Sensitivity and Uncertainty Analysis of Building Parameters integrating energy, daylight and thermal comfort

Abstract: The objective of this thesis was to perform multidisciplinary sensitivity and uncertainty analysis of the building parameters integrating thermal comfort, energy and daylight. The case study of a Danish office building was used for performing the simulations. The study evaluated the suitability of developed methodology for further usage in the early design stages of the building projects. A literature review was conducted to summarize existing methods for sensitivity and uncertainty analysis as well as to identify the most commonly used variables. Eighteen building parameters such as window types, opaque constructions insulation thicknesses, infiltration rate, ventilation rate, setpoint and setback temperatures, internal gains, and surface optical properties were tested. Total energy consumption, number of rooms compiled with Danish Building Regulations thermal comfort requirements and spatial daylight autonomy, were used as the result indicators. After validation of the statistical model of Pearson’s method, Spearman’s rank-order correlation method was chosen for this study. Both the sampling method and sample size were carefully determined for the generation of sampling. Results of the study included the most crucial parameters for the case building optimization. In addition, the results showed the quantification of the uncertainty in according to the results. Filtering the best-performing multi-disciplinary results led to the identification of the best performance input regions according to the input parameters. A significant outcome of the study was the development of DIVA code and Python code in IES VE which could be further readjusted and reused based on the consultant needs.