Custom Component: ENTSO-e Day Ahead Energy Prices

[haraldov (Harald)]

I do not have any blueprint I can share, but you can make a template with Tibbers “PriceLevel” using the Entsoe price sensors.

template:
  - sensor:
      - name: "Prisnivå"
        unique_id: "pricelevel"
        state: >-
          {% if states('sensor.current_electricity_market_price')|float(0.5) >= states('sensor.average_electricity_price_today')|float(0.5) *0.9
              and states('sensor.current_electricity_market_price')|float(0.5) < states('sensor.average_electricity_price_today')|float(0.5) *1.15 %}
              NORMAL
          {% elif states('sensor.current_electricity_market_price')|float(0) >= states('sensor.average_electricity_price_today')|float(0) *0.6
              and states('sensor.current_electricity_market_price')|float(0) < states('sensor.average_electricity_price_today')|float(0) *0.9 %}
              CHEAP
          {% elif states('sensor.current_electricity_market_price')|float(0) < states('sensor.average_electricity_price_today')|float(0) *0.6 %}
              VERY_CHEAP
          {% elif states('sensor.current_electricity_market_price')|float(0) >= states('sensor.average_electricity_price_today')|float(0) *1.15
              and states('sensor.current_electricity_market_price')|float(0) < states('sensor.average_electricity_price_today')|float(0) *1.4 %}
              EXPENSIVE
          {% elif states('sensor.current_electricity_market_price')|float(0) >= states('sensor.average_electricity_price_today')|float(0) *1.4
              and states('sensor.current_electricity_market_price')|float(0) < states('sensor.average_electricity_price_today')|float(0) *2.0 %}
              VERY_EXPENSIVE
          {% elif states('sensor.current_electricity_market_price')|float(0) >= states('sensor.average_electricity_price_today')|float(0) *2.0 %}
              EXTREMELY_EXPENSIVE
          {% endif %}

Then you can make a template binary sensor which is ON when the price is expensive and OFF when price is normal or cheap. With this you can make a automation which use the binary sensor to heat when it is off and lower the temperature when it is on.

  - binary_sensor:
      - name: "Dyr strom"
        state: "{{ states('sensor.prisniva') == 'EXPENSIVE' or states('sensor.prisniva') == 'VERY_EXPENSIVE' or states('sensor.prisniva') == 'EXTREMELY_EXPENSIVE' }}"

You can also modify this blueprint which use Tibber price data to use Entsoe price data.

Tibber price and thermostat control

For Tibber users. Trigger actions (e.g. toggle HVAC) depending on temperature and electricity price. Actions are triggered intelligently when price, temperature or thermostat setting change. [Open your Home Assistant instance and show the blueprint import dialog with a specific blueprint pre-filled.] blueprint: name: Tibber price and thermostat control description: > Trigger actions (e.g. toggle HVAC) depending on temperature and electricity price. Actions are triggered *intelligently…

@lazmo88

Also, it would be quite interesting to have “cheapest x hour(s) slot/interval” available, so tasks consuming electricity for multiple hours (washing machine, EV charging etc.) could be scheduled accordingly. Is this already doable?

This code for finding the cheapest 1-2 hours and 1-3 hours with Entsoe is from @stigvi from this norwegian forum: https://www.hjemmeautomasjon.no/forums/topic/11102-strømpriser/?do=findComment&comment=106063

    - unique_id: billigste_timer_1_2
      name: billigste_timer_1_2
      state: >-
        {% set l=state_attr('sensor.average_electricity_price_today', 'prices')[14:]|sort(attribute='price') %}
        {% set t = now() %}
        {{ (t >= as_datetime(l[0].time) and t <= as_datetime(l[0].time) + timedelta(hours = 1))
          or (t >= as_datetime(l[1].time) and t <= as_datetime(l[1].time) + timedelta(hours = 1)) }}
    - unique_id: billigste_timer_1_3
      name: billigste_timer_1_3
      state: >-
        {% set l=state_attr('sensor.average_electricity_price_today', 'prices')[14:]|sort(attribute='price') %}
        {% set t = now() %}
        {{ (t >= as_datetime(l[0].time) and t <= as_datetime(l[0].time) + timedelta(hours = 1))
          or (t >= as_datetime(l[1].time) and t <= as_datetime(l[1].time) + timedelta(hours = 1))
          or (t >= as_datetime(l[2].time) and t <= as_datetime(l[2].time) + timedelta(hours = 1)) }}