AI Incident Prediction Energy
The Problem
“Predict and prevent energy asset safety incidents”
Organizations face these key challenges:
Fragmented data across SCADA/DCS, historians, CMMS, lab systems, and safety reporting prevents a unified view of leading indicators and risk.
Threshold-based alarms generate high noise and miss complex precursor patterns, causing alarm fatigue and delayed interventions.
Aging infrastructure, load volatility, and increased cycling (renewables integration) accelerate wear and introduce new failure modes that static maintenance plans do not capture.
Impact When Solved
Real-World Use Cases
AI Grid Congestion Management
This AI helps optimize the layout of power grids to reduce congestion without increasing costs or carbon emissions.
AI Power Grid Congestion Management
This AI system helps manage electricity grid congestion by optimizing the layout and connections of the grid, reducing costs and emissions.
eGridGPT: AI-Assisted Power System Operation
eGridGPT is an AI tool that helps power system operators make better decisions by analyzing data and suggesting optimal actions.