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[00:01:21] Olivier Corradi: For me, I’ve always had this thesis that if we provided a single platform that could tell anyone, when should I consume electricity, how should I electrify? Then we’re basically doing the best we can to fix climate change.
[00:00:28] Tom Garrison: Hi, and welcome to the InTechnology podcast. I’m your host Tom Garrison, and with me is my co-host Camille Morhardt. And today our guest is Olivier Corradi. He’s founder and CEO of Electricity Maps, which has the mission to organize the world’s electricity data in order to drive the transition towards a truly decarbonized electricity system. He’s a tech entrepreneur, data scientist, and software engineer with a background in math, statistics and software development working at the intersection of machine learning and climate change.
So welcome to the podcast, Olivier.
[00:01:06] Olivier Corradi: Thank you for having me.
[00:01 :08] Tom Garrison: So in the introduction there, I talked about this whole idea of decarbonization and electricity maps and so forth. So why don’t we just start with the basics. What is an electricity map and how can you use it?
[00:01:21] Olivier Corradi: So electricity maps, as the name hints at, is a big data platform that showcases visually where the electricity comes from at every place on the world and how much carbon is emitted on the process. So the question that we’re answering really is to say, “when you are using electricity at a particular time in a particular place, where did it physically come from? and what are the carbon emissions associated to your consumption at that moment?”
[00:01:51] Tom Garrison: And what kind of level of granularity are you talking about?
[00:01:53] Olivier Corradi: So it really depends on the data availability, because the platform is open sourced. So we have this community of developers that are helping us source the data from all different places. We’re processing it and then afterwards it gets into the platform and serves to our users and customers.
So in some places, the data availability unfortunately doesn’t enable us to have very, very fine grain data. But in other places, we can go down to like the state level, the regional level, and hopefully very soon to the city level, as well.
[00:02:26] Camille Morhardt: Are you putting it together based on like a grid output? Electricity grid output, or based on a city or a country granularity?
[00:02:33] Olivier Corradi: Yeah, so there’s always a trade off we have to make because for some users, we wanna make sure we represent the grid as accurately as possible. And so we’re following the physical boundaries. The electrons do not know what state they’re in or what country they are in, but for some use cases we actually wanna showcase in this, play the data in some more intuitive manner, and therefore we have to group it by states or by other dimensions. But at the core, we’re following grids, you are correct.
[00:02:58] Tom Garrison: I guess an example, Camille and I are both in Oregon, and so we’ll just use Oregon as an example. So we could pull up an electricity map and we could see at any point during the day, real-time information about Bonneville Power. So Bonneville Power, are they getting their electricity from hydroelectric at this point? or maybe from Eastern Oregon where they’re getting wind powe? or maybe it’s, I don’t know, what their non-green power is. But we would know at any given point in the day where that electricity was coming from, how it was being generated?
[00:03:35] Olivier Corradi: Yeah. So I really encourage everyone to go and and explore and play around with the tool and electricity maps, because what you can see is when you click on a particular area, you can then see through a graph how much of the electricity is being produced locally and what these sources are–you know, could be hydro, could be called, could be gas, could be other things.
It also looks at what are the imports and exports of electricity, because at a particular place, you can either produce as electricity locally or you can get it from neighboring areas, right? And these neighboring areas can also get it from other neighboring areas. We can get back to sort of the technical aspects after, but you can see all this in the map and then all of these sources mixed together. And if you look at the mix of electricity, you can derive from it the carbon emissions that you would cause, essentially, by consuming electricity at a particular time in a particular area.
[00:04:29] Camille Morhardt: Are you applying this in a kind of predictive kind of matter, so that you can presume which way, which kind of utilization is kicking in at any time for the resource?
[00:04:38] Olivier Corradi: Yeah, so some of our customers are using it for granular carbon accounting, so we’re looking at the historical information in order to make sense of “what are my carbon emissions from the electricity usage of my data centers or my factories, or other things?” But you are correct. We also have a predictive element to it.
My vision is that, you know, if we want to truly decarbonize the electricity, we will need to make sure that we can use low carbon energy sources everywhere at all times. And right now intermittency problems of wind and solar means that we need to figure out what we do when the wind is not blowing or the sun is not shining. And so if your dishwasher, for example, it’s playing its part by getting a signal that, you know, in a couple of hours there’s gonna be wind, but right now there’s none. So maybe it should actually wait a couple of hours before it schedules itself. And if we could get that automation level built into any flexible device or appliance, we would really be helping out the grid to deal with this fluctuation of renewable electric.
[00:05:42] Tom Garrison: Do you also envision, I’m, I’m just envisioning like a commercial user, so you’ve got a big company, it’s got lots of employees or whatever else. It’s not like a dishwasher that can say, “well, I’ll, I’ll just do my work in two hours when there’s wind.”
You said before you’re using the information now just to do accounting sort of in the rear view mirror. Where did the electricity that we used come from? That makes sense.
