| Title |
Uncertainty in Sensitivity Analysis of Architectural Design Variables for Heating and Cooling Loads Depending on Usage Scenarios |
| Authors |
유영서(Yoo, Young-Seo) ; 이동혁(Yi, Dong-Hyuk) ; 박철수(Park, Cheol-Soo) |
| DOI |
https://doi.org/10.5659/JAIK.2021.37.11.247 |
| Keywords |
Building energy; Sensitivity analysis; Sobol method; Uncertainty analysis; Performance-based; decision making |
| Abstract |
It has been widely acknowledged that rational decision making at architectural design stage is important for energy efficient building design.
In other words, the relationship between building energy use and design variables must be carefully analyzed. For this purpose, the global
sensitivity analysis (GSA) can be a useful tool because GSA quantifies the unit change of a model’s output against the unit change of the
individual model input for the entire input space. With the use of GSA, the influence of each design variable can be quantified in terms of
sensitivity index. However, such sensitivity index can be dependent on crude assumptions for building usage scenarios, e.g. occupant density,
equipment density, infiltration rate, etc. In general, these parameters are set as deterministic values based on simulationist’s subjective
judgment, and it can be inferred that this subjective assmptions could cause uncertainty in sensitivity analysis. With this in mind, the authors
propose a sensitivity analysis process for building energy design variables considering the uncertainty of building use scenarios. For this
purpose, Sobol sensitivity analysis was performed on five design variables (wall U-value, fenestration SHGC, lighting power density, window
U-value, window-wall ratio) according to assumptions of five building usage scenarios (occupant density, equipment density, infiltration rate,
cooling and heating set-point temperatures). As a result, it is found that uncertainty in the sensitivity of design variables is significant and
the sensitivity ranking of the design variables can vary. This indicates that in order to reach rational decision making, careful attention must
be paid to selection of uncertain building usage scenarios, and stochastic sensitivity analysis must be employed. |