Day 1 - Wednesday 18 October 2017

Registration And Refreshments


Chair’s Opening Remarks

Thomas Pump, Head Of Asset Information Systems, E.ON

Using Data To Reach The Full Potential Of Your Wind Farm


Keynote Address: Using Data To Improve O&M Efficiency And Drive Down The LCOE

  • What has moved on with data capabilities?

  • Utilising automation and smart systems to reduce the number of times you send employees offshore

  • Planning operational activities based on weather forecasting

  • Driving down costs without eroding the certainty in level of results

  • How to increase the life of a turbine and decrease maintenance required for less OPEX expenditure

  • How can you demonstrate return on investment for data initiatives?

Jeff Bryan, Market Analysis Manager, Natural Power


The 1st Open Data Windfarm : “La Haute Borne”

  • Strategically making digitalisation a major focus area in the transformation for greater efficiency

  • Why ENGIE decided to make public the data of the “La Haute Borne” wind farm and what is it all about?

  • Bringing together a community for improved wind turbine operation and developing wind farm services

  • Capitalizing on the increasingly large amount of data available

Nicolas Girard, Head Of R&D & Technical Support, ENGIE Green


Applying Operational And Event Data To Understand The Turbine’s Performance And Reliability Behaviour

  • Why data is needed to describe continuous condition of wind turbines
  • Identifying abnormal behaviour to assess and improve performance
  • Enabling predictive maintenance by association analyses

Stefan Faulstich,  Reliability Analyst,  Fraunhofer IWES


Morning Refreshments And Networking


Case Study: Improving Wind Farm Data Quality, Performance Diagnostics And Issue Resolution

Tim Naylor,  Director, Envision

Forecasting Failure And Performance Degredation With Better Measurement Tools And Analysis


Creating Opportunities For LCOE Reduction By Employing Data, Reliability, And Innovative Tools In Wind Turbine Electrical Components

  • Why electrical components in wind turbines are important for LCOE reduction?

  • What kind of data is required for degradation performance and reliability assessment of electrical components?

  • 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


The Future Of LiDAR On Operational Wind Farms: OWA Power Curve Tests With LiDAR – Evaluating Nacelle And Floating LiDAR To Validate Power Curves

  • A look at analysis of wind turbine performance tests using LiDAR in a number of use cases – nacelle based, TP based and floating.
  • An overview of the process and the lessons learned.
  • Analysis of the uncertainty with LiDAR relative to traditional cup anemometry.
  • Recommendations and best practices for undertaking power performance tests with LiDAR.
Michael Stephenson, Offshore Wind Associate, Carbon Trust

Networking Lunch


Measurement And Optimisation Of Blade Angle Deviations And Quantification Of Subsequent Performance Improvements

  • How to measure blade angle deviations pros/cons of different systems on the market
  • Development of a calculation method to quantify the performance improvements after correction of the blade angles
    • Impact of blade angle misalignments on the measured wind speed on top of the nacelle
    • Is the performance correlation with neighbouring turbines a reasonable approach to quantify the improvement?
  • 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

Understanding Preventative Maintenance, Prognostics And Artificial Intelligence To Improve O&M Activities


Predictive Analytics Of Turbines – Combining Multiple Data Sources

  • How 1 0 min SCADA data is analyzed to identify turbines with deviating signals and applying machine learning methods
  • Integrating vibration measurements with the SCADA data to improve drivetrain analysis
  • Indentifying serious issues early before expensive parts are affected and long downtimes occur
  • Downtime identification and categorisation processes
  • Connecting SAP data to streamline the work process and enrich the detections

Tobias  Winnemöller, Asset Optimisation Wind -  Asset & Pipeline Management, E.ON


Turning Predictive Analysis Into Preventative Maintenance: Fleet-Based Operational Optimisation As An A.I. Task

  • Getting enough good data for the task
  • How combining data sources can result in better predictions
  • Turning data alarms into workable task orders
  • 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


Challenges And Solutions To Operationalise Predictive Analytics

  • Hands-on strategies to build and operate predictive insights
  • How to imbed insights into organization – a stepwise approach
  • The importance of clear feedback measurements in a scrum-based development of a predictive program

Anders Hvashoj,  CEO and Founder,  ZEVIT


Networking Break And Afternoon Refreshments


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!


Chair's Closing Remarks 

Thomas Pump,  Head Of Asset Information Systems, E.ON


End Of Day 1