SteamyTea

Was my thinking, maybe a trial is the answer. Shaded area and compare temperatures. It has come about as my OAT sensor (DHT22) has eventually got too wet and packed up. So probably time to change it to a DS18B20, should be fairly easy to do.

Ask a Quantum Physics to do it, then the bats will be both there, and not there.

When working out thermal losses through walls, it is usual to use outside air temperature (OAT). Would it be more accurate to use actual outside wall temperature (OWT). This would more accurately describe the thermal flux as it would account for solar gain, wind, evaporation etc. Should be easy enough to bury a sensor a few mill deep into a wall. May also be worth adding sensors to opposing, or all external walls even. This would give a much better picture of what is happening. Thoughts anyone?

I am awaiting @Dave Jones to comment, I am sure his input will shed light on it. Until then, one question? Does this installation do the DHW?

Does the module array have shading issues? Also worth looking at the efficiency distribution, it is not often that system work anywhere near maximum output, most of the time they are below 25% of the name plate capacity. Would be better to add an extra module or two if you can.

I take it you did not pay the hundred quid with a credit card.

Run the Peugeot off it.

Be more like 20⁰C difference, and I assumed UFH with thicker insulation and radiators with thinner insulation, where the dT may only be 10⁰C (assumes winter ground temperature is 8⁰C). But think the original question was with regards UFH and where does the thickness come from. It comes from Part L building regs. Probably why they are going to be updated to take low temperature UFH into account.

Not as if we go below 0⁰C for very long in the far SW. That is the easy and cheap way. https://www.ebay.co.uk/itm/353514304085

What delta T have you calculated that on? Room temperature to Ground temperature (about 10°C) or slab temperature to ground temperature (about 22°C). Two things, BEVs, even if powered purely from coal fired powerstation have a lower life cycle analysis than ICE cars. Lithium is not, generally, 'dug from the earth'. It is dissolved in water and then naturally evaporated, leaving a salt that then gets processed. Unlike iron and aluminium ore which is mined, generally open cast mining.

https://www.bbc.co.uk/news/uk-england-somerset-60453727 Don't use four candles. Still, at least their fire brigade has a roof. Was told that one of the fire stations lost it's roof, along with the RNLI at Sennen Cove.

That is missing the point. This extension is getting UFH, so the slab will be at 30⁰C plus, not at 17 or 18⁰C. You would not expect a plumber to bury a radiator in the garden.

why do you think that when the UFH makes the temperature gradient to the ground a lot higher?

It is an extension to an existing building, so a lower U-Value of 0.7 W.m-2.K-1, so the drawings are probably correct. Don't mean it is a wise decision.

I think is is a great topic. Chance to meld mathematical modelling and process control.

PP9s and a buzzer.

I have just downloaded, for free, Python Machine Learning. Personally I don't think it needs to be too difficult. Really just a simple feedback loop based on basic thermodynamics, which is similar to an RC circuit in electronics in this instance.

Trick is to not have a freezer. I have managed without one for decades. Tinned and dried food is the way to go.

Yes. And it could be testing the MET Office prediction as much as anything else. I am going to ponder the whole problem more as I think there is merit in a simple self learning algorithms that can put the correct amount of energy into a building. This may become more useful with variable ToU tariffs as you can bank prior to a known expensive time, or take a bit of a hit until a cheap time come.

Was thinking more along the lines of deviation from binned prediction ranges. So something like this with made up numbers: Δ Temp Range Predicted Energy Input Actual Energy Input 0 0 0.0 1 0 0.0 2 0 0.0 3 0 0.0 4 0 0.0 5 0.1 0.1 6 0.2 0.1 7 0.4 0.1 8 0.5 0.1 9 0.6 0.6 10 0.7 0.8 11 0.8 0.7 12 1.0 1.1 13 1.1 0.8 14 1.2 0.6 15 1.3 1.3 16 1.5 0.1 17 1.6 0.2 18 1.7 1.5 19 1.8 0.2 20 2.0 0.8 Giving a chart like this Which give a Chi Square result of 0.985, when tested on values greater than 0. As it is greater then 0.05, then the null hypothesis is not rejected. Though that does not mean the hypothesis is correct of course.

It was a rhetorical retort to @ProDave's reply. Book is OK, even if 14 years old now.

If there is a fork truck in the building, then block. If an office, then look at timber frame and cellulose insulation as the sound deadening is impressive.

Is in my place as well. Generally less than a °C. And I have basically no control unless I manually twist the input and output knobs on the two storage heaters. Still be interesting to run a Chi Square on it as that will check the formula/equation/algorithm, rather than the outcome. Maybe @DamonHD can have some input as his devices are trying to do the same, but via a different pathway (and they may have got a statistician on board now).

Took me over 20 years to realise how to do it properly. And how to manage people, especially my boss.

I know, just I am a bone idle (expletive deleted). One of the reasons I do what I do is that I have a very decent work/life balance. Friday night was a bit fraught with the unexpected power outages and half term, but within 15 minutes of closing (sold out), we were joking about it. Some jobs/companies, when you have a really bad day, have a lingering, negative feeling on for months. I have tried very hard to get rid of that attitude as I know that everyone is doing their best in a fast moving, and changing, environment. And I get paid more than my mate who is a very good thermal engineer in the biogas field. But can I do those jobs remotely when I am sitting in a cafe, or just overlooking the sea? That I would be interested in.