Optimizing space heating and cooling through digital control and predictive mean vote thermal comfort index

Abstract

Increased awareness on sustainability and rising energy costs have intensified the need for more efficient and occupant-responsive building operation. In this context, this study evaluates the use of Fanger’s Predicted Mean Vote (PMV) index as a Heating, Ventilation and Air Conditioning (HVAC) control strategy within Building Management Systems (BMS), comparing it to traditional occupant-driven or fixed-range temperature set-point methods commonly used in commercial and public buildings. Three consecutive occupied-environment tests were conducted, each employing a different control approach: full occupant control, restricted temperature-range control, and a PMV-based fixed set-point. HVAC energy consumption and indoor environmental conditions were collected through the building installed BMS and then analysed together with occupant thermal comfort surveys. Results indicate that PMV-based control is a feasible and potentially effective methodology, capable of maintaining thermal comfort while reducing energy consumption. The study further shows that more refinement and broader testing could enable PMV-driven control to support more efficient, comfort-oriented building operation.