Monday, 6 March 2017

How warm are other people's houses?

We are often advised to save energy by turning down the thermostat. But how low is reasonable? What do other people do? A recent paper in Energy and Buildings uses data from 821 homes for a whole year (2011/2012) to explore this issue [1]. They constructed a model to predict the temperature in our homes based on house age, type and size, household type and income, tenure (owned, private rented, council home or housing association) among other factors. Some of their findings are quite unexpected, at least by me. But I was not surprised that with all these factors in the model they still only managed to account for about 25% of the variation in living room temperatures between homes. If there is one thing I have learnt about home energy it is that no two households are the same.



The study looked at temperatures in the living room in the daytime (defined as 7-10am and 7-10pm because people are most likely to be around at that time) and in bedrooms at night (between 8pm and 8am). For each home they tracked how the temperature varies with the weather outside - generally the colder it is outside the colder inside too, but some homes vary little in the winter and one or two were actually warmest when the weather was at its coldest. In the daytime when it was 5°C outside, living rooms varied from 11.5°C to 26.7°C. The chart below shows the distribution of temperatures.

Variation in living room and bedroom temperatures standardized to 5C outside from [1].
Bedrooms are slightly cooler (mean 18.3°C) compared to living rooms (mean 19.0°C).


Bedrooms are slightly cooler than living rooms. The mean night time temperature for bedrooms (when it was 5°C outside) was 18.3°C. Bedrooms are also more a little more weather dependent, being more cool when the weather outside is cool.

The researchers looked at a range of factors that could influence temperature. Finally they used a model that looks at all the factors together which is a good way to isolate different effects. For example suppose more retired people live in purpose build flats; this method separates the effect of living in the flat from being retired.

Factors relating to the dwelling
Fabric efficiency is very important. The most efficient homes (based on type of walls, roof insulation, window types and so on) were 1.7°C warmer in the living room than the least efficient. This is not surprising because in many cold homes the heating system is not capable of heating the dwelling to a comfortable level even should the residents choose to. I speak from experience, remembering my Victorian house before we had it insulated! However, I am surprised that across the sample of homes, the effect of fabric efficiency was much less pronounced in the bedroom. This suggests that people keep their living rooms warmer if they can, but don't worry so much about bedrooms.

Over and above this effect, purpose built flats tended to be warmer by about 1.5°C in the living room and 1.4°C in the bedroom than in the coldest homes which were detached. Other dwelling types were not significantly different. This might mean that the way the fabric efficiency is calculated does not quite capture all the features whereby flats are different - or maybe it is something to do with the kind of people who live in flats.

Dwelling age is significant, even after fabric has been taken into account. Even more surprisingly, the warmest homes are not the newest. The warmest homes were built 1945-1980; in post 1990 homes the living rooms were 0.5°C cooler. This is very interesting and I suspect it is because the newest homes were less draughty and so felt comfortable at a cooler temperature. Also, in the newest homes there was much less difference in temperature between the living rooms and the bedrooms. This is probably because the better insulated a house is the more even the temperatures tend to be across all the homes.

Temperature model: some factors relating to the dwelling
Feature
Effect on living room
daytime temperature
Effect on bedroom
night time temperature
Moderate efficiency
(E-value 100-499)
-0.9not significant
Least efficient
(E-value >= 500)
-1.7not significant
Purpose built flat+1.5+1.4
Built 1945-1980+1.0+0.9
Post 1990+0.5+0.9
Local authority rented+1.1+0.7
Housing Association+0.4+0.3

Looking at tenure, local authority rented homes were the warmest, then housing association homes. Owner occupied homes and private rented homes were the coolest. This effect is much stronger in the living room than the bedroom. Local authority homes were 1.1°C warmer in the living room and 0.7°C warmer in the bedroom than owner occupied homes. I find this surprising because you would think that people in these sorts of homes would be more frugal with their energy bills. I wonder if in practice this effect is mainly due to blocks of flats where the tenants have little control over their heating. For example I have friends who use to live in a housing association flat that was always tropical! (We found it uncomfortable; they loved it.) District and communal heatings often have a bad press. It is now required that each heat user is metered separately and charged only for their use - where this is practical [2].

Geographical location was not significant - across 9 regions from the North East to the South West standardized temperatures inside the home (at 5°C outside) were much the same. However, this does not mean that actual temperatures were the same. In the South West it is usually a good deal warmer than 5°C!

There were some other factors that seemed to be significant when looked at individually but the effect disappeared when the model was viewed as a whole. Smaller homes tended to be warmer - homes less than 50m2 where warmer by 0.7°C in the living room and 0.2°C in the bedroom.

Homes with communal heating were on average much warmer than other heating systems - by 5°C. However as there were only five examples of these heating systems in the sample of 821 this result is not necessarily representative. The researchers did not include this in their model.


Factors relating to the household
Most surprising, to my mind, income was not a significant factor for temperatures in either the living room or the bedroom. However, there were some differences between household types.
  • Couples kept their homes warmer than single people
  • Older couples and retired people kept their homes warmer, especially their living rooms
  • Unemployed people kept their living rooms cooler
Temperature model: some actors relating to the household
Feature
Effect on living room
daytime temperature
Effect on bedroom
night time temperature
Couple under 60+1.4+1.2
Couple over 60+1.4+1.0
Retired+1.0+0.6
Unemployed-1.3not significant

Again there were some factors that looked interesting but were not significant in the combined model. For example, households in receipt of benefits had cooler homes on average, but this effect disappeared when looked at with other factors such as household composition and dwelling type. Also households in fuel poverty under the old definition (needing to spend more than 10% of their income on fuel) had cooler homes and this time the effect was more pronounced in the bedroom: living rooms were 0.7°C cooler and bedrooms 1.2°C cooler.

As we transition to low carbon heating, our new heating systems need to take our varied requirements into account. For example, air source heat pumps typically have slow response times and are less efficient in very cold weather. If residents find them inadequate and resort to backup electric heaters this will increase demand substantially on winter evenings which is peak time - the worst possible outcome for our electricity infrastructure. On the other hand if they use wood stoves for backup heat then this is potentially bad for air quality (see Will air pollution from biomass heating damage our health). This is why I am beginning to think that hybrid heat pump systems which also have a gas heating component might be a good idea.

[1] Old and Cold? Findings on the determinants of indoor temperatures in English dwellings during cold conditions. I.G. Hamilton, A.O'Sullivan, G. Huebner, T. Oreszcyzn, D. Shipworth, A. Summerfield, M. Davies. Energy and Buildings volume 13 April 2017
[2] The heat network regulations; What landlords need to do (Out-law.com) March 2015

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