How to plot room heat balance results in IES using Python

This post provides an IES Python script to plot the annual heat gain totals for all rooms in an IES building model.

Why do this?

This plot is really useful for checking that an IES building model is set up correctly and for understanding the variation in air temperatures and heating loads between the different rooms.

How to use this IES Python script

• Create an IES building model.
• Run a simulation.
• Download and install the IES Python script "PlotRoomHeatBalance.py" which is available here. (Instructions for adding Python scripts to IES can be found here).
• Run the Python script.
• Choose the IES results file (.aps file) in the file dialog box which appears.
• The figure will now be created and displayed.

Example

This example uses the Medium Office building in the IES starter geometry options (available from the IES start page).

By running the "PlotRoomHeatBalance.py" script, this figure is created:

This figure provides many insights into the performance of the building, such as:

• the rooms which are being heating or cooled ("Space conditioning sensible" - here the plenum room are not being heated)
• the solar gains in each room ("Solar gain" - there are higher values for south-facing rooms)
• the rooms with the largest fabric heat losses ("External conduction gain" - here the 1st Floor Interior room has large heat losses to the ground)
• the internal flow of heat from room-to-room ("Internal conduction gain" - heat is flowing out of the 3rd Floor Interior room and into the surrounding rooms.)

Next steps

• Download the "PlotRoomHeatBalance.py" IES Python script from here.
• View the IES technical documentation on its Python API here.
• Any issues please let me know. I will update the Python script file on GitHub as needed.
• Any requests for other Python scripts for IES? Please contact me.