Grid Predictive Maintenance Intelligence

This AI solution uses AI, machine learning, and digital twins to continuously monitor distribution networks, microgrids, and connected assets to predict failures, optimize maintenance, and improve power flow control. By anticipating equipment issues, tuning voltage and power management, and guiding EV integration, it reduces outages, avoids costly emergency repairs, and extends asset life while supporting more renewables on the grid.

The Problem

“Predict failures and optimize grid maintenance & power flow using time-series ML + twins”

Organizations face these key challenges:

Unplanned outages and repeated “mystery trips” with unclear root cause

Maintenance is calendar-based or reactive, causing unnecessary truck rolls and overtime

Voltage violations and congestion events increase as DER/EV penetration grows

Data is siloed across SCADA/AMI/PMU and asset systems, making risk hard to quantify

Impact When Solved

Fewer unplanned outages and emergency repairsHigher asset utilization and longer asset lifeMore renewables and EVs on the grid without costly upgrades