I posted it to you since you are familiar with the subject matter, and would provide an unbiased reply.
I suspect a more accurate answer may be that D wants to paint a picture that has D and J as sage old chaps having a learned chinwag in the library while C is the child in the garden having a tantrum.
Some more to the point comments on the above:
(1) I don't know why @derek-m thinks the first part of the original question (do setbacks save money?) has been answered. His own posted hypothetical modelling suggests savings can be achieved, but at the cost of comfort; if a recovery boost is added, the savings become trivial. I don't recall @jamespa making a definitive statement either way, and the general thrust of his most recent comment is that nothing is settled, experiments are doomed because the subject is just too complicated ("this really is too difficult to do by experiment") and our best chances lie with "some more playing with the model...to get a more quantitative feel". None of that suggests the matter is settled. Nor do I think the matter is settled. My hunch, based on the simple idea that it must cost more to maintain a house at a higher average temperature, is that setbacks do save money, but I have yet to demonstrate that, because the experiments or rather observations and analysis are difficult (but not impossible) to do. I say simple because I appreciate that the thermodynamics of recovery and boost are much more complex that those of maintaining a steady state. I also have, as is known only too well, a profound distrust of models, and the depth of that distrust increases the further the model is from observed data. I stress this is a personal view, if others want to fly model aeroplanes, and then find themselves wondering why they are crashing to the ground, that's fine by me, though I might be inclined to add please don't crash in my back garden, because then I might have a real tantrum.
(2) @derek's "second part [of the question]" isn't really a second part to be answered, it is instead a condition on the first part, that the setback should not compromise comfort. Clearly I could turn the heating off for 23 out of every 24 hours, rather severe to say the least, but it is still a setback, and save a whole lot of money, but it fails on the condition "without compromising comfort". The single question (there aren't two parts) is, to put it another way, 'can a setback that doesn't compromise comfort save money?'.
(3) comfort (ie personal comfort) is subjective, and for that reason I don't think we can put a number on it, like 18 degrees Celsius. Instead, we can leave it as an arbitrary and formally unstated number, and instead say that the actual applied condition, for answering the question, is that the house must over time stay at the same average temperature, whatever that average temperature, chosen by the occupier, is. This is close to, but not identical, to @jamespa's returning to the original state within 24 hours, they are just different ways of testing for the same thing, ie a steady state over time. We now have a simple global test for whether the condition has been met: the average IAT over time must stay constant.
(4) This global test is necessary but not sufficient. It could be satisfied by a running state in which the house is chilly at breakfast time, but does recover by early evening. There needs to be an additional requirement, and this again is a personal choice. For me, it is that the actual IAT should have recovered to within one degree of the desired IAT by 0700. Others can choose whatever works for them. Again, this is a simple test, either the house is or isn't within one degree of the desired IAT at 0700. It is by this simple test that setback without a recovery boost fails in my house for me: simple observation tells me the house is more than one degree below the desired IAT on most (but not all, eg if it is very mild) mornings. To meet the comfort condition, if I have a setback, I must also have a recovery boost.
As noted above, I remain sceptical of the supremacy of modelling over observation (others are perfectly entitled to hold opposing views, we don't need or benefit from having a spurious row about it), and for that reason I am going to continue to collect observational data, and try to find out what it can tell us. In the meantime, I mentioned I had nonetheless attempted to run @kev-m's real world data through @derek-m's model. I did this by reading the (approximate) numbers of @kev-m's charts and putting them into the model. I've probably got this wrong, as the instructions on how to use the model are not exactly clear. What I did is enter the initial starting IAT, the hourly OAT, and then adjusted the heat pump running state (top row, 1 or 0 for on or off) to add the setback. The results, top half with setback, bottom half with no setback, appear to suggest a substantial saving by using a setback, around 12 kWh over a 24 hour period (note I had to convert PI (W/h) to PI (W/m) to match @kev-m's data format). However, the setback and recovery fails my comfort test, the actual IAT is more than one degree below the desired IAT at the end of the modelled period, and I suspect over longer periods the settings would fail the global average IAT must stay the same test, but I am not sure how I can increase the recovery boost to meet the comfort test. All that said, these are the results I got:
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I also plotted the model's setback results (lower plot), and compared them to @kev-m's original plot (upper plot):
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The right hand side of the model results plot is really rather good, as is the IAT throughout. The left hand side of the energy in (PI) on the other hand appears to be a long way out. A Mk 1 Eyeball averaging out of the cycling in the real world data suggest an average PI somewhere around 10 or maybe 12, while the model results have it running between 15 and a little over 20 W/m. Perhaps @derek-m would be kind enough to explain where I have got it wrong, to get such contrary results.
