The modellers are determined to settle this question using models, in much the same way that alchemists sought to turn base metals into gold by using dark magic, but my own inclination is that the only satisfactory answer will be an empirical one, even if such an approach has the problem that no two days are the same, in other words, I can't do a controlled experiment, instead I have to rely on observations.

I was browsing older threads and found this, seeing as it is the quite holiday time between holidays and it is horribly wet and windy out there, I have nothing better to do.

Basically alchemists did not use dark magic.  There's no evidence they did or tried to; surviving texts don't say that.  The main accusation of using demons came from a Spanish  Inquisitor in the late 14th century, but even at the time they thought he was a bit of an extremist. 

The aim usually was to use knowledge of natural processes to change the constituents of the metals in question in order to make them into gold or silver.  Of course one of the reasons alchemy never quite made it as a serious university topic was that people greatly disagreed on whether it was possible or not in the first place and there were arguments for and against it.  Ultimately it failed to do what was promised so was gradually abandoned in favour of it's offspring, chemistry. 

You are indeed correct, while Alchemy may have received a bad press, probably because it was feared by the then church hierarchy, Chemistry is now fully accepted by modern society.

The main problem with using any form of simulation is first identifying the main variables which affect the process, and then measuring them with the required precision for the end results to be accurate and meaningful.

I believe that the first objective has been achieved, although I do keep adding more capability to the spreadsheet as more knowledge becomes available. The second part of the requirement is gradually improving, but does need more data from different sources.

I was browsing older threads and found this, seeing as it is the quite holiday time between holidays and it is horribly wet and windy out there, I have nothing better to do.

Basically alchemists did not use dark magic.  There's no evidence they did or tried to; surviving texts don't say that.  The main accusation of using demons came from a Spanish  Inquisitor in the late 14th century, but even at the time they thought he was a bit of an extremist. 

The aim usually was to use knowledge of natural processes to change the constituents of the metals in question in order to make them into gold or silver.  Of course one of the reasons alchemy never quite made it as a serious university topic was that people greatly disagreed on whether it was possible or not in the first place and there were arguments for and against it.  Ultimately it failed to do what was promised so was gradually abandoned in favour of it's offspring, chemistry. 

I believe this due to the fact that the thermal energy output of the heat emitters is not linear, so although LWT may change linearly with OAT, the quantity of thermal energy being supplied is not linear. I adjusted the WC curve settings to be balanced at 0C and 15C, but this balance is not maintained at other OAT values. I would welcome your thoughts if my assumptions are correct.

I can respond to this straightaway as I played around it when I did my WC simulation model (a very focussed model designed to test that one thing only - attached).

As you say the 'ideal' WC (with rads) is not linear and a linear WC will lead to slight mismatches in output vs demand.  In my model I looked at several variants on possible linear and non linear wc curves, to see if they made much difference (answer - a percent or two in energy use).  You can see the variants in the tables.  A 'best fit' linear approximation is one of the options, as is that jacked up by a degree or two to ensure that the house is always warm enough.

Oddly enough this is where HPs that do not modulate the flow rate for constant delta T may be slightly better.  Linear WC with constant flow rate' is a bit closer to the 'ideal' weather compensation curve than is 'Linear with fixed delta T'.  

Thanks for the explanation, very helpful, I will give it a look over and try some breaking tactics.  

Hi James,

You are indeed correct, the WC 'curve' is a straight line calculation based upon the values in cells I5 and I6 and K5 and K6.

Energy Demand : This is calculated from the standard heat loss as set in Initial Data and the temperature difference between IAT and OAT.

Energy Supply : This is an awkward one to calculate since it needs to limit the value when the heat pump reaches maximum output and cannot go any higher. Whilst the heat pump is operating within its normal range, energy supply is a measure of how much thermal energy the heat emitters can accommodate at the given LWT. It also takes account of changes in Delta T and variations in IAT, such that as IAT increases, the heat emitters can dissipate less thermal energy for a given LWT. The problem was trying to limit the maximum value of energy supply, since this varies with LWT and OAT, so in the end I took the simple solution of only calculating the limit for the energy supply, when energy demand exceeded 14000W. This approach works okay unless the OAT is above -4C, and a large positive WC offset is applied when energy demand is below 14000W. If you can think of a solution I will be 'all ears'.

Duty Cycle : This is a measure of when the energy supply falls below the minimum continuous output of the heat pump, so will likely start to cycle.

PI (Power Input) : This is derived by dividing the energy supply value by the COP value.

LWT : This is calculated from the WC curve values and the WC offset.

COP : This is obtained from the Detailed Data tables via the Lookup Table and the Intermediate Table and should be the value at the given LWT and heat pump loading.

Building Thermal Capacity : This was added to investigate how different thermal masses could affect how a system responds. The effect is seen in the Actual IAT (finish) calculation, where the change in energy balance affects the IAT.

Obviously the green highlighted cells are the ones that can be varied.

One thing that became apparent is that although the WC curve may be linear, the actual response in thermal energy output is not. I believe this due to the fact that the thermal energy output of the heat emitters is not linear, so although LWT may change linearly with OAT, the quantity of thermal energy being supplied is not linear. I adjusted the WC curve settings to be balanced at 0C and 15C, but this balance is not maintained at other OAT values. I would welcome your thoughts if my assumptions are correct.

Possibly contributing?

I suspect that the second increase in LWT occurs after your heating system and heat emitters are fully up to temperature, hence the RWT starts to increase which in turn pushes up the LWT.

That sounds very plausible, except for the fact the LWT rise appears to start just before the RWT rise, see at around 0703h. The four phase pattern is ubiquitous at the moment, here is another random selection from late October, and again the LWT starts just before the rise in RWT in two of the three cycles (in the other, the left hand one, they change at the same time). That said, we are relying on the Midea sensors being spot on... 

I suspect that the second increase in LWT occurs after your heating system and heat emitters are fully up to temperature, hence the RWT starts to increase which in turn pushes up the LWT.

Interestingly, the first ramp up isn't associated with a disproportionate increase in energy use (energy in). In fact, it (energy in) is pretty stable throughout the on phase, while the energy out rises a bit during the on phase, suggesting a slight increase in efficiency over the on phase (which I suppose could also be worded as it starts off a bit less efficient). But, overall, as I see it, nothing world shattering to see here, no obvious cycling penalty.    

https://shellystore.co.uk/product/shelly-em-2x50a/