Few electric grids were designed to meet the demands of today’s electrified and connected society. Most utilities have invested in monitoring high-voltage transformers, yet medium-voltage transformers remain largely ignored. The need for an advanced maintenance strategy has never been greater.
Using AI-driven digital twins, transformer specialists and grid-control operators can solve performance issues before they disrupt operations, alleviate the bottlenecks of unexpected downtimes and forecast future needs.
Transformer specialists are surrounded by data, but only a handful leverage critical information to extend asset longevity and improve performance. Digital twins enable utilities to move beyond simple reporting by forecasting how and where to invest based on AI-generated data insights.
Transformer Health Digital Twin equips utilities with a powerful tool to develop asset health scores that consider more than two dozen critical aspects,
including oil levels, oil temperature, load data, IR scans and bushing condition. With a digital twin that considers real-time transformer monitoring data, telemetry sensor/relay data and maintenance information, utilities can make operational and strategic decisions faster and more confidently while achieving better results.