Am I misreading this or is there cycling on the LHS of what i presume to be actual measurements, whereas the model shows no cycling?
4kW peak of solar PV since 2011; EV and a 1930s house which has been partially renovated to improve its efficiency. 7kW Vaillant heat pump.
Am I misreading this or is there cycling on the LHS of what i presume to be actual measurements, whereas the model shows no cycling?
Correct, the actual measurements (upper plot) shows some cycling on the LHS, the model (lower plot) does not.
@derek-m may correct me but I don't believe the model does cycling as such. My understanding is that it recognises the occurrence in the 'duty cycle' figure for any given hour (calculated by comparing the energy demand to the min o/p) but then doesn't impose any penalty or other behavioural change, other than to match the average supply to the demand. Effectively it behaves as if there is at least one cycle per hour so that the energy supply can be represented by the average. In the absence of any concrete information on the penalty of cycling and assuming that there are sufficient cycles that the flow temperature does not have to rise materially to compensate for the on-off working, this isn't a bad assumption*.
I cant actually work out for certain why the real thing is cycling. It looks as if it might be responding to excursions of IAT which perhaps are outside some limits set by some part of the control system (which could be the HP controller or a secondary thermostat), not to a limitation of modulation, although why that is occurring isn't clear (some external influence like solar gain or cooking, a slightly wrongly adjusted WC curve, something else). Some insight to that would certainly help interpret the differences in output from the model and the 'real' system.
* as an aside there is interesting argument here that 'short cycling' is a good thing not a bad one, where in this case 'short' is defined as faster than the response time of the water in the system.
This post was modified 1 year ago 2 times by JamesPa
4kW peak of solar PV since 2011; EV and a 1930s house which has been partially renovated to improve its efficiency. 7kW Vaillant heat pump.
Am I misreading this or is there cycling on the LHS of what i presume to be actual measurements, whereas the model shows no cycling?
Correct, the actual measurements (upper plot) shows some cycling on the LHS, the model (lower plot) does not.
@derek-m may correct me but I don't believe the model does cycling as such. My understanding is that it recognises the occurrence in the 'duty cycle' figure for any given hour (calculated by comparing the energy demand to the min o/p) but then doesn't impose any penalty or other behavioural change, other than to match the average supply to the demand. Effectively it behaves as if there is at least one cycle per hour so that the energy supply can be represented by the average. In the absence of any concrete information on the penalty of cycling and assuming that there are sufficient cycles that the flow temperature does not have to rise materially to compensate for the on-off working, this isn't a bad assumption*.
I cant actually work out for certain why the real thing is cycling. It looks as if it might be responding to excursions of IAT which perhaps are outside some limits set by some part of the control system (which could be the HP controller or a secondary thermostat), not to a limitation of modulation, although why that is occurring isn't clear (some external influence like solar gain or cooking, a slightly wrongly adjusted WC curve, something else). Some insight to that would certainly help interpret the differences in output from the model and the 'real' system.
* as an aside there is interesting argument here that 'short cycling' is a good thing not a bad one, where in this case 'short' is defined as faster than the response time of the water in the system.
