FlexMeasures is the intelligent & developer-friendly EMS to support real-time energy flexibility apps, rapidly and scalable.

In this talk, we want to focus on the "developer-friendly" part, and demonstrate the steps it takes to turn FlexMeasures into a smart backend, for instance to power the intelligent scheduling in your new climate tech startup! (you can also tinker with this at home, of course)

In this highly relevant example, we assume you control the heating for your customers' buildings. There is a heat pump and solar panels. You promise your customers to heat their home with their own solar power if possible. You even promise to use the cheapest grid power when the sun isn't shining. Green building, low energy bill!

Our tutorial will turn this promise into reality ― in any case, the data-driven optimal computations you'd need (measuring and on/off control of hardware not included).

FlexMeasures is a Flask web server, so this tutorial will use Python. We will use the FlexMeasures API, but also its CLI and the Python client ― the possibilities are rich. We also show how to add custom logic in a FlexMeasures plugin.

In short, we will:

• create a new customer account with the relevant asset models for this use case (via a new API endpoint, e.g. called from your CRM)
• feed local measurements (e.g. solar, temperature) regularly into your FlexMeasures server, using the FlexMeasures Python client
• get the latest price and weather forecast data from third-party-APIs (regularly via cron jobs), using existing FlexMeasures plugins
• create forecasts for solar data and prices (regularly via cron jobs)
• call the FlexMeasures scheduler to compute when to draw green & cheap electricity for heating (via the FlexMeasures API) which you can out to use in the building
• define a cost reporter and let it run (regularly via cron jobs)
• configure a FlexMeasures dashboard to show the relevant data in one place

We hope to see you there, and that some of you get inspired to put some climate tech into the field!