,
Fleet Performance Analyst,
VERBUND Hydro Power GmbH
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Understanding Preventative Maintenance, Prognostics And Artificial Intelligence To Improve O&M Activities
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14:15
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Predictive Analytics Of Turbines – Combining Multiple Data Sources
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How 1
0 min SCADA data is analyzed to identify turbines with deviating signals and applying machine learning methods
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Integrating vibration measurements with the SCADA data to improve drivetrain analysis
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Indentifying serious issues early before expensive parts are affected and long downtimes occur
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Downtime identification and categorisation processes
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Connecting SAP data to streamline the work process and enrich the detections
Tobias
Winnemöller,
Asset Optimisation Wind -
Asset & Pipeline Management,
E.ON
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14:45
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Turning Predictive Analysis Into Preventative Maintenance: Fleet-Based Operational Optimisation As An A.I. Task
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Getting enough good data for the task
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How combining data sources can result in better predictions
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Turning data alarms into workable task orders
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Using signals from vibrations, scada data, temp data and pressure data to get a more effective overall picture of maintenance required
Elena Tsiporkova,
EluciDATA Innovation Lab & OWI-Lab,
Sirris
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15:15
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Challenges And Solutions To Operationalise Predictive Analytics
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Hands-on strategies to build and operate predictive insights
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How to imbed insights into organization – a stepwise approach
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The importance of clear feedback measurements in a scrum-based development of a predictive program
Anders Hvashoj,
CEO and Founder,
ZEVIT
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15:45
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Networking Break And Afternoon Refreshments
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16:15
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Speed Networking
Realising the importance of connecting with your peers, we organised a moderated networking session where delegates are prompted to meet others in brief 3/4 minute rounds. The moderator will be keeping track of time and announcing participants when to switch partners.
Make sure you bring lots of business cards along with you!
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16:45
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Chair's Closing Remarks
Thomas Pump,
Head Of Asset Information Systems,
E.ON
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17:00
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End Of Day 1
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