I can. What you are seeing is cycling caused by IAT. It's reaching its set point, or, because AA allows it, up to 1.5 deg above it. It then stops calling for heat and the ASHP stops until the house cools down a bit. The other type of cycling (which this isn't) is caused by RWT being getting too close to set LWT and the ASHP stopping because it can't modulate down any more. This is Mitsubishi AA in action; it really, really tries to prevent the LWT type of cycling at the expense of higher LWTs and pushing the hysteresis on the set IAT to the limit.
BTW my house is a bungalow with a lot of windows so the south side of the house gets some solar gain. The controller is normally on the other side but still. As for cooking, the microwave doesn't give off much heat...
Life has got in the way a bit but I'm going to pull together some proper data to correspond with the charts I produce. The current issue is that the Melcloud data dump is now too big (about 600,000 rows) to load into Excel on my laptop and I need to find a way to extract parts of it rather than Melcloud's approach of giving you all data since your system was installed.
What I do is have the data in csv format, which I can then load into a text editor, such as Notepad++, and extract slices at will. I also use python's pandas module to do the same and more, but that needs some coding knowledge (not complicated), which your son might be able to assist you with. A third approach is to use q - Text as Data. This is an extremely useful command line program that lets you run sql type queries on text (eg csv) data, with the bonus that it can run the queries on multiple files, eg if you have a collection of csv files, say one for each year, you can run a single query on all of them in one go eg "select datetime, OAT, IAT from mydata*.csv where datetime like '%-07-%'" to get the data for July from each file, assuming datetime has July as -07-. By default, it dumps the results on screen, or you can redirect the output to another file (> mydata-jul.csv). It is freely available for Windows, Mac and Linux systems.
PS I hope you don't mind me doing an eyeball extraction of your data, as I did above. It was at least a way of getting something pending you posting the actual data.
I used to do a bit of sql and other programming so I'm reasonably familiar. It's been a while though but I'll have a go.
I used to do a bit of sql and other programming so I'm reasonably familiar.
You should be fine, they are not complex queries, with the csv file(s) becoming the tables you select from. The sql 'dialect' is sqlite, which, as you will know, is straightforward to use. I would go so far as to say Q Text as Data (I got the visible words in my earlier post the wrong way round, now corrected both in my post and your quote from my post, though the underlying link was correct) is a game changer, one line of code can effortlessly do what would need several lines of code in python. It is also very human readable.
One potential q 'gotcha' is if you have invisible 'nul' bytes (0x00, not 0x30 '0') in the data, it will not run (gives you an error message instead). If that happens, use a hex editor to find the nul (0x00) bytes and delete them.
I look forward to seeing your data!
Midea 14kW (for now...) ASHP heating both building and DHW
I don't know why @derek-m thinks the first part of the original question (do setbacks save money?) has been answered
For what it is worth I'm fairly comfortable that modelling results predict modest savings (3-5%) for mild OATs with a setback regime that for many will be tolerable, albeit perhaps a bit colder than ideal at breakfast time. And I'm happy, until we have divergent experimental results, to believe the models.
If I had a heat pump (if only ... my local authority is driving me mad!) I would base my behaviour on the models for now, not because models are superior to experiment, but because they are currently all we have. However I think there are potential gotchas, just applying logic to the results, which I would look out for:
If the oat is lower during recovery than during setback, I would be concerned that this might reverse thr savings. This is more likely the earlier the target time of breakfast. I would want to look at some typical curves for diurnal variation before aiming for a full-ish recovery ( say to better than a degree) for breakfast earlier than say 8am
I wouldn't expect the tentative conclusion necessarily to work in a very well insulated house with very high thermal mass (basically a house that doesn't cool by at least 2-3C in a six hour setback). Such a house is a pure energy integrator and so to first order its obvious that 24x7 at the lowest ft possible is optimum. However it may be that, at times of year when the day is much warmer than the night (principally spring and autumn when the diurnal range is larger) that such a house benefits from turning off in the depths of the night because it results in more of the energy being delivered at higher cop. Modelling or experiment, taking into account a typical daily temperature profile, would be needed to determine this.
