Historical heating cycles learned by the ML model
Representative cycles are shown by default. Thin traces approximate historical variation; rare and excluded profiles can be enabled for comparison.
ML-only empirical model
ML-Only Boiler Power Prediction Demo
Learning heating-cycle patterns from historical power data
ML predicted power
0 W
Cycle progress
ML profile state
Historical cycle playback
HeaterOFF
Cycle time0.0 min
Draw-off classHigh
Simulation inputs
The ML model receives only hot water draw-off and elapsed cycle time.
Inferred from historical heating-cycle energy, not directly measured as flow.
Advanced physical reference parameters Elnett EUN 5 defaults
30.3 °C
The reference is integrated with a one-second step using energy balance, heat loss, and thermostat hysteresis. Continuous outlet flow during reheating is zero by default; prior hot-water draw-off is represented by the calculated lower start temperature.
Outside dense training range
Prediction may look precise but may not be meaningful.
12historical training cycles
Physics-informed data filter
Elnett EUN 5 reference: 5 L, 2 kW, measured 18 °C inlet and 59 °C maximum hot-water temperature.
Total detected cycles-
Representative used for ML-
Rare / possible draw-off-
Implausible / excluded-
Ideal full heat-up energy-
Ideal full heat-up time-
ML-only predicted power profile
ML-only prediction
Uncertainty
Current time
Physical model vs ML-only power prediction
ML-only prediction
Physical reference from estimated start temperature
Current ML power
0 W
Historical profile surrogate
Physical reference
0 W
Energy-balance model
Current difference
0 W
Mean absolute difference: 0 W
Training evidence
Sparse
11 cycles in selected class
ML demo self-check: pending