From Complex Models to Climate Solutions: The Transition Zero Story

Hello, Climate Champions! In today's episode of the Climate Confident Podcast I had the pleasure of hosting Matt Gray, the co-founder and CEO of Transition Zero, a trailblazer in energy systems modelling.

In our conversation, Matt delved into the intricate world of energy systems modelling, a crucial tool for stakeholders and decision-makers in shaping our energy future. He emphasized Transition Zero's mission to democratise this complex tool, making it accessible, auditable, and reproducible. This, Matt believes, is vital for accelerating the transition to a sustainable energy future.

We explored the significant challenges in moving towards net zero, particularly the technical and political barriers. Matt highlighted the crucial role of transmission investments in the energy grid and how these investments, or the lack thereof, influence our ability to harness low-cost renewable energies like wind and solar.

Another key takeaway from our chat was the importance of data transparency in fostering global collaboration. Matt underlined how Transition Zero's commitment to open data and models aims to bridge the gap between pledges and actions in climate commitments, thereby enhancing global climate action.

Matt's insights on the role of transmission in achieving net zero were particularly thought-provoking, revealing how strategic investments can save trillions while facilitating a faster shift to renewable energy sources.

We wrapped up with Matt's thoughts on COP28 and his future plans for Transition Zero. For those keen to learn more about their groundbreaking work or get involved, check out the TransitionZero website.

Check out the video version of this episode on YouTube.

Tune in, get inspired, and let's continue to make strides towards a sustainable future together! Remember, every step counts in our journey to net zero. Let's keep the conversation going – and remember to stay climate confident!

Transcript

Matt Gray: 0:03

We think energy system modeling is foundational to enabling a policy environment that will support a rapid, phase out of fossil fuels, towards renewable energy or carbon free sources of electricity. But for those models to be used and to scale the decisions required within the time that we have, it's essential that those models are used by everyone

Tom Raftery: 0:33

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Climate Confident podcast, the number one podcast showcasing best practices in climate emission reductions and removals, and I'm your host, Tom Raftery. Don't forget to click follow on this podcast in your podcast app of choice to be sure you don't miss any episodes. Hi everyone and welcome to episode 147 of the Climate Confident podcast. My name is Tom Raftery and before we kick off today's show I want to take a quick moment to express my sincere gratitude to all of this podcast's amazing supporters. Your support has been instrumental in keeping this podcast going and I'm really grateful for each and every one of you. If you're not already a supporter I'd like to encourage you to consider joining our community of like minded individuals who are passionate about climate. Supporting the podcast is easy and affordable with options starting as low as just three euros or dollars. That's less than the cost of your latte and your support will make a huge difference in keeping this show going strong. To become a supporter, simply click on the support link in the show notes of this or any episode or visit tinyurl. com slash climatepod. Now, without further ado, with me on the show today, I have my special guest, Matt. Matt? Welcome to the podcast. Would you like to introduce yourself?

Matt Gray: 1:57

Yeah. Thanks Tom, and thanks for, for having me. It's, it's great to be here. So I'm Matt Gray, co-founder and CEO of Transition Zero.

Tom Raftery: 2:06

Okay, and Transition Zero is what Matt?

Matt Gray: 2:10

So Transition zero is a relatively new, not-for-profit. We've been in operation for about two and a half years now. We're based here in London in the UK but we have people in other parts of the world where we develop our models. What we do is we provide energy systems, data, and modeling as a service. And for those listeners who don't know what energy systems modeling is, energy systems modeling is a complex tool that allows a wide range of stakeholders and decision makers to understand the energy system and to make decisions, investment, or policy decisions about how to, prepare for the future. For example, if a government wants to understand the cost of a climate policy, they typically use energy system models. If a, a corporation wants to understand the cost of meeting their net zero targets, they typically use an energy systems model. And if an investor wants to understand where to put wind or solar farms exactly, in a country or a region that they're operating in, they typically use energy systems models. Energy systems models due to their complexity, historically have been quite closed and inaccessible. You need to know or have a, a graduate level understanding of modeling to use them, to interact with them. We are different. So what we're trying to do is create, data sets and models which are accessible, auditable, and reproducible. And the reason we want to do that is because we believe that these tools to accelerate the transition need to be more widely available. And if they are made more widely available, it will hopefully turbocharge the stakeholder engagement process whereby we have more people having a constructive and productive discussion about what the energy system should look like and how quickly we need to move.

