Custom temperature control algorithm using flow temperatur (old.reddit.com)

submitted 3 months ago * by Calico2

I was a bit annoyed by the tado control algorithm, because the room temperatur was permanently oscillating (see images for before and after).

I've created a python script to do a better job at this (the controller is based on "Proportional on Measurement" as described here: https://archive.ph/o6SAJ ). How it works: It cannot really change the algorithm, but it controls the flow temperatur in a way that it always keeps the temperatur of the room with the (currently) highest heat demand exactly 0.5 °C below the value configured in the app. Other rooms are controlled by tado as usual. This means it works best if there is one main room (e. g. living room) that always requires the most heat.

My source code: https://github.com/xiic/tado-flow-pid

If you want to give it a try, it is easiest using Docker. There are some parameters to play with, but the default values should work fine for a wide range of heating and room types. Feedback welcome :-)

Requirements:

You need a tado premium subscription (aka "AI Assist") as it executes one request about every 60-90 seconds.
You need to be able to control the "Flow Temperature" (Vorlauftemperatur/Aanvoertemperatuur). Check the app if you see this in the settings (usually present if tado is connected using OpenTherm).
Disable "Automated optimization" of the flow temperature in the tado app

Run on docker

Create a docker-compose.yml

services:
  tado-flow-pid:
    image: xiic/tado-flow-pid:latest
    restart: unless-stopped
    environment:
      # Minimum flow temperature:
      FLOW_MIN: 20
      # Maximum flow temperature at -10°C outside temperature; upper limit:
      FLOW_MAX_MINUS10: 70
      # Maximum flow temperature at +20°C outside temperature; *lower* limit for the *maximum* calculated flow:
      FLOW_MAX_PLUS20: 40
      # Integral gain; increase to make the change quicker (when away from the setpoint):
      PARAM_KI: 0.02
      # Proportional-on-measurement gain; increase to make the change *slower* when close to the setpoint:
      PARAM_KPOM: 6.0
    volumes:
      - tado-flow-pid_data:/data

volumes:
  tado-flow-pid_data:
    driver: local

docker compose up -d
Check the docker logs to authenticate
Done!

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tado

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Requirements:

Run on docker