Jinho Park

Model-Based Reinforcement Learning for HVAC Energy Optimization Under Hot, Mixed, and Cool Climates

HVAC control trades energy against thermal comfort, complicated by two building features: thermal mass spreads a setpoint change over hours, and the input-to-outcome mapping shifts across the year. Model-free algorithms such as PPO, SAC, and TD3 carry no model of building dynamics and cannot evaluate a setpoint’s downs...