Tom Raftery: 4:16

Interesting. Interesting. Before we get into that, you said you're based in London. That's not a strong London accent. I hear there, Matt. That's a, that's a Kiwi accent, right?

Matt Gray: 4:27

Yes, it is originally from New Zealand. Came to the uk. About 15 years ago although it does still feel like yesterday but originally came over, to study. So I got my master's in the University of Manchester, but also to, to work. So I as I came over, I managed to, to get an opportunity, as an intern on a trading desk at one of the major investment banks at the time. So that's that's the reason why I came over to the UK and since then have got married and, and, and had kids. So I'm, I'm, I'm in all likelihood here forever.

Tom Raftery: 5:07

Similar, I'm, I'm, I'm in Spain 15 years, so still haven't picked up the Spanish accent yet either, so

Matt Gray: 5:14

no accents, don't go.

Tom Raftery: 5:16

And we won't talk about the Rugby World Cup

Matt Gray: 5:20

No, please don't.

Tom Raftery: 5:22

Okay. Back to the modeling . So, I mean, you're talking about energy systems modeling and it's, it's, it's quite abstract and, and, and for most people, I, I would've thought. So, for example, you mentioned for people who are investing. If, say a company was trying to justify building a new gas fired power plant, is that something that the, the models would be useful for? Because we hear a lot about things like the carbon bomb or the carbon budget and the fact that we have far too much proven reserves of carbon. And you know, you'd want to be able to say that if someone was building something like that, that its probable lifetime would be a lot shorter and the, the chances of getting return on investment would be low, you'd have to think. So is that something that energy models would be useful for?

Matt Gray: 6:20

Yes, absolutely. And those, those terms carbon bombs, carbon budgets remind me a lot of my old boss, Mark Campanale. So the, the, the genesis of Transition Zero is we, we spun out from the Carbon Tracker Initiative, which is a, a financial think tank. And what we were doing at Carbon Tracker was, we were developing economic models to understand exactly what, what you were talking about. So stranded asset risk for coal and gas fired power plants. We built the models for Europe and America, which went really well because there was lots of data. But then we sort of moved into, as we moved into Asia and in particular China, we found that there was this fundamental lack of data. Which is why we started experimenting with machine learning and computer vision with the use of satellite imagery, was to augment and estimate data points that weren't publicly available. And that's what led to Transition Zero. But, just back to your, back to your question. Yes, absolutely. These models can be used for asset level decisions all the way up to global level decisions. So for instance, at an asset level, you can work out, to what extent your gas or coal fired power plant will be utilized. If it has a lower utilization rate, that's a very good indication that it in all likelihood won't recover its revenues and therefore will become a stranded asset. Right up to the global level. So, for instance, if you are a country that does not have the resources to build out lots of wind and solar, you can work with other countries via interconnectors, which are big cables that cross oceans or vast long areas of, of land to connect electricity systems. So taking advantages, taking advantage of the resources that your neighboring countries have, and all of those decisions can be made with, with, with the energy systems models.

Tom Raftery: 8:29

Okay. And. You said that the models up until now have been quite closed and proprietary and private, and you want to create a model that is open and a standard even that people buy into and everyone starts using. Is that a fair assessment of what you're up to?

Matt Gray: 8:53

Yes, exactly. So we, we think energy system modeling is foundational to enabling a policy environment that will support a rapid, phase out of fossil fuels, towards renewable energy or carbon free sources of electricity. But for those models to be used and to scale the decisions required within the time that we have, it's essential that those models are used by everyone from energy consumers to taxpayers, to policymakers, to investors, and to corporates corporates as well, who to date have been speaking a big game with regards to net zero. If you compare the, the number of pledges with the actual number of credible plans, there's a number of institutions that are doing that, like Net Zero Tracker for instance,. there's a big gap between what companies, investors, and countries are saying they'll do and what they're actually doing on the ground. And we believe one of the reasons for that is this barrier between, the data and the availability of these models. They're simply not being used at the scale that they need to be. And the reason for that is because the, the, they're closed or inaccessible, um, yeah.

