Using the CEA API in Jupyter notebooks as an additional interface for advanced data manipulation

In this blog post, I’m going to introduce how I use Jupyter notebooks to interact with the CEA. In my research, I’m focusing on the impact of occupant behavior onto district energy demand and supply. For this purpose, I have to manipulate occupancy schedules on a building-by-building basis in the simulation. To automate this process over many scenarios, I am using Jupyter notebooks and the CEA API.

The CEA python environment already includes Jupyter. This means that there is no additional installation required and we can start right away. To create a new notebook in your desired location, start the CEA Console, navigate to your desired folder, and start Jupyter with the command:

jupyter notebook

Jupyter automatically starts in your default web browser. Navigate to your desired folder and create a new notebook. Here is the notebook that I created to interact with CEA via the API. You can learn the basics of the CEA API from reading through the code and text. The notebook is also available on my GitHub.