The importance of commissioning - I’m going to rewrite this one with a bit more of an intro to the work analysing the Electrification of Heat data and hopefully some numbers on how many systems appear to have high weather comp etc. It would be nice to have some examples of before and after optimisation here as well.
Thanks @chrisg@Nando.Tolboom We dont have humidity data for all tests, but I will add it where it has been noted, good idea, it’s obviously a key factor
Hi @TrystanLea, I am concerned that you have used my system (Samsung 12kW NE Derbyshire) as an example of oversizing. My usage is so atypical that I don’t think that your method of calculating heat loss will be accurate. I only run the heat pump during Cosy cheap times, don’t heat 2 of the bedrooms and put up with the north facing kitchen cooling to 15C at times. This means that our pre - install quoted heat loss which assumed steady state conditions and room temperatures of 18C in all rooms apart from living room (21C) was always going to be more than our current one.
I think if we did run 24/7 at 18C then 8-9kW might be a more accurate heat loss at OAT - 3.7C.
Hi TrystanLea, Is it possible a relationship exists within the dataset linked to the design choice of UFH and low temperature operation? The sole adoption of UFH on a surface area heat transfer basis suggests it should achieve lower flow temperatures when compared to radiators (or a mix of radiators + UFH).
There are some high performing under floor heating systems on there, I haven’t specifically done any comparative analysis on that, apart from noticing that the design flow temperatures on some of the under floor heating systems is amazingly low!
Hi Trystan, Here is some source information extracted from the CIBSE “The UFH design and installation Guide”. It shows the ability to generate a low temperature heating system design and improve efficiency for UFH systems. The CIBSE does not present below 30C (Mean Water Temperature). However, I have extrapolated down to 25C (MWT) in the chart.
On a separate point, If you could remove the requirement of a buffer vessel, then it would reduce the flow temperature by ~3-4C. Is this a possible recommendation in your article for simple heating designs involving UFH only.
Here is a better comparison of a typical radiator (K2 Type) versus UFH. It shows the inherent design benefits of UFH versus a typical radiator system in lowering the water temperature. I ran these numbers when my own installer recommended a mix of radiators and UFH. In my case, it was an extensive retro-fit and I had the benefit of going fully UFH (top and bottom floors). A mix of UFH and radiators would have defaulted to a much higher mean operating water temperature, since it defaults to the radiator MWT. It was not an important consideration or conversation topic for the installer, but it would affect my future running costs and performance. As shown in the chart. I predicted a MWT difference of 20C for the house heat loss of ~40 W/m2.
Hi Trystan, The chart makes clear the relationship between low flow temperature and higher SCOP. I used your dataset to try and draw some further insights on the likely performance of the various emitters (old Rads, new Rads, UFH) and high SCOP. I made a crude attempt to filter each emitter type within the Top SCOPs and made the following observations.
The old radiator systems obtained a SCOP>4 for 17% of that datasets ( only 12 houses in my filter).The high performers all had a temperature of <37C.
The UFH systems obtained a SCOP>4 for 40% of that dataset (only 15 houses in my filter). The high performers all had a temperature <35C.
The new radiators obtained a SCOP> 4 for 32% of the dataset ( 44 houses in my filter). The high performers all had a temperature <36C.
If my filtering is reasonable, then it appears old radiators alone would be less likely to achieve a SCOP>4.0. This may explain the dominance of new radiators and UFH in achieving high SCOP outcomes within the Top of the SCOPs.
I checked the same dataset for the percentage of emitter types with SCOPs>3.5.
Old Rads: 67%, new Rads: 84%, UFH: 79%.
