TA-23-C044 – Reimagining Energy-Efficient Cooling Through Comfort-Based Occupant-centric Micro-zonal Control

With the rising need to improve the efficiency of HVAC systems, one of the critical concerns is energy wastage in large thermal zones when the entire volume is conditioned to a single setpoint while the zone is only partially occupied. Micro-zonal occupant-centric control (MZOCC) is an emerging strategy in this matter and focuses on creating virtual micro-zones, each having independent diffuser level control. While the energy-saving potential of MZOCC has been conceptually established, there is a need to evaluate the thermal comfort of occupants and devise comfort-based control strategies. This is important because MZOCC aims at creating a micro-comfort zone only around the occupant, and increased airflow onto the occupants may cause draft discomfort. Further, since only a portion of the thermal zone is conditioned in MZOCC, there are high probabilities of discomfort due to temperature gradients and strategies must be developed to avoid it. This study aims at proposing and evaluating comfort-based control strategies for MZOCC. The objectives are to use experimentally validated transient state CFD models to explore thermal comfort (PMV, PD and thermal gradients using the 6 comfort parameters) within a thermal zone and suggest strategies for planning microzones, locating diffusers and airflow control to achieve maximum energy efficiency without compromising thermal comfort. Results indicate that tuning airflow conditions for comfort-based MZOCC improves energy efficiency within micro-zones, leading to about 40%-80% savings in total energy consumption. Compared to setpoint-based control, comfort-based control saves 25% more energy. Further, strategies such as using a setback (higher setpoint) temperature or using a setback airflow (low airflow rate) in all unoccupied micro-zones or in the micro-zones adjacent to the occupied micro-zones can help reduce discomfort due to thermal gradients and draft. This study provides significant contributions to the future development of smart MZOCC controllers by identifying airflow control strategies considering thermal comfort. Developing optimization models based on the understanding of this study and integrating them with building control systems using IoT networks poses a significant opportunity to address the current issue of energy wastage in large thermal zones.