Tom Raftery: 10:18

There's a very well known XKCD cartoon about standards and introducing a new standard. You know where it says there are 15 standards, we need one standard to rule them all. And now , then time passes, and now we have 16 standards. So how, how do you avoid that happening? How do you make sure that if you come up with this standard that it's widely, widely adopted?

Matt Gray: 10:49

So, yeah, I mean, that's a really good point. Even within the energy sector, there is a whole host of standards. So, what we are talking about with regards to creating a global standard is, not necessarily, in the conventional sense where you have standards like the greenhouse gas protocol, which, tells everyone but is particularly used by, by corporations as they interact with the renewable energy market what a ton of CO2 represents. What we are trying to do is more, I think, foundational in the sense that within these energy systems models, there's a number of key assumptions. Assumptions around the cost of different power generation technologies. What do they cost? There's assumptions around commodity prices. There's assumptions around, resource potentials. So you have countries which have different levels of resource potential, and that level of resource potential determines how much of a certain fuel they can build. So if it's somewhere like Japan, for instance, where it's mountainous and there's lots of forest area that limits their potential or at least gives the country an understanding of what they can do and the trade-offs around pursuing a sort of solar, predominantly solar electricity system. So what we are trying to do is to make sure that, all stakeholders have a common understanding and rely on a common evidence base with regards to those assumptions. And we believe if we can get buy-in at that level, it will reduce data barriers because as countries, and investors, and corporates, try to meet their net zero targets, they will be trying to understand what the data, is telling them. And they'll need to have an understanding of the assumptions underpinning that data, to make decisions. And just to use an example of, of how we see, the state of standard evolving. So for instance, you have climate finance. And climate finance is all about wealthy company countries giving money to, low income countries to help them phase out fossil fuels and build a zero carbon electricity system. What's happening at the moment is there is, there is no shared understanding or shared evidence base around how much that will cost. I.. And the reason for that is, is the data's closed. The model's closed. So what happens is like reports just get circulated by think tanks saying it costs this much, and then someone will say it costs that much. And what we need to do is just really expose the data and the, the, the assumptions underpinning that data. And that will, we hope, create a level playing field where both sides of, of that, that ledger, so that the countries who need the money and the countries who are giving it, are at the very least, not arguing about data and cost anymore. They're arguing about what they're getting in return. As rich countries give that money, and then low, low income countries use that money. That's what we should be debating. We shouldn't be debating how much this costs because the data is there. It's just not in the hands of the people who are making the decisions.

Tom Raftery: 14:23

Sure. And where is the data coming from that you are using as opposed to the one that the various consultants in their reports are using? And why is yours more trustworthy than theirs?

Matt Gray: 14:36

So our data comes from a variety of sources. So at the, the very fundamental level, we scrape all publicly available data from reputable institutions that we can find on the internet. Typically, that's empirical data. So data around how many coal plants there are, how many gas plants there are, where they located, the size of them, the type of technology that they're using. Then we identify a series of gaps which are affecting the accuracy of our models, and that's where our research team comes in to use machine learning techniques, computer vision techniques, like I discussed in the history of, of Transition Zero. And that allows us to estimate and augment data that doesn't exist. So for instance in some parts of the world, the number of assets that are in an electricity system is, is not known or it's not publicly available. We can come in with computer vision and identify those assets and size them. So for instance, we have algorithms that tell us or that, that identify solar panels and solar farms and tell us the size of those solar farms. We do a similar thing for grid assets such as substations, which are the the assets that convert generation onto the grid. So it reduces the voltage to get it to the consumers. Vitally important assets that are, again, not, not much information on them. And then there's the final step, which is I think our, our, our unique offering. We have in-country analysts. So we develop the product and the technology here in London, but for the markets that we are operating and engaging in, we have in-country analysts who are typically locals who live in the region and they engage with the data and validate the data just to make sure that it is reflecting market constraints, but also what's happening on the ground, which is typically quite different from what is going into these models in the first place.

Tom Raftery: 16:59

Sounds kind of expensive. Mark, how, how is this being funded?

