Uptime HARVEST™ – Wind Energy II

The Problem

An operator of a global wind turbine fleet with several Gigawatts of installed capacity has a very strong financial motivation to maximise fleet performance. Even when in operation, wind turbines, similar to all power plant, may produce energy with an efficiency below the intended level if incorrectly configured. Many issues remain undetected for prolonged periods of time, leading to continuous financial losses and in the worst case, to complete system failure and associated downtime.

The Challenge

Detection and correction of such issues is extremely challenging given a very large number of turbines distributed across many sites and managed by many different service organisations. Field inspection of turbines is expensive due to the related labour and tooling costs, and limited resources prevent the operator from investigating all issues in adequate detail. Furthermore, in many cases it is known that individual turbines perform below the expected level, but the diagnosis and correction of such issues is often complex and expensive.

The Solution

Operational SCADA data is available from each turbine and can be gathered, managed and reported using a commercial solution such as Uptime HARVEST™. Once available, such data provides valuable information about the health state of almost all major systems in the wind turbine. Uptime HARVEST™ provides a fully automated solution for the analysis of such data, and generation of advisory support. The software uses a library of physics-based models to analyse multiple systems within the wind turbine and to generate events wherever unexpected system behaviour is detected. Combined with a logic-based reasoning engine, under-performing turbines are identified, proposals for the most likely root cause are generated and recommendations for follow-up inspection and repair activities are made.

The Commercial Impact

Using Uptime HARVEST™ to support fleet performance analysis activities, a large fleet of wind turbines is continuously monitored. Performance issues are detected automatically, and using the diagnostic capabilities of the software, analysts are able to quickly generate recommendations that are passed on to service technicians, leading to corrective actions. The overall performance of the fleet is therefore improved with a minimum of effort and cost.

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