Great to hear that you are doing this @Vincent.
After a bit of a break from this side of things I’m also back trying to improve on our HeatpumpMonitor data analysis. I’ve attached a Claude based regression analysis you might find interesting regression.zip (20.0 KB). I’m a bit embarrassed that even with all this data we still dont have a solution that can predict the performance of each system on the site to better than e.g R² 0.630 (weighted flowT-outsideT combined with utilisation factor) or CV-R² 0.56 using measurements that are slightly more intuitive and more relatable to design stage variables such as measured_mean_flow_temp_coldest_day or (lift + ln(utilisation) + DHW fraction) I would love to hear your thoughts on how we can improve on this!
To your questions:
1. Per-system heat feed provenance. Yes all the metrics such as combined_heat_kwh are integrated from the power register data from the heat meters themselves (for MID-metered systems), the power register data does go negative on defrosts and so is not affected by the heat only energy registers on the heat meters. Doing a quick check now I did notice ~5 systems that were still not showing negative heat on defrosts and have added data error flags to those so that they are flagged as having that issue.
2. How is metering boundary code derived ? The code that derives the boundary code can be found here heatpumpmonitor.org/www/Modules/system/system_view.php at main · openenergymonitor/heatpumpmonitor.org · GitHub.
The reason we dont require monitoring of the indoor controller for all systems on H4 is that we noticed early on that Vaillant Arotherm+ indoor controller only used about 1W of electrical power which only makes about a 0.01 SPF difference and so is not worth the cost of an additional electric meter to record. The Grant R290 indoor controller is similar at ~3W, both are roughly an order of magnitude less than the potential metering error from the electric and heat meters e.g Heat meter accuracy testing - #6 by TrystanLea. I noticed reviewing a few systems now that some of the Viessmann units had not ticked the box even though we can see on the backend feeds that they had the indoor controller metered so have corrected those. Thinking about it I think we could actually improve on this and have a standarised way of dealing with the case of known negligible power indoor controllers. E.g have an option to add additional small power draws manually as a constant value and have a list of what we expect those to be for applicable makes and models.
Looking at the H3 systems, there are a lot of H3 systems with hydraulic separation but no metering of secondary distribution pumps hence H3.
I notice your total numbers of systems 66 code4 systems without control metering and 71 code3 systems are larger than the totals I get. I assume you are quoting numbers for all systems including those that are not mid metered or/and have metering errors? I would recommend filtering out all non mid-metered systems in your analyses.
3. Outdoor temperature resolution. Most of the hourly outdoor temperature data is from the MetOffice weather data API. Higher resolution outdoor temperature data indicates a local sensor at the home.
Good to hear, let us know how you get on! would love to hear if you can make any headway on the performance prediction challenge!