Matt Gray: 17:05

So we're entirely, we're entirely grant funded. So we're a registered charity. What that means is we take grants from big foundations such as Google.org, Bloomberg Philanthropies and a number of other foundations. And we provide that service, for free. So we create public goods which is consistent with our with our mission to, make sure that we're accelerating the transition by creating open data sets and open models that, that are usable for everyone. But in terms of cost actually producing the data isn't the biggest cost for us. I would say over time, the biggest cost is making sure that we get this data in the hands of the right people, at the right time, in the right way. And that's where our in-country analysts are, are so important.

Tom Raftery: 18:02

And what about takeup then? Is, is, is this being Uh, How, how, I mean, you said you're a, a new company, only a couple years old. Where are you in that kind of scale of getting it out and getting it in people's hands to be used?

Matt Gray: 18:18

Yeah, so we're only, we are only getting started. I would say there's, there's two aspects to take up. So where we have an in-country presence at, we know our data is being used already and that you know, that's unsurprising given we have people on the ground engaging with, with stakeholders in the countries that they cover. But we also have a partnership model. So I think I've been involved in a number of data products that have failed to take off, and the reason being that they just haven't, there, there hasn't been much of a focus on user growth and user uptake. So what you, what you're left with is a nice website with great visuals and data sets, but no one actually using it. Wanted to make a, a conscious decision this time round that we were putting the user first and focusing very heavily on the user. So what we mean by a partnership model is we identify initiatives and organizations that are that had the same mission as us. And instead of us working with users, we give the data to those organizations or those initiatives and they interact with the users on our behalf. An example of that is the V20, which is a consortium of climate finance ministers, from countries that are particularly vulnerable to climate change. So low income countries that are based in regions such as the Pacific where you know, sea level rise is going to make them very vulnerable to the worst impacts of, of climate change to, to everywhere else like, Sub-Saharan countries where obviously drought's an issue. Countries like Pakistan, for instance, which has been, you know, having a really hard time with, with floods recently. So that that partnership we have with the V20, we give them our data and our models and that allows them to put together climate prosperity plans. And these climate prosperity plans are then the basis for applications for grants and, loans for, for climate finance, which is what I alluded to previously. And that's a good example, a really good example of our data being used. If we get our data into those countries, it'll mean that 50%, 15% of the global population will be using our data for climate finance. And that is one of our, one of our company objectives over the next couple of years is to make sure that our data and models inform those prosperity plans by 2025.

Tom Raftery: 21:03

Nice. And what are some other kind of key goals that you have?

Matt Gray: 21:09

So we have a, a number of goals. I think the first step for us is to make sure that we have our platform up and running, which we're working towards at the moment. And in, in that context, the platform has three components. So there is what we're calling a results viewer, which will have, key scenarios for over 160 countries. So there will be what we're calling a least cost scenario. So the models just run unconstrained and deliver the least cost outcome for the electricity system. Then we'll have the current policies scenario, which is a scenario that tries to understand what governments are doing at the moment and what sort of outcome that's gonna lead to in the future. And that helps governments and stakeholders understand the, the ambition gap. And then there'll be what we're calling in net zero scenario, so a decarbonized electricity system consistent with the temperature goals in the Paris Agreement. And we'll be providing those three scenarios off the shelf. They'll be available to anyone via an API or a ui. And then there'll be what we're calling the data explorer, which will really go to the heart of what I was talking about around the data standards. So understanding the provenance of data and how the data is influencing the model results. That will, be another component of the platform. And then lastly, we are doing what we're calling the model builder, which will allow anyone regardless of their level of technical expertise, to come onto our platform and to create their own model. To select their own assumptions, to interact with the platform, to understand what they're trying to optimize for. Is it for fossil fuel volatility? Is it for phasing out coal plants? And then be able to run that model in real time, which is something both within the public and private sector that is, is not is not available at the moment. So we're really excited about publishing those, those suites of, of tools in the future.

