Analyzing the Relation between Input Data and Key Performance Indicators for Building Energy Certificates: An Approach Using Algorithmic Modeling

Abstract

(no german abstract) This contribution concerns the reproducibility of energy certificates. To examine the impact of different input data assumptions on the results of energy certificates, sensitivity analysis was performed. Conducting such sensitivity analysis manually is not only time consuming and error-prone, but is also typically limited in view of input- data/result combinations. This can be a problem, as a number of input data combinations can have contradictory influences on corresponding KPI (key performance indicator) results. For instance, transparent building components increase not only solar gains, but also transmittance losses. As an alternative to manual modification of input data, the parametric algorithm-editor, Grasshopper (an Add-on to the CAD/CAM-environment Rhino) was utilized. The calculation standards of the Austrian energy certificate procedure were implemented in this environment. Input data values can be modified via a graphical user interface (rulers), and the impact of the change is instantly generated by the environment. Past research regarding planners' usage of energy certificate tools identified usability and overall user acceptance of such calculation tools as a weak spot. Thus, the implementation of calculation routines within a widely used drafting/parametrization tool could result in increased acceptance by planners. In a first methodological approach, the impact of input assumptions regarding building typology and window properties on solar gains, transmittance losses, and heating demand were considered.

This contribution concerns the reproducibility of energy certificates. To examine the impact of different input data assumptions on the results of energy certificates, sensitivity analysis was performed. Conducting such sensitivity analysis manually is not only time consuming and error-prone, but is also typically limited in view of input- data/result combinations. This can be a problem, as a number of input data combinations can have contradictory influences on corresponding KPI (key performance indicator) results. For instance, transparent building components increase not only solar gains, but also transmittance losses. As an alternative to manual modification of input data, the parametric algorithm-editor, Grasshopper (an Add-on to the CAD/CAM-environment Rhino) was utilized. The calculation standards of the Austrian energy certificate procedure were implemented in this environment. Input data values can be modified via a graphical user interface (rulers), and the impact of the change is instantly generated by the environment. Past research regarding planners' usage of energy certificate tools identified usability and overall user acceptance of such calculation tools as a weak spot. Thus, the implementation of calculation routines within a widely used drafting/parametrization tool could result in increased acceptance by planners. In a first methodological approach, the impact of input assumptions regarding building typology and window properties on solar gains, transmittance losses, and heating demand were considered.