Forecasting Life Cycle and Sustainment Costs With Wind Turbine Sensors

The Two-Decade Wind Turbine Life Cycle

The wind turbine life cycle spans some 20-25 years, but year-to-year sustainment costs and failure rates vary significantly across that time. The highest failure rates actually occur within the first 3 years or so — often due to issues that need ironing out with new models or suboptimal calibration of operating controls. Turbines that survive the break-in process will generally run for the next decade or two with little to no problems outside of routine maintenance. After 18-20 years, components start wearing out and failure rates increase.

The cumulative lifecycle and sustainment costs over a two-decade wind turbine life cycle are estimated to add up to 65-90% of the total investment cost. Maintenance is by far the most costly aspect of life cycle sustainment. The global cost of onshore wind operations and maintenance soared to $15 billion in 2019 (including $8.5 billion on unplanned repairs and remediation of component failure).

Proactive Maintenance Improves Life Cycle Sustainment

These costs are significant in an era where wind energy is no longer subsidized. A reactive approach is nearly always more expensive than proactive one, however. Operators seeking to reduce lifecycle costs will need the tools to engage in both styles of proactive maintenance: preventative and predictive.

• Preventive Maintenance: Maintenance can be regularly and proactively scheduled to stay ahead of failures and increase throughput on the wind turbine life cycle. A preventive approach results in 12-18% lower cost than purely reactive maintenance, as waiting for problems to arise can cause additional damage and result in further complications from unplanned downtime.
• Predictive Maintenance: With a life model of wind turbine sensor data and robust analysis, it’s possible to predict component degradation and estimate the remaining useful life of equipment. Accurate predictions allow for targeted replacements or maintenance (before a failure) and ultimately 8-12% cost savings compared to preventive maintenance. Because predictive maintenance is informed by data rather than simply routine, it’s less labor intensive.

“Major” failures — with downtime of one day or more — only make up about a quarter of wind turbine errors, but they’re responsible for 95% of total downtime. The best way to prevent a major failure is to amass nuanced data for an accurate predictive model.

Amass Data With Wind Turbine Sensors

The majority of current wind turbines feature SCADA (Supervisory Control and Data Acquisition) sensor systems that collect data on RPM, power produced, wind characteristics, and other basic operational parameters. This data is useful, but insufficient for assessing component degradation, damage, and fatigue. Maintenance evaluations still depend too heavily on manual observation.

According to Eleni Chatzi, chair of Structural Mechanics and Monitoring at ETH Zürich,“Unfortunately, because existing tools have not yet caught up with the maturity of wind turbine technology, visual inspection and offline evaluations remain the norm.” What’s needed is a reliable and cost-effective wind turbine life cycle monitoring system.

TurboTrack from Sensatek

A fully implemented TurboTrack sensor network allows wind farmers to gather direct measurements of torque, strain, thermal changes, and other structural parameters on components like wind turbine blades, drivetrains, and gearboxes. This data is invaluable in efforts to predict (or even extend) the wind turbine life cycle and keep sustainment costs under control. 

Transient torque events such as high wind spikes or abrupt de-loading of a generator can have a significant impact on rotor bearings and the shaft connected to the gearbox. Sensors in wind turbines create a life model of strain and thermal activity within these parts — critical to forecasting their remaining useful life or failure risk. Recent research continues to prove that “the use of embedded sensors in wind turbines could potentially reduce maintenance costs and increase EOL profit.” 

TurboTrack is designed to capture and characterize straining events while monitoring structural performance throughout the operational life of the turbine. Contact Sensatek today to discuss the TurboTrack system and how it can help you forecast wind turbine life cycle and sustainment costs.