Reflections on energy and housing


Jenny Love, UCL Energy Institute

I’m going to be leaving academia in a couple of months. Aside from my colleagues being able to finally get some peace and quiet and not having their chocolate supplies taxed on regular occasions, there are some other benefits to this. One is that it has made me reflect on what I have learned whilst doing a PhD in energy and housing. Here are four reflections that you may find interesting.

1. We still don’t really understand a lot of factors behind energy use in buildings.

Much of the blame for this can be attributed to a poor evidence base for physical performance of houses. For example, not enough studies have measured energy use and linked it to real measurements of heat loss from the building. Researchers like Virginia Gori, Sofie Pelsmakers and Sam Stamp are working on these actual measurements.

If we don’t understand how energy is used in the first place, this makes knowing the effects of things like retrofit quite difficult to predict. Researchers like Ian Hamilton are using the best data we currently have to assess the effect of energy efficiency measures.

2. Social scientists and physicists/engineers must go further than just collaboration

We have an unfortunate tradition in our field of a lack of respect between physical scientists and social scientists. What I mean by saying we must go further than collaboration is not just working together and bearing with each other – but setting an example of genuine appreciation of the other’s discipline – including stopping dissing each other’s disciplines behind our mutual backs. When I started my PhD I didn’t know much about social science, and therefore used to be quite rude about it. Now I have come to see that it’s the people who bring about the physics in buildings that I like to study. For example, I described here how when houses are retrofitted, the outcome is determined by the amount by which the occupants adjust the heating. Researchers have to understand what made the occupants adjust the heating, and then the effect that this has on energy use.

The best combination of social science and physics in one project I’ve seen is the work Lai Fong Chiu and Bob Lowe‘s Retrofit Insights team are doing, here. As it happens, the two lead authors of this study are married. Now, although this happened before they wrote the study, there’s nothing to say it couldn’t happen the other way round – you never know, multidisciplinary collaboration could lead to love. In my role as Dr. Love I’m happy to point you towards eligible physical or social scientists with whom you could start a multidisciplinary collaboration.

Another person to keep your eye on is Adam Cooper of UCL STEaPP, who is doing great work in starting to develop the theoretical framework within which social science and physics can fit together in order to study energy use.

3. ‘Behaviour Change’, like religion, is (mis)used as an excuse for all kinds of wrongs

What I mean by ‘Behaviour Change’ is trying to get occupants to reduce their energy use by changing their home heating behaviour. This is only beneficial if there is actual evidence that occupants are exhibiting wasteful behaviours in the first place. In my case study sample in social housing, many of them were heating far less than average and trying to get them to turn the heating down would not only be morally wrong but also bad for the house (leading to more mould, etc).

The second problem I have with ‘Behaviour Change’ is that it is sometimes used as a pretend solution in order to avoid the real issue – the fact that our housing stock is among the least thermally efficient in Europe. We need to get on with insulating it, instead of trying to make people colder by using less heating.

I’m certainly not against occupant engagement. Quite the opposite. What I would recommend it looks like is firstly listening to the occupants about how they do use the heating, and then, only if they are up for it, deliver tailored advice which will help them meet their heating needs using less energy. Also. we should be giving advice on wider aspects of maintaining a healthy home, like how to ventilate adequately.

4. Separate energy/climate change policy from warmth policy.

A crude description of the way retrofit policies worked during the time of my PhD is that energy companies ‘offset’ their CO2 emissions by funding retrofit of social housing. There is very little measurement of whether energy or CO2 has actually been saved, but if there were, it would be seen that some occupants do not save energy but have a warmer home instead – in fact, this is what the occupants need. However, this would be counted as essentially a failed policy, even though the occupants now have a better quality of life. Maybe that’s why no one measures the actual savings.

There are two agendas going on here  – allowing people to be warm in their homes, which is very important, and mitigating climate change by reducing energy use, which is also very important but is the opposite to making people warmer. The more you do of one, the less you do of the other: in my mind, the trade-off is like this:

trade off

I think our climate change and energy demand reduction policies should not target
social housing – there are plenty of other places to focus energy demand at. This sector
needs policies measured in terms how much more comfortable the previously-cold
occupants become.


So, there are some thoughts. I invite you to challenge or add to any of them in the
comment section below. As always, feel free to contact me on if you would like to have a more detailed discussion on anything raised above or have any questions about energy and climate change in general.


Becoming Dr. Love: part 3 (does behaviour matter?)

Jenny Love, UCL Energy Institute

Now, I realise that taken out of context the title of this post might be interpreted as, “Dr. Love will now answer your relationship questions”. Please don’t write to me with your relationship problems – I won’t be able to help unless they can be solved by building physics.

The title is actually referring to the implications of the previous post here, about the fact that when dwellings undergo energy efficient retrofit (e.g. insulation, double glazing), the outcome which arises is partly dependent on how the occupant reacts. I found some occupants who kept their home colder afterwards; I found others who for various reasons increased their use of heating and made their home much warmer. I couldn’t have predicted which occupants would do what.

