Dr Lirong Liu
“I want it to feel like an open door, where everyone feels comfortable and welcome to join in.” Dr Lirong Liu, EDI+ Fellow
Energy system models simplify something vast: how energy is produced, moved, paid for and used. We can use them to test what might happen when electricity demand rises, when more renewable power joins the grid, or when households are asked to change how and when they use energy.
But to make any of that work, the modeller has to make choices. How much electricity a household might need. What counts as a secure supply. Where the data is solid, where it is patchy, and where judgement has to fill the gaps.
Those assumptions are never completely neutral. They carry something of the person who made them. Once they are built into a model, they can go on to shape decisions about infrastructure, investment and the route to net zero.
For Dr Lirong Liu, Associate Professor at the University of Surrey’s Centre for Environment and Sustainability, that is why representation matters. She has spent much of her career as the only female modeller in the room. Her centre brings together colleagues from many disciplines, but, as she puts it, “I’m the only one who is using quantitative modelling to support my research here.” In a field where many of the established figures are men, she has rarely needed to be reminded of how few women do what she does.
Where judgement begins
Ask Dr Liu why that matters, and she goes straight to the work itself. Physical laws and equations shape a modelling framework, but as soon as a model is used to answer a real-world question, the modeller has to make choices. The data may be incomplete. The context may be unfamiliar. The answer may depend on what the modeller thinks is reasonable.
“In most cases, we don’t have the accurate data, so we have to assume,” she says. “This could be a good representation of availability, or of people’s energy demand. But this is where the bias could be created.”
One example came through an Energy Modelling for All webinar. Someone who has lived only in the UK may not see access to electricity as a problem. Someone who has only worked in a country that imports its energy may weigh supply, geopolitics and household income differently from someone with another experience.
“We have to make sure the model’s assumptions can reflect diverse households, their actual situation and their future expectations,” Dr Liu explains.
For her, models are more likely to do that when the people building them have lived, studied and worked in different contexts.
Who makes it into the room
The network Dr Liu leads, Energy Modelling for All, began with funding from the UK Energy Research Centre. By the end of its first phase, it had grown to more than 100 members, with around 30 women. But turning membership into attendance was harder. When the first in-person workshop took place, only 12 women were in the room.
Dr Liu is candid about one reason. New to the UK, she scheduled the session during half term, not yet realising what that would mean for people with caring responsibilities.
“I chose a really bad timing,” she says. “It was half term, but to me, I didn’t understand what half term is.”
Online events told a different story. They reached people across disciplines and sectors, and the network was careful not to define itself only as a space for women. Dr Liu wanted it to stay open to everyone, while still encouraging more women to take part.
“We’re not trying to limit all members to be female, because we still want to be an inclusive environment for everyone,” she says. “But we did encourage more women to join.”
The current phase, supported through her EDI+ Fellowship, has been more deliberate. It has put human stories at the centre, including speakers who have taken less direct routes into the UK energy sector. It has also treated the network as something built with its members, not simply delivered to them.
“We need everyone to join this,” she says. “How can we build it in mutual understanding, and help energy modelling better serve society’s future needs?”
The LinkedIn group Dr Liu established for the network has grown to nearly 200 members, and a learning platform now gives people a way in, even if they cannot attend events. But online sessions still draw more people than in-person ones. Travel costs remain a barrier, and Dr Liu sees the network as still under construction rather than already solved.
“It’s better than phase one,” she says, “but I still think there is a long way to go.”
The word that gets in the way
The most surprising finding came through Dr Liu’s interviews with network members. She asked how they felt about the community before taking part and how they felt afterwards. Across different starting points, she heard a similar shift: people who had arrived unsure of their place felt more confident that they belonged. But some of the most revealing conversations were with people who said they had no experience in energy modelling.
“I can feel there is a real change in their confidence level, no matter their starting point,” she says.
People who arrived unsure of their place left more confident that they belonged. But some of the most revealing conversations were with people who said they had no experience in energy modelling.
“What surprised me is the people who classify themselves as having no experience in energy modelling,” she says. “But actually they do. They’re just not very confident.”
One woman worked in energy management, thinking through where a grid operator should invest, where it should expand a substation, and how the costs and revenues of those choices might compare. It was modelling in practice, even if she had never called it that.
“She always said, ‘I’m doing energy management work,’” Dr Liu recalls. “But never used the word modelling.”
Others did something similar. They would say they did not understand modelling, then describe work that sat very close to it. What stopped them was not necessarily the work itself, but whether they felt qualified to claim the word.
“The word ‘modelling’ builds a barrier already,” she says.
That has changed how she thinks about the community. The question is not only how to train new energy modellers. It is also about helping people recognise the modelling knowledge they may already have.
Making the door feel open
The interviews also showed Dr Liu that no single community can meet every need in the same way. Researchers often want collaboration and joint projects. People in industry may be looking for something more immediate: how a model can be used, and what it can help them decide.
That has changed how she thinks about Energy Modelling for All. Sometimes the network needs to bring everyone together. At other times, it may need smaller spaces for people with shared interests, sectors or levels of experience, in what she calls “a merge and then disaggregate process”. The open door still matters, but so does what happens once people are inside.
What she comes back to are the people: the woman who did not realise her work counted, the members who left more confident than they arrived, and her own sense that she cannot build this field alone.
“I don’t think me, myself alone, is enough,” she says.
Dr Liu can see a future where Energy Modelling for All works more closely with established bodies such as the British Institute of Energy Economics, and where inclusion becomes part of the energy modelling conversation rather than an add-on.
“To isolate energy modelling from the wider energy community shouldn’t be the way,” she says. “I should really team up with other organisations.”
Further ahead, she hopes the models themselves will open up too.
“I hope all the modelling will be open access,” she says, “and that modellers are happy to share their framework, their coding and their data.”
For Dr Liu, the ambition is not simply to grow a network. It is to make energy modelling feel less closed, less specialist from the outside, and more honest about the choices beneath its results. Having spent so long as the only modeller in her own building, she wants the field to become somewhere no one has to feel like the only one.