# Add new metric - comfort score

**URL:** <https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976>\
**Category:** Emoncms\
**Created:** [24 October 2024 13:11 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976 "2024-10-24T13:11:14Z")\
**Posts on this page:** 20\
**Page:** 2

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**Author:** ![Andre\_K](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/andre_k/32/28208_2.png) [@Andre\_K](https://community.openenergymonitor.org/u/Andre_K)\
**Post date:** [30 November 2024 07:05 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/21 "2024-11-30T07:05:16Z")

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> [@critictidier](#):
>
> **20%~ lower heat output required to maintain indoor temperature** , compared to heat pumps in similar sized properties

If you are maintaining the same temperature in your house, you will always need the same heat energy for that - even the most advanced control system cannot work its way around the physics. If you need less heat than similar sized properties this means you have better insulation and/or air tightness and/or more favourable external climate conditions.

I would go so far to say that any gains in efficiency due to a control system like your thermostat should only be compared within the same house and not between different houses as the uncertainties will completely drown out the “signal”.

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**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [30 November 2024 07:08 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/22 "2024-11-30T07:08:59Z")

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Thanks @Andre_K you are right, it is only an estimated comparison. It’s the best one I could come up with ☺

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**Author:** ![Timbones](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/timbones/32/20308_2.png) [@Timbones](https://community.openenergymonitor.org/u/Timbones)\
**Post date:** [30 November 2024 10:07 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/23 "2024-11-30T10:07:01Z")

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You could compare against properties with the same ‘Heat loss at design temperature’ or same annual ‘Assessed space heat demand’, though these are both estimated rather than measured.

 ![Screenshot_20241130_095920_com_android_chrome_ChromeTabbedActivity](https://community.openenergymonitor.org/uploads/default/original/3X/5/6/56efec8882ca15d97995da1475765c3d06092d49.jpeg)

Variation in hot water usage will also skew results, so try to factor that in (or out).

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**Author:** ![Timbones](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/timbones/32/20308_2.png) [@Timbones](https://community.openenergymonitor.org/u/Timbones)\
**Post date:** [30 November 2024 10:51 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/24 "2024-11-30T10:51:25Z")

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> [@critictidier](#):
>
> 0.18720£/kWh is the equivalent Heat Pump electricity boiler cost \< 24 hours  
> Boiler Input/Output Ratios to Heat Pump≈3.794/0.799  
> Adj. Input Ratio≈3.032 [0.799\*3.794]  
> 3.032 \* 0.06174 (avg gas £/kWh) = 0.18720

I don’t understand what this calculation is supposed to show, but it doesn’t look right. A more typical presentation would be cost per kWh of heat.

For example: gas price ÷ boiler efficiency = 6.24p ÷ 0.95 = 6.57 p/kWh  
electric price ÷ heatpump efficiency = 24.5p ÷ 4.0 = 6.125 p/kWh

(using current price cap prices for UK)

This makes it easy to compare the cost of the two heating systems _in the same house_, as all other variables will be the same.

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**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [30 November 2024 13:00 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/25 "2024-11-30T13:00:48Z")

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Thanks @Timbones ☺

Let’s put it another way - \>

**Heat pumps have opportunity to be even more efficient if they had more precise control over heat output 🥰**

I did another run where heat loss value is not 0 and less or equal than 6, and here are the results:

Heat Pumps \*average  
in 130.6 kWh  
out 511.5 kWh  
COP 3.9  
Mean Room Temp 19.8°C

Boiler  
in 425.0 kWh  
out 402.5 kWh  
Efficiency 94.7%  
Mean Room Temp 20.5°C

\*[0 \< ‘Heat Loss’ \<=6, ‘Floor Area’ = 185±30]

0.15838£/kWh is equivalent Heat Pump electricity boiler cost \< 7 days  
Boiler Input/Output Ratios to Heat Pump≈3.254/0.787  
Adj. Input Ratio≈2.561 [0.787\*3.254]  
2.561 \* 0.06185 (avg gas £/kWh) = 0.15838

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**Author:** ![Timbones](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/timbones/32/20308_2.png) [@Timbones](https://community.openenergymonitor.org/u/Timbones)\
**Post date:** [30 November 2024 15:13 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/26 "2024-11-30T15:13:58Z")

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> [@critictidier](#):
>
> Heat pumps have opportunity to be even more efficient if they had more precise control over heat output 🥰

Indeed, a well installed heat pump with correct controls will control its heat output very precisely using a combination of weather + load compensation. It’s the poor system design, oversizing and incorrect controls that cause some to under perform.

> [@critictidier](#):
>
> 0.15838£/kWh is equivalent Heat Pump electricity boiler cost \< 7 days  
> Boiler Input/Output Ratios to Heat Pump≈3.254/0.787  
> Adj. Input Ratio≈2.561 [0.787\*3.254]  
> 2.561 \* 0.06185 (avg gas £/kWh) = 0.15838

I still don’t follow what this calculation is. 0.15838£/kWh seems way too expensive. Can you explain it?

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**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [30 November 2024 21:32 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/27 "2024-11-30T21:32:19Z")

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Here’s a paper a found [link below], which looks at thermostats with different precision levels.

According to the study:

1. **Precision Impact on Savings** :

- A thermostat with 0.1°C precision achieves energy savings nearly identical to **theoretical** adaptive setpoints, enabling optimal use of heating and cooling strategies.
- Thermostats with 1°C precision (common in older HVAC systems) result in significantly reduced energy savings. In some cases, energy consumption can even increase compared to static operational patterns due to the inability to finely tune the setpoints.

1. **Energy Consumption Variations** :

- In heating, the energy consumption increases by 22.44% on average when using a thermostat with 1°C precision compared to 0.1°C precision in the current climate scenario​

Quote from the paper

> In the current scenario, an average increase in annual
> 
> heating energy consumption of 1.02, 10.47 and 22.44% was obtained
> 
> with AP-2, AP-3, and AP-4, respectively, and in the annual cooling
> 
> energy consumption, the increase percentages were greater: 5.09%
> 
> with AP-2, 41.40% with AP-3, and 76.44% with AP-4.

In simpler terms, here’s what this means:

- **Heating energy use** :
  - If the thermostat is very precise (AP-2, accurate to 0.1°C), the extra energy used for heating is very small—just 1.02% more compared to an ideal thermostat.
  - If the thermostat is less precise (AP-3, accurate to 0.5°C), heating energy use increases by 10.47%.
  - With the least precise thermostat (AP-4, accurate to 1°C), heating energy use jumps by 22.44%.

[https://www.sciencedirect.com/science/article/abs/pii/S037877882100308X](https://www.sciencedirect.com/science/article/abs/pii/S037877882100308X)

[bienvenido-huertas2021.pdf](https://community.openenergymonitor.org/uploads/short-url/fM2P1Mj0TxmjVDsN365iXE7y9QU.pdf) (8.0 MB)

So again, if your heating source (whether it’s boiler or heat pump), cannot work down to 0.1 precision, then your property might be missing on about 20% energy savings 🙂

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**Author:** ![Andre\_K](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/andre_k/32/28208_2.png) [@Andre\_K](https://community.openenergymonitor.org/u/Andre_K)\
**Post date:** [30 November 2024 23:12 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/28 "2024-11-30T23:12:20Z")

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The short answer is: No 😃.

The long answer:

Let’s not look at the paper and instead start with the basic physics and a quick worst-case estimate. Let’s say we have to heat for 220 days a year and during that heating period accumulate 2500 degree days (should be somewhat representative of London) with an internal setpoint of 20°C. My crappy thermostat however delivers 21°C all the time (very precise, but not accurate). This means that every day I accumulate one extra degree day, ending up with 2720. Thanks to linearity of the underling physics, this translates to an 8.8% increase heating energy use; with heat pumps the electrical energy use increase will be slightly higher because of the reduced COP at higher flow temperatures.

One thing to note here: The added degree days scale with the number of days where I use my heating per year and have to be put in relation to the total accumulated degree days. For colder climates, like in Germany, we get closer to 3800 degree days per year and assuming the same number of days for heating the increased energy use already drops to 5.8%. The article you cite is for Spain, which is much warmer and 1°C inaccuracy will have a higher impact. But they are also probably heating for less days during the year.

In reality things will be much different. If I feel too warm after setting to 20°C and getting 21°C, I will reduce the setpoint and the problem is solved. Real thermostats will however not simply systematically over- or underestimate but rather oscillate around the setpoint with varying amplitude - let’s use 1°C again. So the temperature will overshoot, but also undershoot. The nice thing about the linearity is that we just have to care about the average temperature. When it’s 21°C, we use slightly more energy, when it’s 19°C we use slighly less. Over a year (or even shorter timeframes like a day), it takes the same energy to keep the house at exactly 20°C compared to having it oscillate by ±1°C, provided the average temperature is 20°C.

Finally, let’s quickly look at the paper. They are analyzing an adaptive setpoint technique where (for the heating part) they reduce indoor temperature when it’s colder and increase it when it’s warmer. This of course leads to savings. If the adaptive model calls for 22.268 °C but my thermostat can only be set to 23°C, then of course I will use more energy. This is a discretization error, and if their adaptive energy savings model is built based on continuous temperature adjustability then it is not surprising that quantization/discretization errors can lead to large deviations from the desired result - this is a well-known issue in a number of fields. So what they are saying is that for their adaptive setpoint model, a thermostat adjustability of only ±1°C leads to increased energy use - probably also because they seem to always round towards the next highest integer and never down. This has exactly nothing to do with what most people here are doing: Keeping their house constantly at a temperature they find comfortable and affordable.

Thanks for coming to my TED talk 😃.

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**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [1 December 2024 09:58 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/29 "2024-12-01T09:58:39Z")

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Thank you André! I respect your important points raised and I also politely disagree 🥰 In general, I encourage that we promote for our heating controls to become more open source and more configurable, not less 🥰

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**Author:** ![Andre\_K](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/andre_k/32/28208_2.png) [@Andre\_K](https://community.openenergymonitor.org/u/Andre_K)\
**Post date:** [1 December 2024 10:25 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/30 "2024-12-01T10:25:02Z")

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Which points do you disagree with? You can disagree all you want with the physics, but it’s not going to change reality.

At no point did I advocate for less or closed source controls. I just stated that the benefits of these high accuracy controls in terms of energy savings was severely overstated by you.

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**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [1 December 2024 11:47 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/31 "2024-12-01T11:47:48Z")

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With open source, we could swiftly test the algorithm on heat pumps and then celebrate our enhanced efficiency at a cozy pub with excellent German beer and Wurst 😊👍🍺🌭

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**Author:** ![Kocta](https://community.openenergymonitor.org/letter_avatar_proxy/v4/letter/k/22d042/32.png) [@Kocta](https://community.openenergymonitor.org/u/Kocta)\
**Post date:** [21 February 2025 07:57 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/32 "2025-02-21T07:57:39Z")

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Hi everyone,

is it possible to add Frequency to the APP MY HEATPUMP dashboard?  
I can fined it anywhere, maybe someone can point me to the right direction.

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**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [16 April 2025 22:43 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/33 "2025-04-16T22:43:11Z")

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@Andre_K @Timbones @TrystanLea

How about using standard deviation to calculate the comfort score for any selected period of time? 2σ as shown in the image gives a way to calculate a value without having to know what the target room temperature is. A value of 2σ = 0°C would be 100%, and let’s say 2σ = 10°C would be 0%. Then, anything between would give us an actual score?

 ![collage](https://community.openenergymonitor.org/uploads/default/original/3X/3/f/3f7d767af9f2262c99c481f4b07a8bbb22b62cb4.png)

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<div class="post-metadata">

**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [18 April 2025 19:29 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/34 "2025-04-18T19:29:57Z")

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Here’s the full **Comfort Score** ranking. The data below is for the period “ **2025-Jan-01 00:00** ” --end “ **2025-Feb-19 23:59** ” which was the coldest period for many. Some heat pumps are missing as they didn’t have \> 85% roomT data available for the selected period.

@TrystanLea @Zarch @Timbones @Andre_K @UrbanPlumber

| Ranking | Heat Pump ID / Boiler | Comfort Score | Mean Room Temperature | Mean Range (2 σ) | % within ±0.5 °C of mean | Time within ±0.5 °C (days) | Mean+1 σ | Mean-1 σ | Mean+0.5 °C | Mean-0.5 °C |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | boiler | 97.68997464 | 20.50947643 | 0.231002536 | 99.12265702 | 49.31128472 | 20.6249777 | 20.39397516 | 21.00947643 | 20.00947643 |
| 2 | 436 | 96.30195076 | 19.96952439 | 0.369804924 | 98.35109135 | 48.84565972 | 20.15442686 | 19.78462193 | 20.46952439 | 19.46952439 |
| 3 | 261 | 94.45110992 | 19.75638225 | 0.554889008 | 93.34846773 | 45.47447917 | 20.03382676 | 19.47893775 | 20.25638225 | 19.25638225 |
| 4 | 280 | 93.86514626 | 21.97065127 | 0.613485374 | 88.77485007 | 44.07378472 | 22.27739396 | 21.66390859 | 22.47065127 | 21.47065127 |
| 5 | 249 | 93.59009155 | 19.27768568 | 0.640990845 | 89.14116273 | 43.0578125 | 19.59818111 | 18.95719026 | 19.77768568 | 18.77768568 |
| 6 | 37 | 93.38766549 | 20.84752512 | 0.661233451 | 93.05038646 | 45.79322917 | 21.17814184 | 20.51690839 | 21.34752512 | 20.34752512 |
| 7 | 215 | 93.36843562 | 22.37275636 | 0.663156438 | 86.93346141 | 43.36666667 | 22.70433458 | 22.04117814 | 22.87275636 | 21.87275636 |
| 8 | 196 | 92.38761611 | 20.18362561 | 0.761238389 | 86.39338164 | 42.33350694 | 20.5642448 | 19.80300641 | 20.68362561 | 19.68362561 |
| 9 | 8 | 92.03207356 | 18.25168983 | 0.796792644 | 82.54757117 | 41.26475694 | 18.65008615 | 17.8532935 | 18.75168983 | 17.75168983 |
| 10 | 301 | 91.84566062 | 21.77474382 | 0.815433938 | 76.12651341 | 37.50763889 | 22.18246079 | 21.36702685 | 22.27474382 | 21.27474382 |
| 11 | 527 | 91.74950716 | 20.7161001 | 0.825049284 | 81.45516474 | 39.52569444 | 21.12862475 | 20.30357546 | 21.2161001 | 20.2161001 |
| 12 | 288 | 91.6762528 | 20.71666183 | 0.83237472 | 79.86545526 | 34.68836806 | 21.13284919 | 20.30047447 | 21.21666183 | 20.21666183 |
| 13 | 407 | 91.66629699 | 20.83943022 | 0.833370301 | 77.30359558 | 38.10208333 | 21.25611537 | 20.42274507 | 21.33943022 | 20.33943022 |
| 14 | 115 | 91.59001173 | 19.65804052 | 0.840998827 | 75.57634843 | 37.45503472 | 20.07853993 | 19.23754111 | 20.15804052 | 19.15804052 |
| 15 | 46 | 91.36874878 | 20.87490799 | 0.863125122 | 76.35732817 | 38.1703125 | 21.30647055 | 20.44334543 | 21.37490799 | 20.37490799 |
| 16 | 11 | 91.28988586 | 21.18239897 | 0.871011414 | 66.07134373 | 31.38767361 | 21.61790468 | 20.74689327 | 21.68239897 | 20.68239897 |
| 17 | 344 | 91.19699645 | 19.63604805 | 0.880300355 | 72.33238938 | 35.87447917 | 20.07619823 | 19.19589787 | 20.13604805 | 19.13604805 |
| 18 | 59 | 90.92243201 | 20.00578834 | 0.907756799 | 74.37767115 | 34.95711806 | 20.45966674 | 19.55190994 | 20.50578834 | 19.50578834 |
| 19 | 71 | 90.90916797 | 20.50117188 | 0.909083203 | 72.32027339 | 35.71215278 | 20.95571348 | 20.04663028 | 21.00117188 | 20.00117188 |
| 20 | 350 | 90.72546097 | 22.5965976 | 0.927453903 | 78.80363828 | 37.934375 | 23.06032455 | 22.13287065 | 23.0965976 | 22.0965976 |
| 21 | 321 | 90.5512454 | 19.45763835 | 0.94487546 | 71.11569481 | 35.25572917 | 19.93007608 | 18.98520062 | 19.95763835 | 18.95763835 |
| 22 | 445 | 90.42126576 | 18.90927243 | 0.957873424 | 70.17713571 | 34.38350694 | 19.38820914 | 18.43033572 | 19.40927243 | 18.40927243 |
| 23 | 364 | 90.40205295 | 19.39863835 | 0.959794705 | 70.95425943 | 34.63072917 | 19.87853571 | 18.918741 | 19.89863835 | 18.89863835 |
| 24 | 208 | 90.27602138 | 20.87390809 | 0.972397862 | 71.36673695 | 34.49305556 | 21.36010703 | 20.38770916 | 21.37390809 | 20.37390809 |
| 25 | 329 | 90.18058267 | 19.13541539 | 0.981941733 | 75.93362437 | 37.95850694 | 19.62638626 | 18.64444452 | 19.63541539 | 18.63541539 |
| 26 | 607 | 90.17457217 | 17.39899826 | 0.982542783 | 68.33579398 | 31.74114583 | 17.89026966 | 16.90772687 | 17.89899826 | 16.89899826 |
| 27 | 326 | 90.04905695 | 20.3799 | 0.995094305 | 72.53908708 | 36.22256944 | 20.87744715 | 19.88235285 | 20.8799 | 19.8799 |
| 28 | 210 | 89.97668796 | 22.92952178 | 1.002331204 | 67.73137521 | 30.89079861 | 23.43068738 | 22.42835618 | 23.42952178 | 22.42952178 |
| 29 | 160 | 89.71704664 | 18.22053369 | 1.028295336 | 69.13070316 | 34.02586806 | 18.73468136 | 17.70638602 | 18.72053369 | 17.72053369 |
| 30 | 508 | 89.65769572 | 20.8110113 | 1.034230428 | 68.03286997 | 33.79166667 | 21.32812652 | 20.29389609 | 21.3110113 | 20.3110113 |
| 31 | 428 | 89.50598247 | 20.20802072 | 1.049401753 | 66.72890517 | 33.0703125 | 20.7327216 | 19.68331985 | 20.70802072 | 19.70802072 |
| 32 | 159 | 89.2502582 | 20.80527529 | 1.07497418 | 76.39989763 | 37.83559028 | 21.34276238 | 20.2677882 | 21.30527529 | 20.30527529 |
| 33 | 499 | 89.13017193 | 19.23169562 | 1.086982807 | 72.89179021 | 34.04097222 | 19.77518702 | 18.68820421 | 19.73169562 | 18.73169562 |
| 34 | 458 | 89.12203837 | 18.09488589 | 1.087796163 | 70.97179574 | 33.8265625 | 18.63878397 | 17.55098781 | 18.59488589 | 17.59488589 |
| 35 | 265 | 89.10118423 | 19.80307093 | 1.089881577 | 61.00747906 | 30.17847222 | 20.34801172 | 19.25813014 | 20.30307093 | 19.30307093 |
| 36 | 521 | 89.04606701 | 20.0850218 | 1.095393299 | 61.59665546 | 30.49045139 | 20.63271845 | 19.53732515 | 20.5850218 | 19.5850218 |
| 37 | 140 | 89.01094885 | 20.43985318 | 1.098905115 | 62.87310756 | 31.19739583 | 20.98930574 | 19.89040062 | 20.93985318 | 19.93985318 |
| 38 | 223 | 88.85475354 | 19.16042217 | 1.114524646 | 58.4358901 | 28.35763889 | 19.71768449 | 18.60315984 | 19.66042217 | 18.66042217 |
| 39 | 138 | 88.8227115 | 21.52400147 | 1.11772885 | 64.61246683 | 31.99809028 | 22.0828659 | 20.96513705 | 22.02400147 | 21.02400147 |
| 40 | 262 | 88.63775292 | 19.60159754 | 1.136224708 | 63.25320831 | 29.325 | 20.16970989 | 19.03348519 | 20.10159754 | 19.10159754 |
| 41 | 416 | 88.63257683 | 20.33378921 | 1.136742317 | 61.19204393 | 29.54184028 | 20.90216037 | 19.76541805 | 20.83378921 | 19.83378921 |
| 42 | 300 | 88.60614291 | 20.10550424 | 1.139385709 | 71.06230144 | 34.21267361 | 20.67519709 | 19.53581138 | 20.60550424 | 19.60550424 |
| 43 | 345 | 88.45259777 | 22.12505588 | 1.154740223 | 62.00493396 | 29.80295139 | 22.70242599 | 21.54768577 | 22.62505588 | 21.62505588 |
| 44 | 548 | 88.38782255 | 19.09363888 | 1.161217745 | 57.65668562 | 25.41979167 | 19.67424776 | 18.51303001 | 19.59363888 | 18.59363888 |
| 45 | 556 | 88.13441492 | 18.22141861 | 1.186558508 | 63.249024 | 28.38003472 | 18.81469787 | 17.62813936 | 18.72141861 | 17.72141861 |
| 46 | 448 | 88.13252305 | 20.98762117 | 1.186747695 | 55.65184057 | 27.47239583 | 21.58099501 | 20.39424732 | 21.48762117 | 20.48762117 |
| 47 | 552 | 87.76752323 | 18.72257107 | 1.223247677 | 68.71787556 | 29.26892361 | 19.33419491 | 18.11094723 | 19.22257107 | 18.22257107 |
| 48 | 380 | 87.711439 | 19.27795766 | 1.2288561 | 57.20524017 | 27.65555556 | 19.89238571 | 18.66352961 | 19.77795766 | 18.77795766 |
| 49 | 282 | 87.66132792 | 21.43171714 | 1.233867208 | 46.23667492 | 20.87361111 | 22.04865075 | 20.81478354 | 21.93171714 | 20.93171714 |
| 50 | 545 | 87.57863608 | 19.71888902 | 1.242136392 | 60.81485186 | 30.1875 | 20.33995722 | 19.09782083 | 20.21888902 | 19.21888902 |
| 51 | 151 | 87.56896409 | 19.87651402 | 1.243103591 | 65.21404777 | 32.38975694 | 20.49806582 | 19.25496223 | 20.37651402 | 19.37651402 |
| 52 | 239 | 87.42388725 | 23.34813671 | 1.257611275 | 63.22078929 | 29.45572917 | 23.97694235 | 22.71933107 | 23.84813671 | 22.84813671 |
| 53 | 519 | 87.32649218 | 21.80071526 | 1.267350782 | 83.2633188 | 39.81302083 | 22.43439065 | 21.16703986 | 22.30071526 | 21.30071526 |
| 54 | 533 | 87.32612154 | 19.18332522 | 1.267387846 | 58.14626524 | 28.81197917 | 19.81701915 | 18.5496313 | 19.68332522 | 18.68332522 |
| 55 | 313 | 87.31463094 | 19.66511341 | 1.268536906 | 55.733962 | 27.33489583 | 20.29938186 | 19.03084495 | 20.16511341 | 19.16511341 |
| 56 | 75 | 87.21020902 | 20.70904008 | 1.278979098 | 54.29530578 | 26.84375 | 21.34852963 | 20.06955053 | 21.20904008 | 20.20904008 |
| 57 | 381 | 87.14811895 | 17.79901147 | 1.285188105 | 55.12282202 | 25.73211806 | 18.44160552 | 17.15641742 | 18.29901147 | 17.29901147 |
| 58 | 232 | 87.1343409 | 20.64656545 | 1.28656591 | 55.19452175 | 27.44097222 | 21.2898484 | 20.00328249 | 21.14656545 | 20.14656545 |
| 59 | 479 | 87.05895064 | 19.75075067 | 1.294104936 | 62.1533628 | 30.29253472 | 20.39780314 | 19.1036982 | 20.25075067 | 19.25075067 |
| 60 | 379 | 87.03071738 | 18.73016021 | 1.296928262 | 52.76419392 | 26.28142361 | 19.37862434 | 18.08169608 | 19.23016021 | 18.23016021 |
| 61 | 139 | 86.80293784 | 19.69089348 | 1.319706216 | 55.93846219 | 27.53541667 | 20.35074659 | 19.03104037 | 20.19089348 | 19.19089348 |
| 62 | 307 | 86.75594627 | 22.5209502 | 1.324405373 | 54.68405889 | 26.85642361 | 23.18315289 | 21.85874752 | 23.0209502 | 22.0209502 |
| 63 | 363 | 86.60867554 | 21.15645059 | 1.339132446 | 61.40538912 | 30.43628472 | 21.82601681 | 20.48688437 | 21.65645059 | 20.65645059 |
| 64 | 424 | 86.41680409 | 19.75376832 | 1.358319591 | 52.65499421 | 24.53402778 | 20.43292811 | 19.07460852 | 20.25376832 | 19.25376832 |
| 65 | 470 | 86.41638239 | 20.56990973 | 1.358361761 | 64.76365393 | 31.8953125 | 21.24909061 | 19.89072884 | 21.06990973 | 20.06990973 |
| 66 | 431 | 86.41603571 | 19.50510194 | 1.358396429 | 55.24669539 | 27 | 20.18430015 | 18.82590372 | 20.00510194 | 19.00510194 |
| 67 | 372 | 86.3714965 | 20.44862171 | 1.36285035 | 51.40842194 | 24.0328125 | 21.13004689 | 19.76719654 | 20.94862171 | 19.94862171 |
| 68 | 72 | 86.33007434 | 19.80908387 | 1.366992566 | 50.18957819 | 23.55572917 | 20.49258015 | 19.12558759 | 20.30908387 | 19.30908387 |
| 69 | 312 | 86.27628281 | 23.51444134 | 1.372371719 | 54.20526018 | 27.09670139 | 24.2006272 | 22.82825548 | 24.01444134 | 23.01444134 |
| 70 | 370 | 85.89880751 | 20.89405295 | 1.410119249 | 52.48953631 | 24.92934028 | 21.59911258 | 20.18899333 | 21.39405295 | 20.39405295 |
| 71 | 237 | 85.89513266 | 20.17864426 | 1.410486734 | 52.33459919 | 25.52847222 | 20.88388763 | 19.4734009 | 20.67864426 | 19.67864426 |
| 72 | 346 | 85.27520575 | 20.25887312 | 1.472479425 | 57.04624575 | 28.24947917 | 20.99511283 | 19.52263341 | 20.75887312 | 19.75887312 |
| 73 | 390 | 85.10904595 | 20.65681127 | 1.489095405 | 46.25908478 | 22.92916667 | 21.40135897 | 19.91226357 | 21.15681127 | 20.15681127 |
| 74 | 457 | 85.00167198 | 20.84778342 | 1.499832802 | 51.19441421 | 24.74583333 | 21.59769982 | 20.09786702 | 21.34778342 | 20.34778342 |
| 75 | 68 | 84.96089643 | 19.23681501 | 1.503910357 | 48.58050847 | 23.88541667 | 19.98877019 | 18.48485983 | 19.73681501 | 18.73681501 |
| 76 | 64 | 84.87822376 | 19.92466816 | 1.512177624 | 59.38212877 | 29.14930556 | 20.68075697 | 19.16857934 | 20.42466816 | 19.42466816 |
| 77 | 462 | 84.83067431 | 21.59818262 | 1.516932569 | 53.92791598 | 26.68055556 | 22.3566489 | 20.83971633 | 22.09818262 | 21.09818262 |
| 78 | 375 | 84.6574146 | 21.20261588 | 1.53425854 | 36.42612884 | 18.10486111 | 21.96974515 | 20.43548662 | 21.70261588 | 20.70261588 |
| 79 | 56 | 84.6177025 | 20.30382273 | 1.53822975 | 47.15118965 | 23.56388889 | 21.07293761 | 19.53470786 | 20.80382273 | 19.80382273 |
| 80 | 314 | 84.54681639 | 20.76538142 | 1.545318361 | 52.31894719 | 24.81961806 | 21.5380406 | 19.99272224 | 21.26538142 | 20.26538142 |
| 81 | 213 | 84.49405973 | 19.77714139 | 1.550594027 | 47.89347818 | 23.32986111 | 20.5524384 | 19.00184438 | 20.27714139 | 19.27714139 |
| 82 | 95 | 84.40654219 | 19.7002814 | 1.559345781 | 54.63681596 | 26.9 | 20.47995429 | 18.9206085 | 20.2002814 | 19.2002814 |
| 83 | 231 | 84.3155846 | 22.12824725 | 1.56844154 | 44.92457894 | 21.825 | 22.91246802 | 21.34402648 | 22.62824725 | 21.62824725 |
| 84 | 439 | 84.31413943 | 18.91859099 | 1.568586057 | 49.46327334 | 24.31128472 | 19.70288402 | 18.13429796 | 19.41859099 | 18.41859099 |
| 85 | 309 | 84.21094712 | 22.43529613 | 1.578905288 | 51.21809271 | 25.05711806 | 23.22474878 | 21.64584349 | 22.93529613 | 21.93529613 |
| 86 | 517 | 83.90382566 | 22.33400108 | 1.609617434 | 56.92157171 | 28.28142361 | 23.1388098 | 21.52919236 | 22.83400108 | 21.83400108 |
| 87 | 43 | 83.89701057 | 20.62681833 | 1.610298943 | 49.76961171 | 24.07777778 | 21.4319678 | 19.82166886 | 21.12681833 | 20.12681833 |
| 88 | 518 | 83.8432348 | 20.50080954 | 1.61567652 | 45.3316544 | 22.43767361 | 21.3086478 | 19.69297128 | 21.00080954 | 20.00080954 |
| 89 | 334 | 83.68408742 | 22.93756057 | 1.631591258 | 51.65430701 | 24.07673611 | 23.7533562 | 22.12176494 | 23.43756057 | 22.43756057 |
| 90 | 507 | 83.55361882 | 20.77297868 | 1.644638118 | 52.48789126 | 25.83142361 | 21.59529774 | 19.95065962 | 21.27297868 | 20.27297868 |
| 91 | 477 | 83.55135488 | 21.25048115 | 1.644864512 | 53.29463473 | 26.12482639 | 22.07291341 | 20.42804889 | 21.75048115 | 20.75048115 |
| 92 | 332 | 83.16890129 | 19.26111523 | 1.683109871 | 61.39513601 | 29.81597222 | 20.10267016 | 18.41956029 | 19.76111523 | 18.76111523 |
| 93 | 571 | 83.07407139 | 21.09394122 | 1.692592861 | 52.60595045 | 23.01336806 | 21.94023765 | 20.24764478 | 21.59394122 | 20.59394122 |
| 94 | 511 | 83.02579197 | 20.41568433 | 1.697420803 | 48.92654355 | 23.71111111 | 21.26439473 | 19.56697393 | 20.91568433 | 19.91568433 |
| 95 | 512 | 82.96114219 | 17.96038928 | 1.703885781 | 50.35400952 | 24.16336806 | 18.81233217 | 17.10844639 | 18.46038928 | 17.46038928 |
| 96 | 506 | 82.72483493 | 18.78584416 | 1.727516507 | 56.41087605 | 27.55798611 | 19.64960241 | 17.92208591 | 19.28584416 | 18.28584416 |
| 97 | 441 | 82.71004367 | 21.0597091 | 1.728995633 | 52.85127202 | 25.43072917 | 21.92420692 | 20.19521129 | 21.5597091 | 20.5597091 |
| 98 | 371 | 82.70952414 | 18.87605481 | 1.729047586 | 36.85442292 | 18.18055556 | 19.7405786 | 18.01153101 | 19.37605481 | 18.37605481 |
| 99 | 357 | 82.66301209 | 18.85499196 | 1.733698791 | 49.40649488 | 24.0703125 | 19.72184136 | 17.98814257 | 19.35499196 | 18.35499196 |
| 100 | 258 | 82.65292875 | 19.44297517 | 1.734707125 | 52.25601069 | 25.79097222 | 20.31032873 | 18.57562161 | 19.94297517 | 18.94297517 |
| 101 | 665 | 82.43020831 | 22.09542851 | 1.756979169 | 39.83877133 | 19.90486111 | 22.9739181 | 21.21693893 | 22.59542851 | 21.59542851 |
| 102 | 7 | 82.23594199 | 20.69732096 | 1.776405801 | 37.63274553 | 17.9953125 | 21.58552386 | 19.80911806 | 21.19732096 | 20.19732096 |
| 103 | 382 | 82.14222113 | 18.46194778 | 1.785777887 | 44.21584187 | 21.28194444 | 19.35483672 | 17.56905883 | 18.96194778 | 17.96194778 |
| 104 | 467 | 82.12457747 | 19.42650117 | 1.787542253 | 48.82610734 | 24.04253472 | 20.32027229 | 18.53273004 | 19.92650117 | 18.92650117 |
| 105 | 331 | 81.93616793 | 20.42071756 | 1.806383207 | 38.51640863 | 19.08628472 | 21.32390917 | 19.51752596 | 20.92071756 | 19.92071756 |
| 106 | 417 | 81.9288585 | 20.07511161 | 1.80711415 | 46.71958989 | 23.13211806 | 20.97866868 | 19.17155453 | 20.57511161 | 19.57511161 |
| 107 | 391 | 81.92551103 | 19.46746521 | 1.807448897 | 53.5579385 | 25.67517361 | 20.37118966 | 18.56374077 | 19.96746521 | 18.96746521 |
| 108 | 284 | 81.78804229 | 19.56687614 | 1.821195771 | 49.39109897 | 24.39791667 | 20.47747403 | 18.65627826 | 20.06687614 | 19.06687614 |
| 109 | 542 | 81.72511437 | 19.51308894 | 1.827488563 | 48.70753181 | 24.04097222 | 20.42683323 | 18.59934466 | 20.01308894 | 19.01308894 |
| 110 | 429 | 81.51991367 | 21.90189819 | 1.848008633 | 41.21129645 | 20.39930556 | 22.82590251 | 20.97789388 | 22.40189819 | 21.40189819 |
| 111 | 204 | 81.11149832 | 20.26279966 | 1.888850168 | 52.13336409 | 25.50416667 | 21.20722474 | 19.31837458 | 20.76279966 | 19.76279966 |
| 112 | 444 | 81.06369177 | 20.17590244 | 1.893630823 | 35.22054411 | 16.91527778 | 21.12271785 | 19.22908702 | 20.67590244 | 19.67590244 |
| 113 | 351 | 80.60601427 | 19.00719522 | 1.939398573 | 41.06706528 | 19.84166667 | 19.97689451 | 18.03749593 | 19.50719522 | 18.50719522 |
| 114 | 241 | 80.13318942 | 19.11573699 | 1.986681058 | 33.81145364 | 15.46944444 | 20.10907752 | 18.12239646 | 19.61573699 | 18.61573699 |
| 115 | 61 | 80.04112544 | 21.02585212 | 1.995887456 | 38.90863255 | 19.29253472 | 22.02379585 | 20.0279084 | 21.52585212 | 20.52585212 |
| 116 | 510 | 79.81282697 | 19.98470261 | 2.018717303 | 33.50082552 | 16.23958333 | 20.99406126 | 18.97534396 | 20.48470261 | 19.48470261 |
| 117 | 405 | 79.80348392 | 21.08234798 | 2.019651608 | 36.79200045 | 18.11597222 | 22.09217378 | 20.07252218 | 21.58234798 | 20.58234798 |
| 118 | 423 | 79.15175529 | 19.66527741 | 2.084824471 | 34.76139517 | 16.63628472 | 20.70768964 | 18.62286517 | 20.16527741 | 19.16527741 |
| 119 | 525 | 78.96712587 | 8.666945472 | 2.103287413 | 49.51914471 | 21.13263889 | 9.718589179 | 7.615301766 | 9.166945472 | 8.166945472 |
| 120 | 433 | 78.26329946 | 18.80480566 | 2.173670054 | 42.18785512 | 20.94722222 | 19.89164069 | 17.71797063 | 19.30480566 | 18.30480566 |
| 121 | 154 | 77.82729981 | 21.66934196 | 2.217270019 | 40.68816788 | 18.96527778 | 22.77797697 | 20.56070695 | 22.16934196 | 21.16934196 |
| 122 | 409 | 76.99957206 | 17.76283912 | 2.300042794 | 34.73317735 | 16.1078125 | 18.91286052 | 16.61281773 | 18.26283912 | 17.26283912 |
| 123 | 264 | 76.9135872 | 17.36617097 | 2.30864128 | 39.22978251 | 19.06111111 | 18.52049161 | 16.21185033 | 17.86617097 | 16.86617097 |
| 124 | 227 | 76.8611202 | 19.55559319 | 2.31388798 | 49.70241593 | 24.2265625 | 20.71253718 | 18.3986492 | 20.05559319 | 19.05559319 |
| 125 | 367 | 76.6152778 | 21.73550242 | 2.33847222 | 26.76346601 | 12.37777778 | 22.90473853 | 20.56626631 | 22.23550242 | 21.23550242 |
| 126 | 373 | 76.2023446 | 18.94306283 | 2.37976554 | 29.51867229 | 14.35555556 | 20.1329456 | 17.75318006 | 19.44306283 | 18.44306283 |
| 127 | 613 | 76.14669958 | 17.48302776 | 2.385330042 | 51.00360448 | 22.72361111 | 18.67569278 | 16.29036274 | 17.98302776 | 16.98302776 |
| 128 | 553 | 75.86609542 | 19.46831573 | 2.413390458 | 49.38266364 | 22.21336806 | 20.67501096 | 18.2616205 | 19.96831573 | 18.96831573 |
| 129 | 122 | 75.8382196 | 20.96396491 | 2.41617804 | 38.09273611 | 18.62847222 | 22.17205393 | 19.75587589 | 21.46396491 | 20.46396491 |
| 130 | 305 | 74.90898131 | 20.14842413 | 2.509101869 | 7.114106656 | 3.525694444 | 21.40297506 | 18.89387319 | 20.64842413 | 19.64842413 |
| 131 | 266 | 74.78144485 | 19.49982562 | 2.521855515 | 29.00292749 | 14.29305556 | 20.76075338 | 18.23889787 | 19.99982562 | 18.99982562 |
| 132 | 531 | 73.97782979 | 19.71773203 | 2.602217021 | 42.75960061 | 21.21180556 | 21.01884054 | 18.41662352 | 20.21773203 | 19.21773203 |
| 133 | 174 | 72.59653975 | 18.61302042 | 2.740346025 | 36.79020485 | 17.82517361 | 19.98319344 | 17.24284741 | 19.11302042 | 18.11302042 |
| 134 | 173 | 68.4747227 | 16.90080002 | 3.15252773 | 35.3722429 | 16.91388889 | 18.47706389 | 15.32453616 | 17.40080002 | 16.40080002 |
| 135 | 97 | 67.07519172 | 18.45976344 | 3.292480828 | 16.66758985 | 7.836111111 | 20.10600385 | 16.81352302 | 18.95976344 | 17.95976344 |
| 136 | 451 | 67.01057486 | 18.66571681 | 3.298942514 | 13.9944712 | 6.846527778 | 20.31518806 | 17.01624555 | 19.16571681 | 18.16571681 |
| 137 | 555 | 65.65915944 | 21.61985706 | 3.434084056 | 18.26578424 | 8.696701389 | 23.33689909 | 19.90281503 | 22.11985706 | 21.11985706 |
| 138 | 162 | 65.46105941 | 19.76708976 | 3.453894059 | 72.34759096 | 36.13975694 | 21.49403679 | 18.04014273 | 20.26708976 | 19.26708976 |
| 139 | 211 | 64.89503207 | 19.33912296 | 3.510496793 | 27.12528662 | 13.20572917 | 21.09437135 | 17.58387456 | 19.83912296 | 18.83912296 |
| 140 | 295 | 64.45281225 | 19.6776221 | 3.554718775 | 31.72291044 | 15.47152778 | 21.45498148 | 17.90026271 | 20.1776221 | 19.1776221 |
| 141 | 290 | 63.40668865 | 16.95259957 | 3.659331135 | 15.96841038 | 7.793055556 | 18.78226514 | 15.122934 | 17.45259957 | 16.45259957 |
| 142 | 442 | 61.45088688 | 19.69206067 | 3.854911312 | 28.66491151 | 13.08055556 | 21.61951633 | 17.76460502 | 20.19206067 | 19.19206067 |
| 143 | 386 | 54.81660646 | 15.74014676 | 4.518339354 | 28.48098816 | 14.05086806 | 17.99931643 | 13.48097708 | 16.24014676 | 15.24014676 |
| 144 | 341 | 43.1223546 | 19.05242033 | 5.68776454 | 16.0811554 | 7.970138889 | 21.8963026 | 16.20853806 | 19.55242033 | 18.55242033 |
| 145 | 248 | 42.15707704 | 19.88245385 | 5.784292296 | 19.07875165 | 9.463888889 | 22.77459999 | 16.9903077 | 20.38245385 | 19.38245385 |
| 146 | 377 | 24.31173532 | 18.83233751 | 7.568826468 | 5.846881863 | 2.870138889 | 22.61675074 | 15.04792428 | 19.33233751 | 18.33233751 |

 ![sd_01-25](https://community.openenergymonitor.org/uploads/default/original/3X/9/d/9db4e56162a10072b04ee3000e018a6db676d118.jpeg)  
 ![sd_26-50](https://community.openenergymonitor.org/uploads/default/original/3X/2/a/2a1175c3aeb2d82623cfeb1c2a23fc95b8605e6d.jpeg)  
 ![sd_51-75](https://community.openenergymonitor.org/uploads/default/original/3X/6/a/6a4f441cfc2e721820ffa980cb822ad136034e49.jpeg)  
 ![sd_76-100](https://community.openenergymonitor.org/uploads/default/original/3X/f/c/fc67d185bae48322d86288692d1a709199c39c63.jpeg)  
 ![sd_101-125](https://community.openenergymonitor.org/uploads/default/original/3X/1/a/1a62154de3b001f0fbb7e29e2dedcc151bf76aab.jpeg)  
 ![sd_126-147](https://community.openenergymonitor.org/uploads/default/original/3X/6/2/62676cb1e4e144fa5a07a490ab61249226591b9f.jpeg)

---

<div class="post-metadata">

**Author:** ![Andre\_K](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/andre_k/32/28208_2.png) [@Andre\_K](https://community.openenergymonitor.org/u/Andre_K)\
**Post date:** [19 April 2025 22:07 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/35 "2025-04-19T22:07:28Z")

</div>

That’s an impressive amount of work, very nice!

I must say though that I’m not convinced this is the right approach. Without knowing the target this is just the standard deviation. There are lots of people using setback overnight or might warm the house up for specific times. That’s for their comfort but gets “punished” in the model. Different sensor locations, outliers, solar gain, intermittent ventilation boosts (German Stoßlüften 😅) all enter here. An RMS deviation from a target value would be a start as I mentioned previously; after careful outlier filtering (look at the 2nd place) and gating for periods where the occupants care about the temperature. With thermal inertia being as it is, the heat pump has zero control over the cooldown period and the ramp-up can only be accelerated by increasing power and reducing COP. It would be very very tough to get anything truly comparable.

---

<div class="post-metadata">

**Author:** ![critictidier](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/critictidier/32/29731_2.png) [@critictidier](https://community.openenergymonitor.org/u/critictidier)\
**Post date:** [19 April 2025 23:14 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/36 "2025-04-19T23:14:29Z")

</div>

Thanks! You are right, there are many factors. It took me weeks to find a sensor location that minimises stray heat from the TV, kettle, or people passing by. However, I’d like to install MVHR in the future and even that spot would get affected then. Stoßlüften is ingenious 🙂

The beauty of this approach is its simplicity: no extra user configuration is required

Maybe instead of calling it **Comfort Score** which implies that all these factors are weighed and accounted for (maybe in the future), we could give this metric a more general name, e.g.

- **Thermal Steadiness Index**
- **Room Temperature Stability Score**

That way, users can compare their system with another and answer the kind of questions you raised as complexity factors! e.g. “By how much do room‑temperature swings increase under a variable‑rate electricity tariff—where the setpoint is raised during certain hours to maximise savings—compared with a flat‑tariff system?”

---

<div class="post-metadata">

**Author:** ![SianiAnni](https://community.openenergymonitor.org/letter_avatar_proxy/v4/letter/s/3ec8ea/32.png) [@SianiAnni](https://community.openenergymonitor.org/u/SianiAnni)\
**Post date:** [20 April 2025 09:03 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/37 "2025-04-20T09:03:25Z")

</div>

Interesting thread!

I’ve been monitoring whole house room-by-room temperatures for over a year now using 11 sensors logging to Home Assistant.

The heat pump was installed last June, with the Vaillant SensoComfort controls in a central location internal wall downstairs, and an emonTH on an internal wall in the N facing bedroom above. The weather compensation sensor is on a N facing wall. I’ve been running my heat pump purely on weather compensation so far, so the SensoComfort thermostat is not being used to control the heat pump.

It’s been really interesting watching temperature variation day by day and room by room. Solar gain is really obvious from the graphs, far more than any wind effect.

I much prefer the term **Room Temperature Stability Score** to **Comfort Score** because using just one temperature sensor only indicates the temperature stability of, as you say, one carefully chosen room, which may or may not be a room you spend much time in.

Some rooms in my house suffer from a big temperature range mainly due to fabric/airtightness and solar gain, whereas the SensoComfort and emonTH were carefully located to avoid solar gain, and both are in rooms the original house with similar heat losses. A full set of room sensors in a certified Passivhaus would I’m sure tell a different story!

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**Author:** ![dMb](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/dmb/32/22999_2.png) [@dMb](https://community.openenergymonitor.org/u/dMb)\
**Post date:** [20 April 2025 13:08 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/38 "2025-04-20T13:08:09Z")

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> [@SianiAnni](#):
>
> A full set of room sensors in a certified Passivhaus would I’m sure tell a different story!

Well… Still a big influence from solar gain in my Passivhaus. There’s fixed shading to keep out the _summer_ sun but the _winter_ sun (intentionally) gets in under the shading and heats the south-facing rooms, some of which have a lot of (triple) glazing. Obviously the free heating is A Good Thing but it does lead to temperature variations; probably more than you’d expect.

 ![image](https://community.openenergymonitor.org/uploads/default/original/3X/2/3/230c42078def8d581d32b861eb38cbd07b3217d4.jpeg)

The MVHR system tends to even out the temperatures but there remains a distinct north-south split:

- B1 (Bedroom 1; Green line) is on the south-west corner, has a lot of glazing and is the warmest of the bedrooms; also has the highest occupancy
- B3 (Bedroom 3; Cyan line) is on the north-east corner and is the coolest of the bedrooms
- B4 (Bedroom 4; Orange line) is on the north-west corner, directly above LR (Living Room; Blue line)
- HO (Home Office; Red line) is in the ‘attic’, facing west, with less thermal mass than the rest of the house (SIP construction rather than brick-and-block) and has the greatest temperature swings

If the heat pump was to run purely on WC control, the house would overheat in cold-but-sunny conditions, so a centrally-located room temperature sensor acts to dial-back the WC algorithm when that sensor exceeds the target temperature.

I presume the last few days on this graph weren’t very sunny, so they’re showing decent temperature regulation from the NIBE heat pump, compared with the much greater swings on the sunny days.

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**Author:** ![djh](https://community.openenergymonitor.org/letter_avatar_proxy/v4/letter/d/e36b37/32.png) [@djh](https://community.openenergymonitor.org/u/djh)\
**Post date:** [20 April 2025 16:50 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/39 "2025-04-20T16:50:28Z")

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> [@dMb](#):
>
> Still a big influence from solar gain in my Passivhaus.

I’d expect the solar gain to be greater in a passivhaus if anything. It certainly is in my house. At present when there’s no heating, the average temperature starts at around 22.5°C between 08:00 and 09:00 and climbs to around 23.5°C by about 16:00 and then falls back over the rest of the time.

During the heating season, the temperature varies about 1.5 K, because I just run heating overnight on an E7 tariff. So it peaks about 08:00 and is at its lowest about midnight.

We’re quite happy with the reversed temperature profile and comparatively large temperature changes. It’s definitely the most comforatble house we’ve lived in.

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**Author:** ![Andre\_K](https://community.openenergymonitor.org/user_avatar/community.openenergymonitor.org/andre_k/32/28208_2.png) [@Andre\_K](https://community.openenergymonitor.org/u/Andre_K)\
**Post date:** [20 April 2025 16:55 UTC](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976/40 "2025-04-20T16:55:38Z")

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Solar influence is huge for me as well. I’m currently in process building an addon for the MyHeatpump app to perform heat demand estimation including solar gains from official meteorological sources. Have a look here:

> [@A local heat demand tool for the myheatpump app](https://community.openenergymonitor.org/t/a-local-heat-demand-tool-for-the-myheatpump-app/28428):
>
> We’ve got a really great heat demand tool at [heatpumpmonitor.org](http://heatpumpmonitor.org), but I’ve always wanted something similar running locally. I have built a small addon to the bargraph view that does a heat demand plot & regression analysis based on the data window shown - if you select only the last 3 months, this data will be plotted and a regression analysis performed. Similarly, if you select space heating, only the heat for space heating will be used for the analysis. It’s not finished yet, but I’d love to …

[Previous page](https://community.openenergymonitor.org/t/add-new-metric-comfort-score/26976.md?page=1)