Table 8 Energy consumption optimization mechanism breakdown.
From: Digital twin-driven deep learning prediction and adaptive control for coal mine ventilation systems
Optimization Mechanism | Energy Saving Contribution | Implementation Method | Quantitative Basis |
|---|---|---|---|
Fan speed optimization | 15.2% | Predictive demand-based adjustment | Average speed: 85%→72%, Power ∝ speed³ |
Ventilation-on-demand | 7.8% | Production-schedule-aware modulation | 16 h×100% + 6 h×70% + 2 h×50% vs. 24 h×100% |
Predictive feedforward | 2.7% | Anticipatory control using forecasts | Reduced overshoot and oscillation |
Airflow distribution | 1.3% | Dynamic regulator optimization | Minimized network resistance |
Total | 27.0% | Synergistic integration | 5,267→3,845 kWh/day |