Tom Raftery: 23:23

Okay. And if you were, I mean the, the goal is to get to net zero, obviously, at, at the very least, really as soon as possible. What are the main barriers do you see to getting

Matt Gray: 23:36

There's a whole host of barriers to, to, to, to be, to be sure. There's, there's technical barriers and then there's political and institutional barriers. So the, the technical barriers as, as far as we can see is governments, corporations and investors will need to make trade offs about what they want to build and when they want to build it. So, for instance, we are releasing a big study at COP 28 in Dubai which will be looking at the role of transmission in becoming net zero. So that's a global study across 160 countries looking at how much transmission needs to be built to deliver a net zero outcome and how much.

Tom Raftery: 24:29

just for clarity's sake, Matt, when you're talking about transition, sorry. Transmission.. You're talking about power lines for getting power from generation to consumption,

Matt Gray: 24:38

The grid. The grid, exactly. And the grid consists of two things. There's the transmission grid, which is the big cables which you, you see sometimes when you're driving down the road. And then there's the distribution grid, which are the, the small cables, which you see when you're walking down the street. That's the, the crudest way of talking about the grid, which is, which is quite a complex topic. But yeah, back to that study. So that study's gonna look at Yeah, how much transmission needs to be built and, and crucially, how much money can governments save if they pursue transmission investments in a manner are consistent with net zero. And the results of that study show that 3 trillion can be saved if those investments are made. But back to my point about trade-offs and decisions, a decision to not invest in the grid is a decision to invest in not only more capacity. So more power, more power plants but also a decision to invest in a different type of capacity too. And what I mean by that is if you don't build out the grid or modernize the grid, you won't be able to take advantage of some of these low cost technologies like wind and solar. You'll have to rely on some of the more traditional carbon free technologies like nuclear, hydro, and biomass for instance. And that, again, is, is a trade off that governments will have to make. And that's something that governments I don't think fully appreciate as we make this transition to net zero. So that's sort of the technical component as far as I can see. And then there's the, the institutional political component, which is currently we're just not moving fast enough. Again, back to back to transmission. On average it takes about 13 years to get transmission lines built. So to go from concept to, having it connected to the grid. Clearly that's not fast enough. If you look at the IEA's Net Zero Scenario, which says a decarbonized electricity grid by 2040, 13 years assuming we start today is nearly, is getting, is getting quite close to, 2040. So we need to really increase our efforts around how we organize markets to get the incentive right and how we, I think, bring the rest of society with us as we make this transition. So one of the main reasons why transmission doesn't get built. It's because of nimbyism. People don't like, some of, don't like looking at the stuff when it's right outside their backyard. So how do we incentivize those people, to want to have those, those, that infrastructure near them. There is a lot of options. You see some really encouraging things in countries like Greece, where if you have a solar plant next to you, you get a share of the revenue. And I think these are the sort of the innovations that we're gonna need to see to bring everyone along with us. And the same applies to this concept of the just transition as well, which is as we transition, there'll be winners and losers. Those who are working for the fossil fuel sector will lose their job. And if we don't create a positive future for them and their careers, that they're instinctively gonna hold up the transition. And that, you know, that is something we can't afford either because we won't be, we won't be aligned with the temperature goals and the Paris agreement.

Tom Raftery: 28:14

Sure, sure. I'd like to dig into a little bit more the point you were making about transmission. So you said we could save up to $3 trillion by increasing transmission. I guess just as a quick 101, why is it important to increase transmission? Is it because we are decentralizing our generation sources? We're using more renewables, so we need more power lines to get to more to more diverse generation sources. And how is that gonna, how is investing in transmission gonna save us $3 trillion?

