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Open Access Publications from the University of California

Performance, Prediction and Optimization of Night Ventilation across Different Climates


Night ventilation, or night flushing, is a passive cooling technique that utilizes the outdoor diurnal temperature swing and the building’s thermal mass to pre-cool a building through increased outdoor airflow at night, allowing radiant cooling to take place during the day when the building is occupied.  Previous studies have demonstrated a potential reduction in cooling load and improvement in comfort from the implementation of night ventilation.  However, very few field studies have been done looking at the impact of location and climate on night ventilation performance.


This thesis describes the performance, in terms of indoor environmental conditions, of three buildings from both the U.S. and India that use night ventilation as their primary cooling method.  The analysis is based on monitored data collected from each building (ranging in duration from two months to one year), including indoor and outdoor air temperature, mass temperature, supply temperature, and airflow rate. The first building, located in Oakland, California, uses forced ventilation at night to increase the airflow.  The second building, located in Sunnyvale, California, uses natural ventilation by means of automated windows.  The third building, in Auroville, India, uses natural ventilation by means of occupant-controlled windows.  The research methods used the following approach: 1) Assess the cooling strategy by comparing indoor conditions from days that did and did not use night ventilation, specifically in relation to the adaptive comfort model;  2) Develop a hybrid model, using both first principle equations and the collected data, to predict the instantaneous air and mass temperatures within each building; 3) Determine an optimized ventilation control strategy for each building to minimize energy and maintain comfortable temperatures.


The study yielded the following results: 1) The buildings in the mild climate are successfully keeping the indoor temperature low, but also tend to be overcooling;  2) The night ventilation strategy has very little impact on the indoor conditions of the buildings in the mild climate; 3) The impact of night ventilation is less significant when there is low internal loads and heavy mass; 4) The building in the hot and humid climate is keeping the indoor temperature within the comfort bounds for 88% of the year; 5) The night ventilation strategy has advantageous impact on indoor conditons of the building in the hot and humid climate, but not enough to cool the space on its own; 6) Model predictive control has the potential to further improve the performance of night ventilation.

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