Come meet the poster presenters to ask them questions and discuss their work
Check the programme for our poster viewing moments. For more details on each poster, click on the poster titles to read the abstract. On Wednesday, 6 April at 15:30-16:15, join us on Level 3 of the Conference area for the Poster Awards!
PO099: Performance indicator calculation based on state & event processing
Moritz Gräfe, Uptime Engineering
Accurate monitoring of operational performance is a key concern for wind farm operators aiming to improve efficiency and minimize levelized cost of electricity. Different key performance indicators (KPI) are commonly used in the industry to assess asset performance from a technical or financial point of view. Well-known indicators for performance on turbine and wind farm level are time based and production-based availability in different forms. Beyond fleet operation these indicators are of special relevance as part of contracts between operators and OEM. Other important performance indicators such as Mean Time to Failure or Mean Time to Repair are focused on reliability or maintenance process efficiency. Despite rather simple definitions of KPIs and general availability of necessary data, calculation is challenging in reality for different reasons. Heterogeneous contract clauses within a fleet have to be considered. Complex asset structures must be well represented in a digital twin for proper assignment of information to a sub-system. Heterogeneous input data from different sources such as SCADA systems, maintenance process data or meteorological information must be processed. The requirement analysis resulted in a generic state & event processing system with free definition of attributes for mapping various legal and operational requirements.The state & event system was implemented in the Horizon 2020 ROMEO project as functionality of a comprehensive O&M information management platform which serves the need to merge data and information of heterogeneous nature to derive advisory statements for most efficient fleet operation.