Previous dynamic building simulation studies have not often focused on analysing the sensitivity of peak loads to input parameters. However, these peak loads may have a critical impact on system design capacities and power network operation. This study aims to examine the sensitivity of cooling demand related results (total electricity demand, HVAC end-use and space cooling) in a large office building using two global sensitivity analysis methods: Morris elementary effect and Sobol indices. More specifically, this paper examines the implications of different type of climates to the uncertainty in these different cooling output results and the sensitivity of the different parameters for each result. Moreover, this paper investigates the difference between the effects of annual and peak analysis for cooling demand of office buildings, which can provide insight on cooling demand from the perspectives of total cooling energy and system capacity for building cooling systems, respectively.
This study has found that generally, the changes are more significant for peak demand than for annual demand. The coefficient of variation for the total peak demand is around 25% and 21% for total annual demand. This study identifies that the ventilation rate is the parameter that contributes the largest for the uncertainty in electricity demand of the HVAC end-use, between 50% to 70% of the change (ST), both for annual and peak demand. Regarding the effect on total electricity demand, ventilation rate is still one of the most critical factors, but equipment and lighting densities also become a significant contributor to the sensitivity of the total demand.