DesignBuilder can automatically run multiple simulations automatically adjusting up to 2 variables to create design curves. Design curves can be very useful as part of the design process to understand how building performance is affected by variations in the building configuration and operation. DesignBuilder allows you to generate curves to show how performance parameters like energy use, cost and comfort vary as key elements of the building design vary. You can select up to 2 design variables. For example you might want to plot the cooling energy consumption for the base design with a range of window to wall % and glazing types variations. The selection of the design variables is done using the Variables tab of the Parametric, Optimisation and UA/SA Analysis Settings dialog. Click on the Parametric tab on the Simulation screen to carry out parametric simulations.
The design curves are generated by automatically running multiple simulations of copies of the base design (i.e. the model defined on the edit screen) with the design variations applied.
Note: It is necessary to run the base simulation with monthly/annual outputs before opening the Parametric tab. The parametric simulations will all be run using the base calculation and model options. So the simulation period and all other options used in the parametric analysis is the same as that defined on the Simulation calculation options dialog.
The number of design variants that are tested for 2 variable tests is the number of variants for the first variable multiplied by the number for the second variable. The variations in the above example would be different combinations of Glazing type and Window to wall %. In all, 6 x 5 = 30 simulations would be required to generate the design curves in this example.
The graph above illustrates the impact of varying both the WWR and the heating setpoint temperature on annual heating load.
The image above shows a parametric analysis of total annual carbon emissions where glazing percentage is varied in a building with lighting control, heating and cooling for 4 different glazing types. It illustrates how optimum configurations can be identified using this approach.
Typical applications for parametric simulation are: