Add offset criteria for self-regulation when in over_climate which underlying that have a temperature sensor

[ikoz]

Version of the custom_component

5.2.2

Configuration

hvac_modes:
  - auto
  - heat
  - "off"
min_temp: 7
max_temp: 35
target_temp_step: 0.5
preset_modes:
  - none
  - frost
current_temperature: 17.5
temperature: 19.2
hvac_action: idle
preset_mode: none
is_on: true
hvac_mode: heat
type: null
is_controlled_by_central_mode: false
last_central_mode: null
frost_temp: 5
eco_temp: 0
boost_temp: 0
comfort_temp: 0
frost_away_temp: 7
eco_away_temp: 7
boost_away_temp: 7
comfort_away_temp: 7
power_temp: null
target_temperature_step: 0.5
ext_current_temperature: -3.31
ac_mode: false
current_power: null
current_power_max: null
saved_preset_mode: none
saved_target_temp: 19.2
saved_hvac_mode: null
window_state: "off"
motion_state: null
overpowering_state: null
presence_state: null
window_auto_state: "off"
window_bypass_state: false
security_delay_min: 60
security_min_on_percent: 0.5
security_default_on_percent: 0.1
last_temperature_datetime: "2024-01-18T09:23:38.671679+00:00"
last_ext_temperature_datetime: "2024-01-18T09:15:23.759238+00:00"
security_state: false
minimal_activation_delay_sec: 10
device_power: 1
mean_cycle_power: null
total_energy: 0.13
last_update_datetime: "2024-01-18T09:23:38.676592+00:00"
timezone: Europe/London
window_sensor_entity_id: null
window_delay_sec: null
window_auto_enabled: false
window_auto_open_threshold: null
window_auto_close_threshold: null
window_auto_max_duration: null
motion_sensor_entity_id: null
presence_sensor_entity_id: null
power_sensor_entity_id: null
max_power_sensor_entity_id: null
temperature_unit: °C
is_device_active: false
ema_temp: 17.45
is_over_climate: true
start_hvac_action_date: null
underlying_climate_0: climate.wiser_dinning_room
underlying_climate_1: null
underlying_climate_2: null
underlying_climate_3: null
is_regulated: true
regulated_target_temperature: 22.1
auto_regulation_mode: auto_regulation_strong
regulation_accumulated_error: 28.109999999999992
auto_fan_mode: auto_fan_none
current_auto_fan_mode: auto_fan_none
auto_activated_fan_mode: null
auto_deactivated_fan_mode: null
friendly_name: Dinning Room Thermostat
supported_features: 17

If it is releveant to regulation performance or optimisation some curves are needed

I'm attaching the following picture to show the problem. In this plot:

• PURPLE line: My desired target temperature (this has been set as target temperature in VTech climate entity)
• DARK BLUE line: The accurate temperature of the room (external zigbee sensor). This is the sensor set in VTech as external sensor.
• LIGHT BLUE line : The internal TRV temperature sensor - takeng from the TRV climate entity.
• ORANGE line: The TRV setpoint, configured by VTech (regulated temperature).
• DARK ORANGE vertical bars: the duration where the TRV was open and heating
  

Describe the bug

I'm was trying to heat the room to 17.2C and then 19.2C (from 6:30AM onwards) (purple line - vtech entity target temperature)
The real temperature of the room dropped below 17.2C around 3:00AM. (dark blue line)
You can see in the graph that around 3:00AM, Vtech started raising the TRV setpoint (regulated temperature - orange line).

However, the TRV did not actually open to let heat into the room, because the internal TRV temperature (light blue line) was higher than the regulated TRV setpoint (orange line) - or it jumped to immediately be higher after heating for a few minutes.

Then I raised the target temperature to 19.2C around 6.30AM. The same thing happened.

So Vtech has been trying to heat the room since 3.00AM and it is now 10AM and the room has not been heated, because the TRV has not actually opened for more than a few short bursts that each lasts a few minutes (vertical bars). These short bursts are also happening at "low demand %", since the demand % is the difference between regulated temperature setpoint and internal trv temperature. This is important, because I am using opentherm: Low demand % means low flow temperature, meaning very slow heating response.

I believe the Vtech self-regulation algorthm should take into account the internal TRV temperature of the climate entity, and calculate an "offset" based on the current value of the internal TRV temperature, so that the regulated temperature is above the internal TRV temperature, and the TRV lets water to flow.

For example I'd expect that if real room temperature is 16C, target temperature is 19C and internal trv temperature is 22C, then Vtech should set the regulated temperature to 25C (a lot higher than 22C, since 19C target is much higher than the 16C real temperature)

Let me know if you need a debug log, but it is fairly obvious what is happening here. VTech calculates the regulated temperature based on external room sensor, completely ignoring the internal TRV sensor. Even in 'hard' self-regulation mode, it cannot work. I am not sure it would work in expert mode either.

[jmcollin78]

Hello,

First thing, many thanks for respecting the template. I have all information in one post. This is great.

2nd thing, I guess VTech is VTherm in your post.

So I see you have an over_climate with Strong regulation activated and the target temperature is not reach.
We can see that self-regulation works (the setpoint of the TRV is above the target temp) but this is not enough because the internal temp of the TRV is reacting very quickly and turns off the valve.

If I am right in this analysis, the solution is too have more self-regulation. What we want is that is interal temp of the TRV don't turn off. This can be done by sending a higher target, which is done by self-regulation algorithm.

Because you are already in Strong regulation mode, you should configure the expert mode (cf. readme) and add configuration like that in your configuration.yaml file:

versatile_thermostat:
     auto_regulation_expert:
         kp: 0.5
         ki: 0.08
         k_ext: 0.0
         offset_max: 10
         stabilization_threshold: 0.1
         accumulated_error_threshold: 70

I suggest to augment the kp (try 0.1 step) and offset_max to 10 and accumulated_error_threshold to 70.

I believe the Vtech self-regulation algorthm should take into account the internal TRV temperature of the climate entity, and calculate an "offset" based on the current value of the internal TRV temperature, so that the regulated temperature is above the internal TRV temperature, and the TRV lets water to flow.

Many people asks for this and if I understand this is the way BetterThermostat works. I continue to believe that self-regulation should do the trick because it does exactly the same (increase the target setpoint) but dynamically.

Try this and let me know.

EDIT: please read this also: https://github.com/jmcollin78/versatile_thermostat/blob/feature_234-add_central_boiler_helper/README.md#the-radiator-heats-up-even-though-the-setpoint-temperature-is-exceeded-or-does-not-heat-up-even-though-the-room-temperature-is-well-below-the-setpoint

[ikoz]

@jmcollin78 Thank you very much for the detailed response. Yes I meant VTherm! I am testing out expert mode now to see how it responds to my TRVs. So far from testing it looks like VTech eventually gets there and can heat the room but the response is very slow (more than 30 minutes until TRV opens for more than a minute). VTech keeps increasing the regulated temperature by small amount at the start, but the internal trv temperature also increases so the TRV closes and the room temperature does not increase. I'll try with higher kp so that it responds more quickly.

Many people asks for this and if I understand this is the way BetterThermostat works. I continue to believe that self-regulation should do the trick because it does exactly the same (increase the target setpoint) but dynamically.

I understand this point, yes it should eventually work.

However I am worried about the response time; the TRV internal temp jumps too quickly in response to heat and I wonder if there's a way to account for it in the PI algorithm, e.g. to add an extra offset parameter similar to k_ext for external temperature, so that the regulated setpoint increases further to account for the trv internal temperature.

Another way to go would be to let the algorithm check if the underlying thermostat is indeed 'heating' when VTherm is supposed to be heating. If VTherm calls for heat but the underlying algorithm does not call for heat, then perhaps an extra offset can be added, to respond more quickly. I think _async_climate_changed() tries to do something similar.

[jmcollin78]

k_ext for external temperature

k_ext mean outdoor here. But I agree that the temperature raise can be slow since to have to wait for the cumulated_error to take the precedence.
It's seems a good idea to speed up the algo using the delta between external and internal temperature. I will study that for the future.

If you want to give it a try with a PR we can try that and I will help you. This is not very difficult to implement. It is more complex for testing this. And because you have TRV, you will be able to test it on a real env unlike me.

[michielbeijer]

Also interested in this solution. Had the same issues as Ikoz, and "fixed" these by setting up my VTherm as a switch and setting the TRV to 16C (switch is off) or 30C (switch is on). This way the TRV doesn't close because the local temperature maxes out at 28C or something (it's in a small closet where the heat exchanger for the underfloor heating is). Temperature in the house is very stable, but my TRV switches on/off very often (drains the batteries) and I'm not sure whether the boiler likes this behaviour (and whether it is energy efficient).

[jmcollin78]

Hello @michielbeijer, @ikoz, @maia

I have release an alpha release to test the algorithm with the improvement. The release is here: https://github.com/jmcollin78/versatile_thermostat/releases/tag/5.4.0.alpha3

What I do is:

1. calculate a device offet as device internal temp - room temp,
2. add this offset each time, VTherm sends a new temperature on the device.

So, the regulation should very quick depending of the offset and progressively will be refined at each cycle with the cumulated_error (the PI algorithm).
On the paper, it will work, but I need more feedback to be sure. I have only one heat pump in a small room to test.

Please give me regulation graphs as feedback (before and after if possible). Plotly is a wonderful for this if you want. See in the README to install and configure it.

I forgot to mention that you have to select the "use device temperature" into the configuration of the VTherm (in the self-regulation configuration section). If something goes wrong, just unselect the option and everything should go as usual.

Thank you in advance for your help !