I haven't seen enough results at low OATs yet to be certain what happens then. Probably its OK provided the setback is constrained so the house doesn't get too cold. Again a bit of exploration needed.
The comfort part of the equation depends on the recovery strategy which is for most people who don't write python scripts etc limited by the controller. If the controller is capable of a timed wc offset that suffices, but if not then there is the very real risk that recovery happens too slowly and the user reaction is permanently to jack up the wc curve wiping out or reversing the saving.
In summary I think I'm prepared to say, based on what we have seen so far, that setback most likely can offer modest savings without materially compromising comfort in some relevant circumstances and provided your controller can operate a suitable recovery strategy. However until the space is explored more (and ideally at least a couple of data points are verified with experiment) I wouldn't want to make it a general 'recommendation' for those who are not so tech savvy (but by the same token wouldn't say definitely dont so it to soneone whobwas determined, unless they were likely to fall into one of the gotchas above). For many modest savings of 3-5% are more easily and more reliably achieved by ensuring that the control system is dominated by the wc curve not by room thermostats or trvs driving the pump into time modulated mode unnecessarily.
I've scanned through the data I have, which although at first glance seems like it is a lot of data, it is in fact only five weeks or so at the end of the last heating season and five weeks or so at the start of this heating season, looking for periods when the OATs were similar, only to find that in reality they haven't really happened - yet. I'm stuck with the fact the real world is in control, and there is nothing I can do about it! Take this period, which spans a few days either side of my transition to running overnight (2100-0300) setbacks with an auto-adapt script to provide a recovery boost when needed:
Take the morning of 7th Nov for example: clearly I used more energy in, but it also the time when the deepest, biggest trough occurs in the OAT, meaning I don't know how much of the extra energy in was due to the lower OAT, via the WCC, and how much to a recovery boost (hence my recent attempts to establish baseline energy values for given OATs, as a way to allocate energy in to baseline (would have been used anyway) use and boost (extra energy used in the boost) use).
There are however two 24 hour periods when the OATs were similar, the 24 hours that make up the 2nd Nov, and the 24 hours from 0900 on the 4th Nov and 0900 on the 5th Nov, with the former being pre setback, and the latter including the first setback. The space heating, ie excluding the DHW spike on the 4th Nov, 24 hour energy in values are quite different, 21.25 kWh against 16.07 kWh respectively, considerably more than the modest 3-5% savings mentioned above but - stupidly with hindsight - I also changed the WCC endpoints at the same time as I introduced the setbacks with auto-adaption, as the house had been running a bit warm (~20 IAT against a desired IAT of 19). Some of the reduction in energy in will be because of that reduction, but how much? A figure often bandied about is that a 1 degree lowering of IAT (which is about what I did by lowering the WCC endpoints) will reduce energy use by about 10%, ie the 21.25 kWh energy in before the change would become 19.13 kWh after the change, but in fact it fell to 16.07 kWh. Was the extra saving due to the introduction of the setback or not? I don't know, I need more data...and I will have to be patient, it takes time to accumulate.
Both the steady state (no long term change in IAT, the average flat lines over the period when setbacks were in use) test and the recovered by breakfast time test (IAT reached 19 degrees at 0704 on the 5th Nov) were satisfied, but the way.
Midea 14kW (for now...) ASHP heating both building and DHW
A figure often bandied about is that a 1 degree lowering of IAT (which is about what I did by lowering the WCC endpoints) will reduce energy use by about 10%
Thanks for the extra data.
1C reduction in IAT should in theory reduce energy consumption by 1/(IAT-OAT). If IAT is 20 and OAT is 10 that's 10%. As these figures are not atypical, 10% is a good rule of thumb which is likely why its bandied about, but nothing more.
