PREDICTIVE MAINTENANCE OF WIND FARMS

The increasing demand for renewable energy provides wind farm owners & operators a strong growth opportunity but also introduces new challenges such as the aging and increasing complexity of turbines :

• How to reduce turbine degradation and unplanned down time?
• How to lower operation, maintenance and repair costs?
• How to extend turbine’s life span and optimize its performance?

Current solutions focus on data analytics and machine learning techniques to improve health monitoring and enable predictive maintenance. These solutions provide important improvements but require large amounts of training data that need to include costly fault or failure incidents.

To overcome this, ESI’s Wind Twin Solution pairs advanced physics based modeling, including nominal and fault system modeling, finite element and reduce order modeling with the latest in data analytics and machine learning.

By working with ESI, it is now possibile for Wind Farms to improve the turbine health monitoring and diagnostics and implement predictive maintenance strategies while leveraging model based performance