Optimize Viessmann Vitodens 200-W

After I had already integrated my Viessmann Vitodens 200-W via OptoLink and thus made it controllable, there were of course plenty of further possibilities to optimize the heating behavior.

The previous heating behavior led to fluctuations of up to 1 degree along the adjusted comfort temperature. Furthermore, the manufacturer-side control heats only on the basis of data from the past. i.e. with strong outside temperature fluctuations like autumn or spring, she was almost always wrong. Furthermore, no factors such as open windows, position of the sun or the structural conditions of the home are taken into account.

All these shortcomings had to be solved with a new logic.

Burner control

First, I first considered how you can reliably turn on and off the heater burner without having to intervene in the hardware of the heater. Generally you should not fumble about such things. I found them via the detour of the reduced operation.
Normally, the burner starts at a certain temperature threshold and switches off again as soon as the heater detects that the generated energy is not being removed quickly enough. Unfortunately, this only works with 100% correctly set floor heating. In my case, the result was that the burner tried again and again to start again and go out shortly thereafter. This resulted in some 1000 burner starts a day.
If, on the other hand, the heating is switched to the reduced mode and after some time back to normal operation, this causes the heating system to temporarily overdrive, allowing enough time for the underfloor heating to “settle in” with the result that the burner starts at approx. 5 to 10 a day and run much smoother. In addition, it can be controlled in this way even when the burner should be on and off.
Reduced operation means “off” and normal mode “on”.

Heating demand calculation

In my calculation of needs, I see the house as a kind of large heat storage in which is filled by heating and sunlight and emptied by heat loss through walls and windows again.

The following data are taken into account.

Now there are 2 openHAB rules which run every 2 minutes and calculate the heat storage status as well as the decision whether to heat or not.

1. Rule - Calculation of the heat storage

This is even the simpler of the two rules. Here are two values calculated. First the energy supply and secondly the energy outflow.

Energy supply

The energy supply is calculated from the temperature difference of the supply line and the return flow of the underfloor heating. For this I attached two temperature sensors to the corresponding copper tubes. In addition, the speed of the circulation pump and thus the flow speed can be read out of the heater. In this way you can calculate exactly the amount of energy in watts that is supplied to the house every minute. In addition, it is calculated how much the sun shines on each window and whether the shutters are down or up.

Underfloor heating water temperature sensor

Energy drain

The energy drain, in turn, is calculated from the thermal conductivity and the area of the outer walls and the temperature difference between the rooms and the outside air. In this way you can calculate how much watts of energy is lost to the room per minute. In addition, it is taken into account whether a window in the corresponding room is open or closed and how much energy escapes through it.
To calculate the temperature difference, I have equipped all rooms with temperature sensors. Details can be found in the section Arduino environmental sensors.

Arduino temperature sensorAssembled Arduino prototype

Heating correction

A third factor is the amount of energy needed to heat the house by 0.1 degrees based on its construction procurement. Here, the storage capacity of the building materials plays a crucial role. Every time the house has warmed by 0.1 degrees, I pull that energy requirement off the heat storage.

Thus, the level of the heat accumulator results from the following formula:

New stored amount of energy = Old stored amount of energy + Energy supply - Energy drainage - Energy requirement in the event of house warming

Log messages from calculation of heating storage

As sources of information the following links were very helpful

Especially the U value calculator should be mentioned here which helps to calculate the thermal conductivity and heat storage capacity of building materials. Not only the masonry itself plays a role, but also what kind of interior plaster, exterior plaster and its thickness and all kinds of additional insulation. Be it on the masonry itself, in the floor slab or on the roof.

2. Rule - Calculation of heating demand

To calculate the heating demand, it is first calculated how high the difference between the current room temperature and the set comfort temperature is. Afterwards it is calculated how much energy one needs to reach this warming. Again, the storage capacity of building materials plays a crucial role. If the required amount of energy is less than the amount of energy that is already stored in the house does not need to be heated. This almost reflects the inertia of underfloor heating.

Requirements determination

But if energy is needed, it calculates how long it takes to heat up to provide that amount of energy. For this calculation hypothetical values ​​are assumed. That is, it is assumed that a maximum heating power. In addition, forecast data (4 and 8 hours) of the outside temperature, the position of the sun and the degree of cloudiness are used to calculate the energy outflow. From this it is possible to calculate in advance when the heating system has to start in order to reach a certain target temperature within a certain time window.

i.e. Again, the inertia of a floor heating is taken into account. It starts, no matter what the weather, early enough to heat at night so it is warm in the morning when you get up. Likewise, it just stops to heat up early enough so that one does not notice the lowering of the nighttime as long as one is awake.

Log messages from calculation of heating demandCalculation details inside the mobile app

When calculating the heating demand, the following things are taken into account

Conclusion and sources

As a result, the temperature is controlled so accurately that it is only subject to a fluctuation of 0.1 to 0.2 degrees. In addition, my gas consumption has fallen by about 30%.

The openHAB rules to calculate and control the heating are part of my deployment project and can be downloaded there. Alternatively, they can also be obtained directly from my Github Repository.

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