Estimating the thermal performance of my house

My house of shame

As I mentioned the other day, I want to make my house as close to carbon-neutral as I can manage.

The largest source of emissions is from the gas I use each winter to heat the house: the emissions have been around 2.5 tonnes of carbon dioxide in each of the last two years. Yes, that’s tonnes.

I could replace this with electrical heating or with a heat pump, but if the house is not properly insulated then it will very expensive to heat, and the heat pump will need to manage a larger load.

Before splashing cash on fancy heat pumps and solar panels and batteries, my intention is to first to improve the thermal performance of the house by:

1. Replacing the windows – which were old anyway – with modern triple glazing.
2. External wall insulation
3. Managing the air flow through the house.

Step 1 is almost complete: Step 2 is planned for the summer: and Step 3 is planned for next year.

I am aware that the return on these investments will be only just a few percent per annum of savings. But I honestly feel ashamed to live in a house that performs so badly.

But in order to plan rationally and to assess the effect of my improvements, I first need a way to assess how the house is performing at the moment.

Assessing current performance

One obvious approach is to record one’s household gas consumption and then plot it over time. This involves looking back through old bills and finding out the consumption of gas (in cubic metres or cubic feet for example) over time.

But typically one only makes readings every few months, and the amount of gas consumed will vary from one year to the next depending on the weather.

My approach is both extremely tedious and not very accurate. But I feel it does offer some insight which I hope you will find interesting!

• Firstly, I read the gas meter every weekend and record the readings on a spreadsheet  that calculates my weekly consumption of gas.
• Secondly I calculate the total energy contained in the gas (in joules) and divide it by the time between readings (in seconds) to give the average power (in joules per second or watts)
• Thirdly I look up the average weekly external temperature near my house for the corresponding period. I use data from my own weather station, but you can pick data any nearby station on the Weather Underground’s ‘Wundermap‘..
• Finally I subtract the average external temperature from the average internal temperature which I think is around 18 °C. So if the average external temperature for a week is 2 °C then I record the temperature difference as 16°C. I expect that the gas consumption will be proportional to this figure.

What do the data look like?

Here is the rate at which my house uses gas (average heating rate in heating watts) versus days since the 1st January 2019.

Estimated average heating power due to gas heating in watts. Click for a larger view

And here is the difference of the average weekly external temperature from 18 °C versus days since the 1st January 2019.

Difference between the average weekly external temperature and 18 °C. Click for a larger view

The correlation between these data sets is striking. And it becomes even more striking if one plots both data sets on the same graph:

The data sets from the two data sets above plotted on the same graph. The weather data is referenced to the left hand axis and the gas consumption data is referenced to the right-hand axis. Click for a larger view.

Notice how the weekly rises or falls in the difference from average external temperature are reflected in corresponding increases or decreases in the rate of gas consumption

Looking at the data up until day 250 (August 2019), the two data sets broadly overlap. By comparing the two scales on this graph, this means the house required 6000 W to heat the house 18 °C above ambient, or 333 W per °C above ambient.

This is rather more than the 280 W per °C I estimated previously.

Since then, the gas consumption data fall consistently below the weather data. I believe this is the effect of the triple-glazing which I installed last summer.

I calculated this would improve the thermal performance of the house by about 10% and this data are broadly consistent with that.

What’s next?

I would love to have better data than this: but I don’t. For example, both internal and external temperatures change hourly. The internal temperature is affected by how many people are at home and at what time of day the heating is required. Perhaps the relevant internal temperatures should be 19 °C.

But being to spot – albeit with the eye of faith – a 10 % improvement in building performance is as good as most building engineers would hope for. And this data can be had for free without purchasing any monitoring equipment.

My understanding last year was that about 20% of the building heat loss was through the windows, and the triple-glazing has – roughly – halved that.

External wall insulation (EWI) should tackle the 80% of the building heat loss that goes through the walls.  In principle EWI could cut this by 75% – see the figure below – but I am sceptical that this can be achieved – and I am hoping for a 50% cut in heat loss through the walls. The reason for my scepticism is that I have not included the effects of heat loss through the floors, or through draughts, neither of which I know how to estimate estimate.

If a 50% improvement in heat loss through the walls is achievable then as I plot this data through next winter I should be able to reduce peak demand in the winter to below 2000 W – comfortably within the range of an electrically-powered air-source heat pump.

Operating with a coefficient of performance of 3, this should require an average of just 600 watts of electrical power – which can all be low carbon.

Exciting times…