Net ZEB Design Processes and Tools - Modeling, Design, and Optimization of Net-Zero Energy Buildings - page 224

O'Brien, Athienitis, and Kesik (2008) chose a cold sunny, cold cloudy, warm
sunny, and mild sunny day to illustrate passive solar phenomena. In the
following example, a typical solar neutral (Hayter et al. , 2001) house is
first simulated. Noting the modest solar gains, the second iteration includes
larger windows and substantial thermal mass. As seen in Figure 4.24 , these
actions reduce daily heating energy substantially - and by about 45%
annually.
Fig. 4.24 Example of use of solar design days. Both graphs show house
performance on a cold sunny day (clear with an overage outdoor
temperature of −15 °C). The graph on the left is for a house with small
windows that are distributed in all orientations, while the graph on the
right is for one with large south-facing windows and added thermal mass
A drawback to SDDs is that they require a model to be created in a
simulation tool that calculates (and reports) in an hourly or finer resolution.
This excludes some tools, such as HOT2000, which reports monthly energy
demand.
4.3.4.3 Parametric Analysis
Parametric analysis - the varying of a building parameter and performing
a simulation to quantify that parameter's impact - is a widely used design
strategy and application for BPS. The concept of Lines of Influence (LoI)
was described by Kesik and Stern (2008) to assess the plotted performance
metric (e.g., heating energy) as a parameter is changed. Parametric analyses
provide at least three valuable pieces of information:
1. The optimal or near-optimal value of a parameter . If the LoI for a
particular parameter indicates that an optimum value for it exists, the