## External Wall Insulation: How well does it work?

Be Constructive will probably finish my External Wall Insulation (EWI) in just a day or two, but I am already trying to see its effect, even as they apply the last coats of render.

So “How well does it work?”

I won’t have a definitive answer until later in the winter, but this article describes the procedures I am using and you can look at the preliminary data and come to your own – preliminary – conclusions.

The data

To work out how well the EWI is working I measure two things:

• the difference between external and internal temperatures, and
• the amount of gas I use each day or each week.

For the last two years I have done this weekly – even I find it too tedious to read the gas meter every day!

But a few weeks ago – in the same week as the EWI work started – I switched to using a ‘smart meter’ and this allows me to download a spreadsheet with daily gas (and electricity) consumption. So now I can work with either daily or weekly averages of gas consumption.

I can then get either the daily or weekly average temperatures from the weather station I have in my back garden. If you don’t have a weather station in your garden then you can use data from nearby stations on the Weather Underground (Link: Zoom in to find weather stations near you).

So how do I use the daily and weekly data to estimate how well the EWI is working?

Weekly data

The graphs below are complex so I will describe each element in turn.

We start with my average daily gas consumption (blue squares) since November 2018. I have averaged the data over 5 weeks to remove anomalously cold or warm weeks. This makes it easier to view the general trend of the data.

My average daily gas consumption (in kWh/day) over the last two years. Click for a larger version and see the text for details.

The data are plotted versus days since the start of 2019, and several events which I think might have affected gas consumption are shown in pink.

• Triple Glazing of most windows.
• Installation of a chimney sheep.
• Triple Glazing of remaining windows.
• External Wall Insulation (EWI).

Notice that in the summers, gas consumption falls to around 5 kWh/day due to water heating and cooking, but that increases in the winter to as high as 100 kWh/day. It is the temperature-dependent part of this consumption that I think is related to the effectiveness of the insulation in the house.

Next we have a graph of the difference between the internal temperature (nominally 19 °C) and the average weekly external temperature over the same period. This is the ‘demand’ to which the gas central heating responds. Again, I have averaged the data over 5 weeks.

This data is plotted (green circles) on the same graph as the gas data, but should be read against the right-hand axis. Plotting the data in this way shows that the gas consumption is obviously related to external temperature.

Average daily gas consumption (in kWh) over the last two years in blue plotted against the left-hand axis and the difference of the average external temperature from 19 °C in green plotted against the right-hand axis. Click for a larger version and see the text for details.

It’s clear from the similarities between the two curves that the variation in winter gas consumption is due to the external temperature. I mention this extremely obvious fact because I was personally surprised by how similar the two curves were.

Model

My model of my house tries to predict the gas consumption based on knowledge of the weather, and a single parameter that describes all the ways that heat flows out of the house. This parameter tells me how many watts of heating power I need to keep the house 1 °C above the outside temperature. In case you are interested, the equations which summarise this are given in the figure below.

The mathematical model – in case you care. In the green background the heating power is expressed in kWh/day and in the blue background the heating power is expressed in W. Click for a larger version.

Initially I matched the model to the data using what is known in statistics as “the null hypothesis“i.e. I assume that nothing I have done has made any difference. So:

• I adjusted the heat loss parameter of the model to match the data in the middle of the winter of 2018-2019.
• The best fit is made by assuming I use roughly 280 W of gas heating for each °C that the external temperature fell below 19 °C. (That’s 6.7 kWh per day per °C)

The red dotted line (- – – ) shows the modelled gas consumption assuming that nothing I have done has made any difference. Click for a larger view.

With this assumption, it is clear that the model overestimates the gas consumption in subsequent winters: so it looks like the actions I took did have some effect i.e. the same demand has led to lower gas consumption. Phew.

To estimate how big an effect I modified the model so that the effectiveness of the insulation could be changed at two points: day 244 and day 657 shown as vertical pink lines in the graph below.

The red dotted line (- – – ) shows the modelled gas consumption assuming that the thermal performance of the house has improved from 280 W/°C in winter 2018/2019 to 240 W/°C in winter 2019/2020, to 134 W/°C in the current winter 2020/21 . Click for a larger view.

• For the first section I assumed that I needed to use 280 W of gas heating for each °C that the external temperature fell below 19 °C.
• For the second section I assumed that I needed to use only 240 W of gas heating for each °C that the external temperature fell below 19 °C – about 15% less.
• For the final section – i.e. currently – I anticipate that I will need to use only 134 W of gas heating for each °C that the external temperature falls below 19 °C.

You can see that in the current winter (day 650 onwards) there is not yet enough data to say which value of heat loss parameter will best match the data.

Looking at previous years, the model does not match the data well in spring and summer – so I don’t feel I can definitively estimate the heat loss parameter until winter is fully upon us.

But the estimate of 134 W/°C – less than half what it was two years ago – does not (at this stage) look unreasonable.

