PMV-optimized smart thermostat control for flexible HVAC operation in nearly zero-energy building

This paper introduces a smart thermostat (ST) control strategy for a monitored nearly Zero‑Energy Building (nZEB), integrating year‑round PMV‑based thermal comfort optimization with grid‑responsive scheduling. By continuously recording HVAC energy consumption and combining it with climatic data, the method enables comfort and energy optimization without requiring explicit envelope property information. A Python‑based genetic algorithm determines optimal indoor setpoints across eight functional zones with diverse occupancy patterns, enabling preconditioning during low‑tariff periods and eliminating standby loads when unoccupied. The results reveal strong interdependencies among climatic variables such as temperature, humidity ratio, wind speed, and enthalpy, while confirming that thermal comfort within ±0.5 PMV can be achieved through coordinated multi‑parameter adjustment. Compared with the Business‑as‑Usual (BAU) baseline, the ST scenario reduced summer cooling energy consumption by 15% (2118.5 → 1802.7 kWh), winter heating consumption by 18% (3397.1 → 2783.3 kWh), and summer peak‑day HVAC demand by 33%. Psychrometric analysis further clarifies seasonal enthalpy differences, supporting adaptive comfort boundaries. Energy Efficiency Index (EEI) evaluation and EPBD‑aligned labeling indicate upgrades to A++ and A in several zones, demonstrating the potential of smart thermostats to enhance building intelligence, maintain occupant comfort, and deliver flexible, low‑carbon HVAC performance in nZEBs.