May Zune, Maria Kolokotroni
Languages: English | Pages: 10 pp
Bibliographic info:
42nd AIVC - 10th TightVent - 8th venticool Conference - Rotterdam, Netherlands - 5-6 October 2022

Occupants in residential buildings usually control natural ventilation through window openings. However, few studies have developed simple rules based on the outdoor weather forecast that can inform the occupants to predict the indoor condition by applying natural ventilation for thermal comfort and indoor air quality (IAQ). This paper describes a model based on indoor/outdoor correlations, derived through simulations using EnergyPlus and CONTAM, to help occupants maintain internal environmental quality manually or through simple controls. Simulation test cases were defined considering factors that can statistically change correlations, including the effect of single-sided and cross-ventilation, trickle ventilators, different schedules for window opening, heating and occupancy, size of the model, and building orientation for the window opening. The study found strong correlations between external and internal hourly temperatures, as well as between airflow and wind speed, and the inverse temperature differences between outdoor and indoors. The derived model consists of coefficients of determination (R2) between the correlated parameters and a set of equations to calculate thermal comfort and pollutant concentrations in the space. The derived correlations are then used independently to predict internal operative temperature and ventilation rates. Based on these parameters, thermal comfort is evaluated for the next period (hours or days) to predict overheating (based on the adaptive thermal comfort model) and indoor concentrations using contaminant mass balance equations for indoor CO2 concentration. An example of the application of this model is presented for a location in central Europe where a pilot building of the PRELUDE H2020 project is located. The findings of this study indicate how to reduce a large amount of data down to a manageable form, useful for occupants to identify indoor conditions for their space based on climatic conditions. This study highlights the importance of a user-driven decision-making process for predicting the indoor conditions from outdoor climatic parameters which could encourage behavioural change strategies and effective use of natural ventilation for thermal comfort and IAQ.