This post is the ‘so what?’ question: does it really matter that occupants react to retrofit in different ways? What effect does this variation in behaviour have on their energy use?

I am going to explain the answer through the medium of cheese.


Now, that’s not entirely helpful in its current form: why this answer, and why the cheese?

  1. A model

When you’re trying to speculate on the value of something you can’t measure, you can use a computer model. For example, I wanted to know what the energy use of a household would be, at all different levels of insulation (a physical variable), and at all different levels of how much the occupants have the heating on (a behavioural variable). I couldn’t go and measure the same house with various different levels of insulation and various different types of behaviour, so I simulated it in a program called EnergyPlus.

  1. The results

After going to all the effort of learning EnergyPlus and working out how to assemble the results on a graph, all of which involved some near-all-nighters, a lot of tea and a significant quantity of Maltesers, I was rather disappointed to see that I had in fact produced….

…a large piece of cheese.

Let me explain. By the way, if you hate graphs, you can at this point skip to the summary.


The cheese shows energy use plotted against heat loss of the building, at different types of occupant heating behaviour. It is marked out by a blue line at the bottom and a red line at the top. The blue line is the relationship between energy use and the leakiness of the house for the situation where the occupants have the heating on as little as is realistic: one hour per day, only at 16 degrees C, only heating one room. If their house is leaky, they end up using more energy, but the relationship is not very steep.

The red line is the situation where the occupants have the heating on as much as possible: 24 hours a day, at 23 degrees C, all rooms of the house. You can see that the relationship is very steep: if the house is leaky, they use a lot more energy.

Since the blue and red lines mark out the extremes, everything within the cheese in between them represents possible energy use at possible types of heating behaviour. The green line in the middle, for example, represents people who have the heating on for 9 hours per day, in some rooms, to 20 degrees C: a sort of medium scenario.

Retrofit is moving from the right of the cheese, to the left. How far you go represents how ‘deep’ the retrofit is – how much more efficient the building is made.

Example 1. Shallow retrofit, no behaviour change

The type of houses I monitored started out where the pink dot is on the picture below. That is, they were very leaky and they weren’t using the heating very much. Let’s say that one of those houses then had the type of retrofit which really occurred on this estate (‘shallow’), and the occupant didn’t change their use of heating at all afterwards. The arrow represents how the house would move through the cheese. You can see that slightly less energy is used after retrofit.

cheese graph shallow no behaviour change

Example 2: shallow retrofit + behaviour change

This time, imagine the occupants do change their use of heating after retrofit. I saw people changing their behaviour in a variety of ways, so this can happen. In this picture it’s taken to the extreme – all possible changes in behaviour are shown.

cheese graph shallow behaviour change

There is a massive variation in energy use after retrofit resulting from this. Energy use could go down or up quite a lot. We might think it’s quite unlikely that after retrofit people use more energy than before, but I saw it happen in my small sample. Furthermore,  when new people move into the house their comfort standards might be a lot higher than the old occupants. I  saw this happen in my sample too, as some of the post-retrofit occupants had a baby and so had put the thermostat to 28 degrees C!

Example 3. Deep retrofit, behaviour change

cheese graph deep behaviour change

This time, imagine the houses start leaky and are made extremely efficient. The same variety of change in occupant heating behaviour – people going from the start point down to the blue line and up to the red line – as in the last graph, is plotted on. But this time, look at what happens to energy use. Whatever the occupants do – however they change their behaviour after retrofit – the resulting variation in energy use is very small. That is, in very efficient houses, whatever the occupants do with the heating doesn’t have much effect on energy use. That means it’s easier to predict the energy use after retrofit, and occupants can live in a warm house and still save energy, without us having to tell them what to do or trying to change their behaviour.


What I am arguing for, through the use of cheese, is that if we only have one chance to retrofit a building, we should do it deeply – put a lot of insulation on, treat all the places it loses heat – as opposed to ‘shallow’ retrofit – what the current policies are leading to in social housing. It is important that energy use decreases after retrofit whatever the behaviour of the occupants who live there through the retrofit, and whatever the behaviour of the the next ones who move in. I did see people increase their use of heating after retrofit, and I also saw new people who moved in and used heating more than the previous ones, and it is important that these actions still result in lower energy use than before.

I hope the cheese made sense to you. Any questions, feel free to ask – although  the invitation to ‘Ask Dr. Love’ applies strictly to energy and buildings…


1. There are many caveats to this work, and in applying the use of a ‘model’ to real buildings. I didn’t go into them here – this is a conceptual argument and not absolute truth.

2. For those who love graphs, you can find a more academic version of this argument here. Not for the faint-hearted.

3. I should say thanks to two very clever people: Tadj Oreszczyn and Andrew Smith (aka my supervisors), for helping me interpret the cheese graph and its five-dimensional counterpart which appears in my thesis.