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as long as I don't have any better solution (looking to HenryMoec), I started like the following:

  1. I defined a statistic-helper ('sensor.statistical_characteristic' type Median, 20 Values, max age 2 mins) of my shellyproem_total_active_power to eliminate peeks (e.g. my electric cooker is heavily PWM-ing). I am not sure, if I want middle value or median, PWM is an Endgegener.
  2. I defined a sensor helper ({{ float(states('sensor.statistical_characteristic')) + 30.0}} where the input is the above statistic and added 30W to the result. So the overall compensation should be 30W less than given by sensor values.

not so nice as HenryMoec's work but as long as I need to implement his solution, it …

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@webkonto
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@HenryMoec
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