Home Assistant is a classic Marmite, some people love it, others hate it. I found it to be just too complicated, too volatile and temperamental, and I did not often find the community support actually produced useful answers. I do still have it (too lazy to remove it and install some other basic OS on the mini PC that does what your Raspberry pi will do), but I only use it for one or two things, like backups (HA has a good working backup add-on, so why not use it?). The bulk of my monitoring is done using python scripts I wrote. It took a bit of trial and error, but it has now been set up for getting on for 18 months, and is very robust eg the data is in csv files, much easier and more table than in sqlite or some other database, and the whole thing even  restarts itself when the power comes back after a power cut.

I suggest you try HA for a while. You may mind it is just the thing for you! But if it isn't, there are other ways.  

Thanks. 

Yes I use a windows laptop, bought a raspberry pi 4 to install Home Assistant recently which is another learning curve.

There's a tutorial online at GitHub for the ESPAltherma that looks complicated , but I can use Google to search for terms I've never heard of, which looking at the tutorial is quite a few. 

I'll get there👍

I've no idea into any computer programming but I'm a willing learner. 

Given willingness to learn, and assuming basic literacy, numeracy and ability to think logically, don't be afraid to look at python. It is a fairly high level (by which I mean human readable) programming/scripting language with hundreds if not thousands of packages that can be used to do almost anything. It may well already be on your PC (assuming that is what you use), in use by some other program, but you will need a generic standalone installation to get started. It's not huge. An example of a simple script (found online) that gets the mean for a variable (rows starting with # are comments, the actual script is only four lines):

# pandas is a package that does all sorts of data manipulation
# 'as pd' means I can refer to it as 'pd' (as in the 'hp_data = pd.read_csv...' line below)
import pandas as pd

# read data from a CSV file full of heat pump data, first row has variable names
# data ends up in a dataframe called hp_data
hp_data = pd.read_csv('data.csv')

# perform analysis on OAT (outside air temp)
mean = hp_data.mean()
print(f"Mean: {mean}")

I've just ordered the kit for the ESPAltherma hook up.

I've no idea into any computer programming but I'm a willing learner. 

I know it's not going to be highly accurate like some off the kits available, but it should give a good baseline to start getting better efficiency because as of now I've no idea how often the heat pump cycles, the Cop/Scop etc as the MMI reading kWh usage is in whole numbers 1.4 would be 1, 1.6 would be 2 etc.

Fingers crossed it goes well🤞

Further, in cold weather, you may be able to set back your temps slightly or adjust your ASHP settings (maybe lower LWT - I'm not familiar with Daikin settings) to just trickle heat into the house at 1kWh thus staying within the capacity of the battery and not allowing the internal temperature to drop significantly, getting you through to the next cheap slot where you can raise the temps again and recharge your batteries. I do this on my Samsung in Weather Compensation mode which allows the target LWT to be easily adjusted up/down by +/- 5C on the controller, setting back the LWT overnight or bumping it up in very cheap Agile slots to deliver more heat at cheaper prices.

suppose I've got to weigh up the cost of additional batteries v cost of hitting the higher Cosy tariff occasionally. 

Or just accept sometimes you will use higher rate electric. You should still come out way cheaper than standard rate electric.

Thank you for reply. 

I suppose I've got to weigh up the cost of additional batteries v cost of hitting the higher Cosy tariff occasionally. 

Although missing the much higher 4pm to 7pm tariff should be achievable at even the coldest days if my usage isn't too far from yours. 

Cheers