A common question for those just starting with performance analysis is “Where do I begin?” With so many options to assess, from window-to-wall ratios to shading design, the task can seem daunting. Here’s a six-step methodology that will have you analyzing passive design strategies like a pro.
1. Identify your goals & how you’ll measure success
What are you looking to achieve? What you’ll measure depends on the project’s goals. For example, LEED energy credits are based on the percentage reduction in energy cost from an ASHRAE 90.1 baseline. The 2030 Challenge provides a target energy use per square foot (pEUI). Many daylighting standards have specific Daylight Factor or Daylight Autonomy thresholds that must be met. Identifying both the target and the metric will allow you to measure success.
Some common energy goals are the 2030 Challenge targets or a percentage reduction from an ASHRAE baseline.
2. Create a baseline
For many types of performance goals, you need to compare your design to a reference case, known as a “baseline.” In the LEED example above, ASHRAE 90.1 provides guidelines for creating a theoretical building with the same geometry as your design, but with specific envelope properties, window-to-wall ratios, HVAC systems, etc. You can get a good early approximation of this baseline by using Sefaira’s envelope, space use, and HVAC templates. For an analysis that doesn’t require a baseline, you can start with your original building design and then compare options against it.
Sefaira’s envelope, space use, and HVAC templates can help you quickly create a baseline energy model.
3. Interpret the baseline results
Once you’ve set up the baseline, run an analysis. Then answer the following questions:
What’s the dominant energy use? Is it heating, cooling, lighting, or something else? You’ll want to focus on the biggest end uses first.
What are the primary sources of heat gain & loss? These will help you understand what’s driving your cooling and heating loads, respectively.
What’s driving peak loads? Look at the top contributors to zones with high peak heating & cooling loads. Is there a pattern? Reducing peak loads can reduce the size and cost of the HVAC system, or can expand the range of HVAC options.
What areas are underlit or overlit? Use Sefaira’s Underlit & Overlit analysis to highlight these potential problem areas.
Next, brainstorm possible passive design strategies that could address these issues. For example, if your cooling loads are large and primarily driven by solar gain, you may want to reduce solar gains with shading or glazing improvements. The “Guidance” tab in Sefaira’s Real Time Analysis plugin can help you identify possible solutions.
Visualize and interpret energy analysis results in order to understand where you should focus.
4. Test various strategies
Now test the strategies you’ve identified, both alone and in combination. Evaluate them against your targets from step 1. When it comes to combining passive design strategies, here are a few guidelines to keep in mind:
Start with the strategies that have the biggest impact, then progressively layer others on top of that.
Look at groups of strategies that are related to one another. For example, when optimizing window-to-wall ratio, also look at shading and glazing properties, as these factors all affect one another. To explore this space, you could fix two of these variables with an approximate design value — say window U-factor of 0.3, and horizontal shading — then optimize the third — in this case, the window-to-wall ratio.
If you want to be exhaustive, you can create a matrix of options to test that combine strategies in various ways. For example, you could create a series of models that test combinations of building form (from compact to extended) and window-to-wall ratio (from low to high).
5. Use Response Curves to optimize
As you begin to iterate toward a set of strategies that achieves your goal, Response Curves can help in two ways.
First, it can help you determine how big an impact a particular variable can have. In the image below, the most benefit you’ll squeeze out of south horizontal shading by itself is a change in EUI of 0.11% — not much.
Second, Response Curves can help you find optimum values for specific parameters, such as window properties or shading length. Because the optimum value for most parameters depends on the rest of the building design, this optimization only makes sense to do once the other variables are close to what you expect them to be. For example, to optimize your shading lengths, make sure you’ve gotten the envelope properties, space use settings, and HVAC parameters in the right ballpark. If you make a big change to one of these other properties, you may need to reassess your shading design.
Response curves can help you identify optimum values, or evaluate the potential impact of a design strategy.
6. Present your results (and assumptions)
Finally, show your work. Include the project targets, baseline results, and recommended strategies. In many cases, it will make sense to include key input parameters in your presentation as well, so you can see at a high level what changed. For example, you may have improved lighting efficiency, added shading, and improved glazing specs. It’s helpful to see the values you used in each case. This can also serve as a quick double-check when others review your work.
Summarize your analysis results and inputs to present them to clients or team members.
By following this methodology, you’ve clearly articulated a goal and identified a path toward achieving it in a way that’s logical and transparent. If implemented early and often in design, this methodology can inform design decisions and help you tell a compelling story about the design and the value it provides to the client.