Matt Gray: 28:49

Yeah, so I, I guess just to, talk about how we, put that study together. It's scenario analysis, which is again, a, a feature of systems modeling. You try and understand or you create constraints within the model to see what that does to the energy system over the future. So the two scenarios that we created, one was the, the, the rapid build out of transmission, to be net zero aligned in a manner consistent with the IEA's Net Zero Scenario, which is complete decarbonization by 2040. The other one was no transmission being built. So it's, it's just contrasting those scenarios. And what we found was the, the cost of electricity in the no transmission scenario was a lot higher than in the scenario where transmission is built out. But to, to answer your question around, why transmission is important there's a, there's a couple of reasons. The first is, our transmission grids have been overlooked, I think for a long time now. So this is aging infrastructure that just hasn't been invested in. Those investments need to be made anyway. And there's a whole host of reasons why those investments haven't been made to date. I think if you think about the investments in electricity over the last decade or so, most of it's been on the generation side. And the reason why investors have targeted generation is, is for a bunch of reasons. So renewable energy levels as a percentage of total power generation have been quite low. So, the IEA says that you don't really need to make grid investments if renewable energy investments, or sorry, if renewable energy generation as a percentage of total generation is below about 5%, you don't need to make any investments in the grid. You can just make simple operational decisions and that will integrate that renewable energy. So that's, that's one reason why people, why governments haven't been investing in the grid. Another reason is, until recently, electricity demand was has been stagnant. So many markets, particularly in OECD markets, so, the US and Europe electricity demand simply hasn't been growing. That's obviously changing with the electrification of other sectors. So electric vehicles and transport and heat pumps and buildings. That's another reason. And then I think within that, we've seen this, the, the rise of battery storage. So battery storage is unique in the sense that it provides a role that allows you to, delay investments in the grid.'cause if you put a storage facility in an electricity system, it'll reduce congestion issues in the grid. And one of the reasons why you want to make investments in the grid is to avoid, avoid those congestion issues. So you're getting the, the supply of electricity to the demand centers. And then lastly, the reason why I think investments in the grid haven't really been happening at scale is because they're regulated monopolies. So,

Tom Raftery: 32:15

hmm.

Matt Gray: 32:17

generation, I think, at least in Europe and a number of parts of the US has been deregulated in the sense that if you're an investor or if you're a corporate, you can, you can, you can invest in and get involved in renewable energy generation. So if, if you are a corporation, you can, sign a power purchase agreement to get a utility to sell you electricity. And you know, the, the, the same applies for investors. You can become an asset manager and, and directly invest in these, in these assets. That deregulation never happened to the grid. I think there's, there's, very good reasons for that. It is because they are large, they're complex, and you don't want many actors tinkering with these things because there'll be brownouts and blackouts, which is obviously politically unacceptable. So I think those are the, those are the reasons why there hasn't been investments in the grid and the reason why grid investments have been, have been overlooked.

Tom Raftery: 33:21

Interesting. Okay, cool, cool. You mentioned you're going to COP in Dubai. What are you expecting to get outta that?

Matt Gray: 33:30

So we want to launch our analysis, which we are really excited about. That analysis we think is coming at, at a really good time. Everyone's talking about the grid and grid investments. There's this big push for a threefold increase in renewable energy. And I think contingent to that, threefold in increase in renewable energy is the need to invest in grids. You won't be able to. buIld out that amount of renewable energy if you don't do that, because there simply won't be a way of connecting that amount of capacity without breaking the, the electric grid. So that's something that we're really excited about and we are, we are looking forward to engaging, with governments with regards to that report.

Tom Raftery: 34:19

Cool. Cool. We're coming towards the end of the podcast now. Matt. Is there any question I haven't asked that you wish I had or any aspect of this we haven't touched on that you think it's important for people to be aware of?

Matt Gray: 34:31

No, I don't think so, other than if you are interested in our work you want to find out more about our analysis or you would like access to our data and tools, then, you know, feel free to to, to get in touch with us at any time.

Tom Raftery: 34:48

Cool. That leads me nicely into my final question, of course, Matt, which is, if people would like to know more about yourself or any of the topics we discussed on the podcast, where would you have me direct them?

Matt Gray: 35:00

Website, LinkedIn, Twitter, or X. You can, you can find us across those social platforms or yeah, just use the old school email if you want to as well.

Tom Raftery: 35:13

Okay, cool. I'll put those links in the show notes, Matt, so everyone has access to them. Thanks and million for coming on the podcast today, Matt. It's been fascinating.

Matt Gray: 35:20

Thanks, Tom. Appreciate it.

Tom Raftery: 35:23

Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about the Climate Confident podcast, feel free to drop me an email to tomraftery at outlook. com or message me on LinkedIn or Twitter. If you like the show, please don't forget to click follow on it in your podcast application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast. It really does help new people to find the show. Thanks. Catch you all next time.