Operational Drift Detection for Thermal Power Plants
Drift is the dominant mechanism through which thermal power plant efficiency erodes. ControlAlign™ makes drift detection deterministic — reconstructed from the unit's own historian record, against its own demonstrated reference state.
Why drift is rarely detected in time
Thermal power plant performance does not collapse — it drifts. The mechanisms are gradual, distributed across the unit, and frequently masked by load, ambient and fuel variability. By the time drift is visible in routine performance reporting, it has typically been present, accumulating, for months.
Conventional drift detection relies on periodic performance tests, KPI thresholds and engineering judgement. These are valuable, but they are not continuous, and they are rarely normalized against the unit's own demonstrated optimum.
Drift as deviation from demonstrated reference
ControlAlign™ interprets drift as deterministic deviation from the unit's best demonstrated performance envelope — reconstructed continuously from the historian record and normalized for load, ambient and fuel quality.
Drift indicators are engineering-reviewable, not inferred. They are traceable to specific historian tags and to a specific reference state revision. This is the operational interpretation discipline that sits beneath heat rate improvement and thermal power plant efficiency outcomes.
How drift detection is delivered
Read-only, deterministic, and continuous across the operating life of the unit.
Historian extraction
Read-only ingestion from PI / Aveva / GE Proficy historians.
Load & ambient normalization
Isolation of true thermodynamic drift from operational variability.
Reference-state reconstruction
The unit's own best demonstrated performance envelope, derived from its historian record.
Deterministic deviation interpretation
Continuous identification and quantification of deviation, with engineering-reviewable causation.
Fleet-scale drift comparability
Cross-unit, cross-site visibility of drift severity and recoverable performance.
Audit-grade reporting
Every drift indicator traceable to source historian tags and reference state revision.
What continuous drift detection delivers
- Drift identified and quantified before it propagates into measurable heat rate degradation.
- Engineering-reviewable causation rather than opaque inference.
- Fleet-level visibility of which units are aligned, drifting, or recoverable.
- Direct contribution to boiler optimization and power plant optimization outcomes.
- Audit-grade reporting suitable for plant engineering, fleet leadership, regulator and infrastructure sponsor.
Deterministic drift interpretation — not anomaly inference
ControlAlign™ does not infer anomalies from opaque models. It reconstructs the unit's reference state and interprets deviation from it deterministically — historian-derived, reproducible and audit-grade.
Move from generic industrial AI to deterministic operational reference alignment
ControlAlign™ is the historian-derived operational reference-alignment layer for thermal power fleets. Request an operational assessment against your own historian environment.