SteamyTea

That is a nice looking unit and the sound levels seem very decent. Does it have filters on the air intake side?

Having slept on this, I feel that the use of a WSHP with such a shallow water supply is always going to cause problems. So, what to do. Fill in our favorite heat loss spreadsheet. https://forum.buildhub.org.uk/applications/core/interface/file/attachment.php?id=18333 That should give you an idea of what is actually needed size wise. Then look at what improvements can be done i.e. insulate and air tightness improvements. Then look at junking the WSHP (sell it on eBay) and fit a properly sized modulation ASHP. A bit of shopping about and you could pick up a decent one for not much more than 2 months winter heating bill.

I have been looking for years, if you have some links to the numbers please share. Porthleven, a place I know so well.

Right, I have been there, but not since I was at school near Witney. 0.75 kW would be 540 kWh over 30 days. Yes, can't see any other option initially.

Is that Wolvercote? Generally WSHP have a very good CoP. Do you have any idea what your CoP is currently. What make of HP is it.

2023 is much lower, which seems a bit odd, but seems to be right. I noticed that I did not put the error correction in what I first posted up and have changed the average function to only show relevant months. Now looks like this for 2023. This may be easier to read 2021 2022 2023 Month 2021 Mean Price 22.43 p/kWh 2022 Mean Price 34.6 p/kWh 2023 Mean Price 18.82 p/kWh January February March April 16.61 30.52 21.13 May 17.62 23.97 18.46 June 18.11 28.35 18.83 July 20.03 38.82 17.19 August 21.71 54.89 18.64 September 32.07 42.35 18.62 October 30.86 23.28 18.85 November December

I use =AVERAGEIFS(WhatToAverage,SortBy,TheCondition) So in my spreadsheet I use something like =AVERAGEIFS(Price,DayName,"="&$A7,Date,">="&$B$1,Date,"<"&$B$2)

2021 2022 2023

Imagine forgetting to turn that off. May be the next snowfall before you notice. Hottest year on record

Is this the sort of thing you are after?

What information are you actually trying to get out? Are you Northern or Southern Scotland?

Probably the same business model. Set up to protect the companies, not the end users.

With wind and solar power now being the cheapest to deploy, and a lot faster than hydro and nuclear, I am not so sure. They do dangle the MCS Quality Assurance as a plus point i.e. correctly calculated size and back up if the installer vanishes. My local council offers a similar assurance that they will pay up for car damage if you hit a pot hole. 3 of us hit the same pot hole one night. When we tried to claim the council said we needed to measure the depth of the hole. The (expletive deleted)ers had filled it in. I suspect that the MCS scheme is similar, used to be called REAL, REA when I was dealing with PV. Never heard of anyone managing to get a successful claim.

Right. May be worth a little time to look at what is happening and how it could fit in with everyday life. Biggest problem is that if the money that supplier makes goes below their usual tariffs, the tariff gets pulled.

Quiet day is it?

@Pocster Here is the TV for you. https://www.whathifi.com/news/lgs-new-signature-series-oled-tv-is-a-see-through-spectacle I am reliably informed that they make them the exact same size as your original walk on glazing. Just think how cool that would be fitted above a bed in your dungeon.

I just screenshotted the start of the files. I now notice that there is Tracker and Agile in the file names. So is Tracker based on a fixed daily price and Agile the more volatile hourly price? I find Octopus has too many tariffs.

Silly sod. How about rubber matting with holes in it?

Yes. You can set up a Solver in Excel to run though possibilities. The only data you have is door area, temperatures and door thickness, plus a list of possible value.

I had a quick look at that Octopus file list. There are 3 relevant files for my area, one is gas daily price Electric Daily Price And hourly Daily Price They look about right but I may be missing something.

You can look at a list of k values and take a guess. See how well it fits. https://www.engineeringtoolbox.com/thermal-conductivity-d_429.html

You know the thickness and surface area as well, so starting with the thermal conductivity, k = W.m-1.K, and resistivity R = L / k (where L is thickness in metres) you can rearrange to make W the subject. Once R is known, U-Value can be calculated U = 1/R, losses then calculated by incorporating the area A. Marks will be deducted for failure to show your workings. (and I did say, as I always do, that I may have made an error)

Hardly, more tears of disappointment, for our education system. Our old mate @DamonHD once told a story about his Father being told, by a youngster, that one of his science programs was a 'bit sciency'. And Stephen Hawking: 'Someone told me that each equation I included in the book would halve the sales.'

"I believe one of the bids could have delivered a comparable, financial return to administration and, crucially, allowed the business to continue to operate, safe-guarding hundreds of jobs and protecting livelihoods." Should be able to pick up the best bits, without debt, from the receiver.

@TerryE designed his heating system to incorporate the following days weather. Maybe he will join us here and explain what he has actually done. I understand it (as he is using a resistance heating system) that he calculates the expected energy for the next day, from the MET Office forecast, then adjusts the time he heats up his slab. After some time, his program looks back at the past data and adjusts for fine tuning. With an ASHP based system it is really a matter of juggling the main variables of optimal CoP and run time. Run time is pretty easy, but optimal CoP is the hard one. If the RH does up, that can cause the defrost cycle to kick in, possibly taking energy back out the system. The probability of frosting should be able to be calculated statistical, as could the SCoP. That may be worth looking at first to see if there are any meaningful gains to be had. A while back @Ed Davies and myself looked into the probability of one sunny day following another, we got negative results, which is a result in itself (I can't remember the P Value now). I do seem to remember that the best fit to sunshine was wind direction, but we have so little northerly winds (where I am) that it was statistically insignificant. Apart from the technical challenge, which is fun, more energy could be saved by driving a very economical car.