Predictive controllers for thermal comfort optimization and energy savings

The present work is focused on the study of indoor thermal comfort control problem in buildings equipped with HVAC (heating, ventilation and air conditioning) systems. The occupants’ thermal comfort sensation is addressed here by the well-known comfort index known as PMV (predicted mean vote) and by a comfort zone defined in a psychrometric chart. In this context, different strategies for the control algorithms are proposed by using an only-one-actuator system that can be associated to a cooling and/or heating system. The first set of strategies is related to the thermal comfort optimization and the second one includes energy consumption minimization, while maintaining the indoor thermal comfort criterion at an adequate level. The methods are based on the model predictive control scheme and simulation results are presented for two case studies. The results validate the proposed methodology in terms of both thermal comfort and energy savings.