Case Study: V2i Energia S.A. cuts wind turbine overheating losses by 33% with Delfos Energy's AI predictive maintenance

V2i Energia S.A reduces overheating downtime by 60% with Delfos Energy

V2i Energia S.A., a wind farm operator, faced a recurring challenge with overheating failures in their wind turbines at the Mangue Seco site, which was a major cause of energy loss and unplanned downtime. Partnering with vendor Delfos Energy, they sought a solution to address the root cause of these failures, specifically alarms indicating overtemperature in the excitation system heatsink.

Delfos Energy developed a predictive maintenance tool using artificial neural networks to forecast heatsink temperature and issue alerts before a failure could occur. This solution allowed V2i to perform targeted maintenance during optimal periods. The implementation resulted in a 33% reduction in the energy impact of these failures and a 60% decrease in downtime, significantly increasing the wind farm's availability and efficiency.

V2i Energia S.A