ControlAlign™ · Industrial Thermodynamic Intelligence — LNG · CCS/CCUS · Refining · Petrochemicals · Thermal Power · Biomass · Industrial Steam & Process Heat
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Demonstration interface · All values shown are illustrative mock data
ControlAlign™ · Fleet Layer · Thermodynamic Intelligence Architecture

ControlAlign™ Fleet Intelligence

A live thermodynamic interpretation layer for industrial thermal fleets — showing where each asset is operating away from its own demonstrated best thermal state. Deployed today across thermal-power fleets; designed to extend to LNG trains, refining heat networks, and industrial process-heat ecosystems on the same architecture.

ControlAlign™ converts plant historian data into fleet-level operating intelligence. Each unit is compared against its ControlAlign™ Baseline of Best Performance, allowing owners to see efficiency drift, excess fuel use, recoverable value, and emissions impact across the fleet.

Fleet Operating View
Live demonstration · Updated continuously from plant historians
Window: Last 24 h
Total MW Monitored
6,950
15 units
Units Monitored
15
3 sites
Fleet Efficiency Gap
3.67%
vs ControlAlign™ Baseline
Excess Coal · Today
3,668 t
Cumulative 24 h
Recoverable Value · Today
$403.5k
@ $110/t coal
Avoidable CO₂ · Today
8,876 t
Scope 1

Fleet Map · Deviation From ControlAlign™ Baseline

Stable Watch Priority

Locations · Click to Inspect

Units nested under each location
Location 1
5 units · 660 MW capacity
Load640 MW
Avg Gap4.30%
Priority
Unit 1
640 MW
1.16%
Unit 2
640 MW
3.14%
Unit 3
640 MW
5.95%
Unit 4
640 MW
10.41%
Unit 5
640 MW
0.83%
Location 2
5 units · 500 MW capacity
Load480 MW
Avg Gap2.96%
Priority
Unit 1
480 MW
1.11%
Unit 2
480 MW
3.82%
Unit 3
480 MW
0.32%
Unit 4
480 MW
6.85%
Unit 5
480 MW
2.71%
Location 3
5 units · 230 MW capacity
Load210 MW
Avg Gap3.49%
Priority
Unit 1
210 MW
1.17%
Unit 2
210 MW
4.84%
Unit 3
210 MW
8.21%
Unit 4
210 MW
2.79%
Unit 5
210 MW
0.44%

Unit Detail · Unit 1

StableLocation 1
Current Load
640 MW
Current Fuel Intensity
0.612 kg/kWh
ControlAlign™ Baseline FI
0.605 kg/kWh
Performance Gap
1.16%
Excess Coal · Day
108 t
Recoverable Value · Day
$11.8k
Excess CO₂ · Day
260 t
Capacity Utilisation
97.0%
Fuel Intensity vs ControlAlign™ Baselinekg/kWh · 24 h
Load TrendMW · 24 h
Performance Deviation% gap · 24 h
Recoverable ValueUSD/day · 24 h
Demonstration data · Coal price assumed $110/t · CO₂ factor 2.42 t/t coal

From Plant Data to Fleet Decisions

ControlAlign™ does not rely on generic benchmarks. It uses each unit's own historical operating data to identify the best demonstrated performance envelope under comparable conditions. This creates a practical, defensible baseline for measuring efficiency drift, excess fuel use, and recoverable value.

Why Fleet Owners Need This View

01

Prioritise units by financial impact

Direct management attention to the units where recoverable value is largest, not just where alarms are loudest.

02

Detect efficiency drift before it normalises

Catch sustained separation from best-demonstrated performance before it becomes accepted as the new normal.

03

Quantify recoverable fuel value

Translate operational gaps into a defensible daily, monthly, and annual recoverable value across the fleet.

04

Link operations to emissions intensity

Connect every unit of excess fuel to its associated avoidable CO₂ — a single, audit-safe view of operational carbon.

Beyond dashboards. Performance intelligence.

Traditional plant systems show operating data. ControlAlign™ shows performance separation — the measurable distance between current operation and the unit's own best demonstrated state. This allows owners to focus management attention where operational value is being lost.

See what your fleet is losing against its own best performance.

Request Fleet Diagnostic Review
Industrial Applications · ControlAlign™
Industrial Thermodynamic IntelligenceThermal-State DiagnosticsIndustrial Heat-Transfer IntelligenceProcess Thermal StabilityIndustrial Operational ThermodynamicsIndustrial Energy Systems OptimisationProcess Heat & Energy-Intensity OptimisationCombustion & Radiative Coupling Optimisation