TUNEOPT: An Evolutionary Reinforcement Learning HVAC Controller For Energy-Comfort Optimization Tuning

HVAC systems dominate building energy use. Existing energy–comfort co-optimization often relies on manual tuning of the trade-off coefficient, limiting generalizability across scenarios. TUNEOPT proposes an implicit evolutionary RL approach that learns and adapts this trade-off online within a predictive comfort–energy co-optimization formulation for setpoint control, improving both energy efficiency and occupant comfort.