Simulation-based comparative analysis of zoned and non-zoned ducted HVAC systems in Canadian dwellings: impact of network versus single-zone airflow modeling

• AFN vs single-zone energy predictions assessed for zoned and non-zoned ducted systems. • AFN model improves the energy prediction accuracy versus the single-zone model. • Energy prediction errors of up to 16% are attributed to the single-zone model vs the AFN model. • The new TRNSYS single-zone AIM-2 component is validated against ESP-r model results. • Airflow modeling discrepancies across Canada are strongly influenced by climate. Zoned ducted systems can provide enhanced thermal comfort and energy efficiency compared to traditional non-zoned systems. Previous simulation studies of these systems have generally employed simplified or single-zone airflow models, which may not fully capture inter-zone airflows or the effects of mechanical pressurization, potentially affecting the reliability of predicted energy use and temperature distributions. This study presents a comparative analysis of zoned and non-zoned ducted systems in Canadian residential buildings, emphasizing improved accuracy of energy and thermal performance predictions through the use of an airflow network (AFN) model. Four building energy simulation (BES) models are developed in TRNSYS to represent non-zoned and zoned ducted configurations, each evaluated using both the AFN and single-zone airflow models. The AFN is implemented via the TRNFlow module, while the single-zone airflow model is simulated using a newly developed TRNSYS Type capable of representing the Alberta Infiltration Model (AIM-2), whose accuracy is validated against ESP-r simulation results. The study evaluates six distinct Canadian climate regions for each BES model, resulting in 24 simulation scenarios. System performance is analyzed by calculating the relative energy savings between scenarios within each climate region. Results indicate that using AIM-2, which neglects inter-zone effects, underpredicts the energy consumption of the non-zoned system by up to 4%, while overpredicting it for the zoned system by up to 12%. Moreover, using AIM-2 to calculate the relative energy savings of zoned versus non-zoned systems can produce underestimation errors of up to 16%. These findings generalize to regions with comparable heating degree days (HDDs).