AI & Analytics
Energy optimization connected to assets, work, and evidence
Identify energy waste patterns across equipment, facilities, and process systems. Connect baseline comparison, demand analysis, load optimization, work execution, savings verification, ESG reporting, and capital planning in one operating layer.
Energy proof
Energy optimization works best when it is connected to assets and work.
TwinEdge connects energy baselines, digital twin context, equipment condition, operating schedules, recommendations, AssetOps EAM, Field verification, ESG evidence, and capital planning so savings are not trapped in a chart.
Baseline
Expected use
Compare actual demand against operating-state-adjusted expectations.
Action
Operational changes
Recommendations can become work, setpoint review, or scheduling changes.
Verify
Savings proof
Track predicted vs actual performance with source evidence.
Common Waste Patterns
TwinEdge identifies these patterns automatically from sensor data. Percentage of total energy spend.
Off-Hours Operation
Equipment running during unoccupied periods. Chillers cooling empty buildings at 2 AM.
Poor Staging
Running three compressors at 60% instead of two at 90%. Lead-lag sequencing not optimized.
Degraded Efficiency
Fouled heat exchangers, worn impellers, and slipping belts reducing equipment performance.
Simultaneous Heating/Cooling
HVAC zones fighting each other. Reheat coils activating while chillers are running.
Peak Demand Spikes
Multiple high-draw systems starting simultaneously, triggering demand charges.
Typical Savings by Category
Real results from TwinEdge deployments across industrial and commercial facilities.
| Category | Before | After | Saving |
|---|---|---|---|
| Pump Systems | 0.42 kWh/m3 | 0.31 kWh/m3 | 26% |
| Chiller Plant | 0.85 kW/ton | 0.62 kW/ton | 27% |
| Compressed Air | 22 kW/100 CFM | 16 kW/100 CFM | 27% |
| HVAC Systems | 18.5 kBTU/sqft/yr | 13.2 kBTU/sqft/yr | 29% |
| Demand Charges | $12.50/kW | $8.20/kW avg | 34% |
Optimization Features
Baseline Comparison
Energy baselines can be adjusted for weather, occupancy, production volume, and operating state to compare actual vs expected consumption.
Peak Demand Analysis
Identify the top contributors to demand peaks. Model load-shedding scenarios and calculate demand charge savings.
Load Optimization
Recommendations for optimal equipment staging, setpoint adjustments, and scheduling changes. Quantified savings per action.
Savings Verification
IPMVP-aligned measurement and verification. Track actual savings against predicted savings with statistical confidence intervals.
Rate Schedule Analysis
Map consumption to utility rate structures. Identify opportunities to shift load from on-peak to off-peak windows.
Carbon Tracking
Convert energy consumption to CO2 equivalent using regional grid emission factors. Track against reduction targets.
Turn energy waste into verified operational improvement.
See exactly where energy is wasted and get actionable recommendations with verified savings tracking.