Performance evaluation of passive cooling in office buildings based on uncertainty and sensitivity analysis

Natural night ventilation is an interesting passive cooling method in moderate climates. Driven by wind and stack generated pressures, it cools down the exposed building structure at night, in which the heat of the previous day is accumulated. The performance of natural night ventilation highly depends on the external weather conditions and especially on the outdoor temperature. An increase of this outdoor temperature is noticed over the last century and the IPCC predicts an additional rise to the end of this century. A methodology is needed to evaluate the reliable operation of the indoor climate of buildings in case of warmer and uncertain summer conditions. The uncertainty on the climate and on other design data can be very important in the decision process of a building project. The aim of this research is to develop a methodology to predict the performance of natural night ventilation using building energy simulation taking into account the uncertainties in the input. The performance evaluation of natural night ventilation is based on uncertainty and sensitivity analysis. The results of the uncertainty analysis showed that thermal comfort in a single office cooled with single-sided night ventilation had the largest uncertainty. The uncertainties on thermal comfort in case of passive stack and cross ventilation were substantially smaller. However, since wind, as the main driving force for cross ventilation, is highly variable, the cross ventilation strategy required larger louvre areas than the stack ventilation strategy to achieve a similar performance. The differences in uncertainty between the orientations were small. Sensitivity analysis was used to determine the most dominant set of input parameters causing the uncertainty on thermal comfort. The internal heat gains, solar heat gain coefficient of the sunblinds, internal convective heat transfer coefficient, thermophysical properties related to thermal mass, set-point temperatures controlling the natural night ventilation, the discharge coefficient Cd of the night ventilation opening and the wind pressure coefficients Cp were identified to have the largest impact on the uncertainty of thermal comfort. The impact of the warming climate on the uncertainty of thermal comfort was determined. The uncertainty on thermal comfort appeared to increase significantly when a weather data set with recurrence time of 10 years (warm weather) was applied in the transient simulations in stead of a standard weather data set. Natural night ventilation, designed for normal weather conditions, was clearly not able to ensure a high probability of good thermal comfort in warm weather. To ensure a high probability of good thermal comfort and to reduce the performance uncertainty in a warming climate, natural night ventilation has to be combined with additional measures. Different measures were analysed, based on the results of the sensitivity analysis. All the measures were shown to significantly decrease the uncertainty of thermal comfort in warm weather. The study showed the importance to carry out simulations with a warm weather dataset together with the analysis under typical conditions. This approach allows to gain a better understanding of the performance of a natural night ventilation design, and to optimize the design to a robust solution. 2010 Elsevier Ltd. All rights reserved