However real life is a bit more complex. Because there are other sources of heating the base IAT for the calculation (and in principle any calculation of loss) is actually a bit lower than the target IAT. Its sometimes taken to be 15.5C (for Actual IAT = 20 - that's the figure 'degree-days' uses by default) but it depends on what other energy sources there are. The consequence of this is that the reduction in heating energy required is actually higher than the simple 1/(IAT-OAT) calculation would indicate, most especially at moderate OATs. As a result, I don't think the reduction is readily calculable to any degree of accuracy, but of course could be measured given sufficient data points.
4kW peak of solar PV since 2011; EV and a 1930s house which has been partially renovated to improve its efficiency. 7kW Vaillant heat pump.
I've scanned through the data I have, which although at first glance seems like it is a lot of data, it is in fact only five weeks or so at the end of the last heating season and five weeks or so at the start of this heating season, looking for periods when the OATs were similar, only to find that in reality they haven't really happened - yet. I'm stuck with the fact the real world is in control, and there is nothing I can do about it! Take this period, which spans a few days either side of my transition to running overnight (2100-0300) setbacks with an auto-adapt script to provide a recovery boost when needed:
Take the morning of 7th Nov for example: clearly I used more energy in, but it also the time when the deepest, biggest trough occurs in the OAT, meaning I don't know how much of the extra energy in was due to the lower OAT, via the WCC, and how much to a recovery boost (hence my recent attempts to establish baseline energy values for given OATs, as a way to allocate energy in to baseline (would have been used anyway) use and boost (extra energy used in the boost) use).
There are however two 24 hour periods when the OATs were similar, the 24 hours that make up the 2nd Nov, and the 24 hours from 0900 on the 4th Nov and 0900 on the 5th Nov, with the former being pre setback, and the latter including the first setback. The space heating, ie excluding the DHW spike on the 4th Nov, 24 hour energy in values are quite different, 21.25 kWh against 16.07 kWh respectively, considerably more than the modest 3-5% savings mentioned above but - stupidly with hindsight - I also changed the WCC endpoints at the same time as I introduced the setbacks with auto-adaption, as the house had been running a bit warm (~20 IAT against a desired IAT of 19). Some of the reduction in energy in will be because of that reduction, but how much? A figure often bandied about is that a 1 degree lowering of IAT (which is about what I did by lowering the WCC endpoints) will reduce energy use by about 10%, ie the 21.25 kWh energy in before the change would become 19.13 kWh after the change, but in fact it fell to 16.07 kWh. Was the extra saving due to the introduction of the setback or not? I don't know, I need more data...and I will have to be patient, it takes time to accumulate.
Both the steady state (no long term change in IAT, the average flat lines over the period when setbacks were in use) test and the recovered by breakfast time test (IAT reached 19 degrees at 0704 on the 5th Nov) were satisfied, but the way.
I haven't tried to work it out but I would have thought the OAT variation over the compared periods makes a big difference. It's a little bit unrealistic, but consider two situations, both with 6 hour setback and 6 hour recovery. Consider two different days. Firstly, an OAT of 0 deg setback, 0 deg recovery then 5 deg for the second 12 hours. Secondly, -5 deg setback and 5 deg recovery then 5 deg for the second 12 hours. I think overall heat loss is the same across the 2 scenarios. But comparing the second scenario with the first, the overnight saving will be more because the ASHP isn't running when it's really cold and the recovery boost happens when it's warmer. Although some of this will be negated by the OAT dropping a bit more during the colder night. Hmmm.
Indeed. It is a very dynamic situation, with lots of variables constantly changing and interacting. At least with observed data, assuming it is accurately measured, we do have real measures of the inputs and outputs. The raw data also needs to be detailed, say every minute as we are both doing, because averages over longer time can obscure important detail. I do remain confident that when we have enough data, it will be possible to draw conclusions, but it is going to take a while.
Midea 14kW (for now...) ASHP heating both building and DHW
Just bear in mind that we need as much data for the 'control' (ie without setback) as we do for the setback situation, whether its historic or newly collected.
4kW peak of solar PV since 2011; EV and a 1930s house which has been partially renovated to improve its efficiency. 7kW Vaillant heat pump.
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