Energy & utility digital twins for reliable, resilient operations
Model your generation assets, substations, grids, and energy flows as living digital twins—so you can plan safely, prevent outages, and operate with confidence in a rapidly changing energy landscape.
Utilities are balancing more risk than ever
Energy and utility organizations are expected to deliver near-perfect reliability while integrating renewables, managing aging infrastructure, meeting regulatory requirements, and responding to extreme weather and demand volatility.
Common challenges in energy & utility environments:
- Aging assets with incomplete or inconsistent condition data
- Growing complexity from distributed energy resources and renewables
- Outage events that cascade across interconnected systems
- Limited ability to test restoration or load scenarios safely
- Regulatory and public scrutiny after failures or service disruptions
When systems are tightly coupled, decisions made in one area can create unintended consequences elsewhere. Intelligent digital twins help utilities see and manage those interdependencies.
From reactive response to system-level foresight
For energy and utilities, an intelligent digital twin provides a living model of how assets and networks behave under real operating conditions.
It continuously represents:
- Asset condition across generation, transmission, and distribution
- Load, flow, and constraint interactions across the grid
- How weather, demand, and outages affect reliability
- How operational decisions ripple through the system
With an intelligent digital twin, teams can:
- Identify emerging asset risks before failures occur
- Simulate outage, restoration, and load-balancing scenarios safely
- Evaluate the impact of renewables and new demand sources
- Make informed decisions without putting customers or crews at risk
Energy & utility use cases powered by intelligent digital twins
Asset Health & Reliability
Understand risk across fleets—not just individual assets.
- Monitor condition trends across substations, transformers, and equipment
- Compare similar assets under different operating contexts
- Prioritize maintenance based on risk and system impact
Outage Planning & Restoration Simulation
Prepare for disruptions before they happen.
- Simulate outage scenarios and cascading effects
- Test restoration sequences safely
- Improve response time and coordination during real events
Energy Optimization & Load Planning
Balance reliability, cost, and sustainability.
- Model demand, generation, and energy flows
- Test load shifting and operational strategies
- Understand the impact of renewables and storage
Grid & Network Resilience
Plan for extreme conditions and long-term change.
- Stress-test infrastructure under weather and demand scenarios
- Identify weak points before they fail
- Support long-term investment and upgrade decisions
(Often combined with outage planning and asset health use cases)
Supporting decisions across the organization
Grid and control room operators
- See a live, system-level view of asset health and constraints
- Understand which issues threaten reliability now—and which can wait
- Respond to events with better situational awareness
Reliability and asset managers
- Track degradation trends across fleets
- Prioritize inspections and maintenance with confidence
- Reduce surprise failures and emergency repairs
Planners and system engineers
- Evaluate the impact of new generation, load growth, or retirements
- Test future scenarios without risking service
- Support evidence-based regulatory and investment planning
What utilities typically aim to improve
While results vary by network and starting point, energy and utility teams often target:
Fewer unplanned outages
and service interruptions
Improved asset utilization
and longer asset life
Faster, safer outage response
and restoration
Better visibility
into system risk and constraints
Stronger confidence
in planning and regulatory reporting
The biggest value comes from understanding the system as a whole—not optimizing assets in isolation.
Start with one area. Prove value. Expand system-wide.
Start
Focus on a high-risk asset class, region, or recurring outage scenario.
Prove
Use real operational data to validate insights and planning improvements.
Scale
Extend the twin across additional assets, regions, and scenarios—reusing proven patterns.
Common questions from utility teams
See how intelligent digital twins can strengthen grid reliability
Start with one challenge—asset risk, outages, or planning—and build from there.