Failure Prediction Secures 7,778 MWh of Generation Over 299 Days and Reduces Maintenance Costs

Context:

A 2.1 MW WEG wind turbine displayed abnormal behavior in its main bearing. Failures in this critical component can lead to unplanned downtimes, high emergency repair costs, and lost energy production during inactivity.

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Implemented Solution:

The Delfos Prediction Module utilized the turbine’s historical data to create predictive models capable of identifying deviations in the main bearing’s operational behavior.

• Day 0: The system detected a behavioral shift, identifying a temperature increase of 4.43°C beyond the model’s predicted uncertainty.
• Delfos’ solution allowed the operator to monitor the anomaly’s progression, apply temporary measures such as partial grease replacement, and strategically schedule the component’s definitive replacement after the peak wind generation period.

Achieved Results:

• 7,778.05 MWh generated during 299 days of continuous operation, without power limitations.
• 7,000 additional operational hours, even with an anomalous component.
• Reduced emergency maintenance costs, eliminating urgency fees and prioritizing a preventive maintenance plan.
• Optimized component utilization until the end of its life cycle, maximizing production.

Conclusion:

With the support of Delfos’ predictive module, the client avoided unplanned downtime, optimized energy generation, and reduced operational costs. This case underscores Delfos' reliability and value in the predictive management of critical assets.

Key Metrics:

• 299 days of continuous operation.
• 7,778.05 MWh generated without interruptions.
• 4.43°C deviation detected and monitored from the onset.
• 7,000 additional hours of production before planned maintenance.

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