ABSTRACT Micro-Zonal Occupant-Centric Control (MZOCC) helps in reducing building energy consumption by conditioning only the occupied regions in a room. For this, MZOCC divides a large room such as open-plan offices into virtual micro-zones to allow independent diffuser level control. But, unplanned MZOCC can lead to heavy thermal gradients and deflection of air jets, leading to thermal discomfort. To evaluate thermal comfort at different regions of a room under MZOCC, there is a need to accurately model parameters of thermal comfort. Field studies, exploring the transient variations in air temperature, humidity and velocity at different regions of the room due to MZOCC, are limited. At the same time, developing validated simulation models or digital twins using experimental data helps in exploring micro-zonal strategies to arrive at the best strategy. The aim of this study is to create a digital twin of an open-plan office and model the parameters required to estimate thermal comfort. This study senses transient variations in air temperature, velocity and humidity using a wireless sensor network and develops a computational fluid dynamic (CFD) model that can accurately model the sensed transient variations. Field data, constituting external surface temperatures captured using thermal images, variations in air-conditioning control strategy, dynamic occupancy and location, are periodically updated in the digital twin. The CFD model accurately predicts the trends in variations in indoor temperature, velocity and humidity at different regions of the room. The developed digital twin can be used in future studies to evaluate thermal comfort and plan MZOCC control strategies.
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