Studying the Impact of Shading on Thermal Comfort: A Step-By-Step Guide
I previously made the case for why Operative Temperature is a great design metric: it aligns well with the ultimate goal of occupant comfort, it’s a more complete picture than air temperature alone, and it captures potential problem areas that whole-building metrics like EUI can miss. Because of these things, it can be a great tool for making the case for sustainable design strategies like shading.
As an example, I previously looked at Operative Temperature in a school, with and without shading devices. We saw that EUI and air temperature barely moved, but shading made a big difference for peak loads and operative temperature.
Here’s how I did that study — and created the final graphics pictured above — using just SketchUp, Excel, and Sefaira’s Thermal Comfort analysis.
Step 1: Prepare the model
I created a quick study model based on the building floor plan. I added custom zones by drawing the rooms on the floor plates. (No need to add interior walls.) In this case, I wanted results on a room-by-room basis, so that’s what I drew — but you could draw any zoning configuration you like. (If using Revit, add rooms to achieve the same result.)
Then I checked Entity Assignments and uploaded to the Sefaira web app.
Step 2: Set up the Analysis
In Sefaira’s web app, set up your Envelope, Space Use, and HVAC parameters — or, for early comparative studies, use Sefaira’s defaults. If you haven’t modeled windows, you can enter overall glazing percentages in the Window-to-Wall Ratio card.
Make sure Zoning is set up correctly. In this case, I wanted to use the custom zones I drew in SketchUp, so I selected “one zone per room” in the Zoning tab.
Step 3: Run a Thermal Comfort Simulation
Go to the “Comfort” tab and turn on Thermal Comfort analysis. Adjust your temperature criteria as desired, then run the analysis.
In this example, I used Operative Temperature, which is often a better predictor of occupant comfort than Dry Bulb Temperature, because Operative Temperature takes radiant temperatures into account.
Then, interpret the results. If zones are not passing, click to see whether they’re over-heated, under-heated, or both. The interpretation will naturally lead to hypotheses about how you could improve performance. In this case, my south- and west-facing zones are overheating, suggesting a solar gain problem that could be mitigated with lower-SHGC glazing or shading devices.
Sidebar: Why are my zones failing?
Keep in mind that zones in conditioned buildings often fail Operative Temperature criteria! This is because HVAC systems are typically controlled by air temperature — so even though the setpoints are being maintained, radiant temperatures (e.g. from solar gain) could cause operative temperatures to exceed the comfort thresholds.
If you’re having trouble getting zones to pass, here are a couple of common issues:
- Your setback and setpoint temperatures are far apart, and you have a short setback ramp-up and/or a slow ramp-up of internal loads in your Diversity Schedule. These can result in early morning hours failing comfort criteria.
- Your operative temperature criteria may be too close to your setpoints. Operative temperature will rarely match setpoints perfectly because the radiant temperatures of surfaces will be hotter or colder than air temperatures.
For more troubleshooting tips, see Sefaira’s Knowledgebase.
Step 4: Test the impact of Shading
Now comes the fun part: test your hypotheses. In this case, I wanted to test the impact of shading. I made a copy of my Baseline case, then added shading to the facades where overheating was an issue, and re-ran the analysis.
You could use the same process to study window-to-wall ratios, glazing properties, insulation levels, etc.
Step 5: Visualize the Results
Below I show how I used SketchUp and Excel to visualize results. But this is just one of many possible options: You can easily capture and use the images directly from Sefaira; you can download the overall annual data for manipulation (as I did), or you can download the hour-by-hour data to create heat maps or other custom visualizations.
