Predict failures early. Plan maintenance with confidence.
Heat‑rate optimizer with approvals & guardrails.
Optimize hybrid portfolios to minimize curtailment.
Ingest: historian/SCADA data (vibration, temp, pressure, flows), CMMS work orders.
Models: anomaly detection, failure classification, RUL (remaining useful life).
Outputs: health scores, failure probability, maintenance windows, spare-parts recommendations.
Actions: work-order suggestions (API into Maximo/SAP), alert routing.Efficiency Optimizer (Heat-rate & Setpoint AI)
Ingest: boiler/turbine parameters, ambient conditions, fuel quality, emissions.
Models: surrogate models + constrained optimization (e.g., Pyomo/OR-Tools) or RL with safety guardrails.
Outputs: recommended setpoints with confidence + constraint compliance (NOx/SOx, ramp limits).
Actions: “Apply to DCS” is never direct—operators review & approve; change-management trail.
Load Forecasting
Ingest: historical load, weather/forecasts, calendar effects, DER/EV signals.
Models: hierarchical forecasts (15-min → day-ahead → seasonal), e.g., LightGBM/XGBoost + TFT (Temporal Fusion Transformer).
Outputs: probabilistic forecasts (P10/P50/P90), error bands, scenario explorer.
Renewable Integration & Dispatch
Ingest: plant availabilities, renewable/Storage SoC, PPA limits, market prices (if applicable).
Models: stochastic unit commitment / economic dispatch with renewables & storage.
Outputs: hour-ahead/day-ahead dispatch plan, curtailment minimization, reserve sizing.