Daily Data

I can apply the same model to the smart-meter data that I download from EDF which gives me my daily gas consumption. I can then compare this directly with the daily average temperature.

I expect this daily data to show added variability when compared to the weekly-averaged data because:

• The ‘constant term’ – in my case roughly 200 W or 4.8 kWh per day – due to use of gas for cooking and heating water may look constant when averaged over 5 weeks. But it likely fluctuates from day-to day depending how much cooking or hot water is used.
• In the short term, heat can be stored and released from the fabric of the building.
• During the EWI works, there have been many days during which doors were open.

Also I must confess to a metrological faux pas in this article by using two units to describe the effectiveness of the insulation: watts and kilowatt hours per day (kWh/day). Both are valid choices, but I will make penance for having used mixed units by showing graphs below in both sets of units!

With these caveats in mind, let’s look at the data.

Daily gas consumption in kWh/day (left-hand axis) and temperature demand (right-hand axis). The straight lines show weekly averages. Click for a larger version.

Daily gas consumption in terms of average power (left-hand axis) and temperature demand (right-hand axis). The straight lines show weekly averages. Click for a larger version.

Notice the strong day-to-day correlation between gas consumption and average external temperature deficit.

I guess it is this strong correlation that allows gas supply companies to order the correct amount of gas in advance.

But the day-to-day data have oddities. For example, on some days the gas consumption seems anomalously low (e.g. days 298, 304 and 307), and on others anomalously high (e.g. days 294, 310).

Bearing these anomalies in mind we can divide the gas consumption data by the temperature deficit data to give the gas power per °C of ‘demand’. These graphs are shown below.

Gas power (in kWh/day) per °C of demand. The straight lines show weekly averages and the double line (===) shows the running average (±3 days). The dotted red line (– – – ) shows the level I hope to achieve. Click for a larger version.

Gas power (in W) per °C of demand. The straight lines show weekly averages and the double line (===) shows the running average (±3 days). The dotted red line (– – – ) shows the level I hope to achieve. Click for a larger version.

The daily data show too much variability to allow easy interpretation. But looking at the running average and the week-to-week data it looks like there is a trend downwards towards improved thermal performance over the course of the EWI works

However there are considerable uncertainties.

• These data take no account of the non-thermal use of gas.
• For example, heating 50 litres of water a day from 10 °C to 50 °C would use 2.3 kWh/day, the energy of which would substantially go down the drain
• Similarly, at these low power levels, I should probably be taking account of:
• The roughly 11 kWh/day of electrical power that we consume.
• The roughly 4 kWh of heating provided by the warm bodies of myself and my wife.

So…

So it will take time before I can definitively evaluate the effect of the EWI. But by spring 2021, I suspect that I will have stared at the data long enough that the best way to analyse the data will have become clear to me. I hope so!

The reason it matters is that next year I plan to stop using the gas boiler altogether and switch to using an air source heat pump. Before spending yet more money on that I am keen to try to anticipate the likely demand so I can pick the right model!

Meanwhile, I am positively enjoying the EWI. I don’t know if this is a psychological effect of spending large amounts of money on something – or a genuine sensation caused by a more stable temperature and – I think – reduced air leakage.

And although still clad in scaffolding, the house itself is beginning to look rather smart. I’ll be sure to post some pictures when the Be Constructive team have left.

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### 5 Responses to “External Wall Insulation: How well does it work?”

1. Ross Mason Says:

“I don’t know if this is a psychological effect of spending large amounts of money on something”.
The placebo effect. Big blue pills are better than small red ones. If you paint your house blue, then you will feel even better….or was it big red ones are better than small blue ones….Check it out – repaint the house next summer!

2. Ross Mason Says:

Ah ha!! Then you will be mellow!

3. Bart Hommels Says:

Hi, great blog posts about your EWI project, and I much like the one on estimating the natural ventilation and infiltration rate using CO2 meters. I had not thought about that one yet.

I think airtightness is the big clue why your insulation “overperforms”. it could well be that the application of the EWI layer has improved the airtightness, most likely in the floor void areas where generally the pointing of the masonry is poor. It would be interesting to repeat the CO2 measurement after the EWI works have completed.

Another proxy for airtightness would be to look a the correlation between outdoor wind speed and the over/underestimation of gas use wrt your thermal model.

And even though it is a nightmare to retrofit, I can really recommend MVHR, even if the airtightness is not below the 3 ACH@50Pa required to make it cost effective.

Although my EWI does not cover the front of the house yet, it has reduced the heat demand to 30% of its original value, which is extremely satisfying to see. Another welcome consequence of the EWI causing the brick walls to sit within the thermal envelope is that the house only warms up very slowly during a heatwave, so in a sense it is both attacking the cause as well as the consequences of global warming.

Hope the new year will bring you only small indoor temperature variations.

• protonsforbreakfast Says:

Bart Hommels,