The future use-case, though, do you see like batteries being used? The batteries during non-wind generation or sun, whatever, you rely on batteries and then when you do have sun and wind, you charge the batteries. Is that kind of part of your vision or no?
[00:06:25] Olivier Corradi: Yeah, absolutely. I mean, you could think a lot of assets that actually exhibit flexibility. And you know, the dishwasher is one of the types of assets that exhibit some flexibility. It doesn’t consume a lot of electricity. So if you look at more impactful use cases such as, you know, grid connected batteries, for example, then obviously you’re gonna step into the next level of actionability on the grid and you’re gonna help the grid on a different level.
Now an example that I like to showcase as well is, look at data centers. Data centers use so much electricity globally, and they have some flexibility. There’s so many AI jobs that are trained and require so much electricity. These jobs can be scheduled with some flexibility. And so if your data center is starting to use electricity at the right time, at the right place, what you’re doing essentially is having sort of a virtual battery because you’re avoiding to use electricity a particular time, and you’re displacing that amount of electricity usage to a different time.
So in a sense, you’re actually storing that electricity in a virtual sense.
[00:07:29] Camille Morhardt: Are you working with data center companies or cloud service providers? If so, how are they actual connecting in to collect the information, so that they can then orchestrate and manage the data center usage?
[00:07:43] Olivier Corradi: Yeah. So the, the public example that I can share here is that Google, since a couple of years now already is orchestrating their data centers by receiving the forecast that we’re producing about how clean the grids are gonna be in the next couple of hours. And then they’re shifting that computation both in time–so they’re may be delaying it or, or moving it ahead of time to match the times at which the electricity is the cleanest–but they’re also doing it spatially now; so it means that if, for example, the wind is blowing in a different place than where the data center is currently located, t hey will move the job to a different data center, which currently has green electricity in order to lower the carbon footprint. So this is already happening right now as we speak.
[00:08:24] Camille Morhardt: And you provide API hooks, or how’s that actual connection happen on the back end?
[00:08:29] Olivier Corradi: Yeah, absolutely. We have a machine learning systems that are continuously making predictions of the whole grid and making all of this information available through an API that any consumer really, or and customer of ours can use to schedule loads more intelligently.
[00:08:46] Camille Morhardt: One thing I noticed when I was looking at your map is France is very green, especially in comparison with some of the neighboring countries. And it made me wonder, so if a company owns a data center but they locate a data center outside of the country where the headquarters are, where does that data center’s usage get counted? Does it go by the company, or by the location of the actual server?
[00:09:09] Olivier Corradi: Our methodology is always to follow the physical flows of the system because in the end we wanna make sure that any action that is taken is reflected in real world atmospheric emissions. And therefore we’re looking at the actual location of the data center and you know what wires are bringing electricity to that data center. So you know, a company like Google might be headquartered in Silicon Valley, still has data centers connected to a certain grids in France or in Denmark or in any other place. And that’s the point of reference we’re using.
[00:09:40] Camille Morhardt: Is there any kind of paradox happening where because people have incentives to move data centers where there is more renewable energy, that then were seeing all of that migration and now those areas are looking less renewable than they did before—just because you can’t use renewable energy 100% of the time?
[00:10:01] Olivier Corradi: That is why it is so critical to actually look at a granular accounting of your electricity. If you were to look at the decision of where do I position my data centers, you want to position them in countries or in locations that can provide low carbon electricity every hour of the year, or at least all the hours where your data center is gonna operate. Right? And there’s a couple of different winning strategies for this. Either you’re looking at, you know, nuclear countries–they have low carbon electricity year round, so to speak; you can look at hydro countries, like Norway is a great example–they have 99% hydro, no, no intermittency; or you look at countries that have a combination with renewables. Denmark is not too bad actually, to that regard, because what they’re doing is to have a lot of renewables, but during the times where there’s no wind, they will actually import from Sweden and Norway who have nuclear and hydro.
So you have these different winning combinations. And to be honest, we often get a little bit in the crossfire between the two religious sides–you know, nuclear or renewables; and we basically try to give a bit this factual basis. But you have to take into account all these things if you want to figure out where do I put my data center in the next couple of years.
[00:11:09] Camille Morhardt: What made you start the company?
[00:12:57] Olivier Corradi: So I’ve been in the tech industry for, for a while, and seven years ago climate change really, really caught my eye and I started reading everything I could about the state of the world and how bad of a future situation we’re potentially leaving our children.
And really from first principles, when I looked at where greenhouse gas emissions come from, I realized most of them come from the energy system and in the energy system, the solution that we basically have is to electrify most of things. We’re even talking electric planes, electric heating, and so on. Hydrogen is a big topic, as well.
We just have to remember, it’s not good enough if we just electrify. We need to electrify and make sure the electricity we use is clean. Cuz right now still the majority of the electricity in the world is not coming from low carbon sources. So in the end, for me, I’ve always had this thesis that if we provided a single platform, trusted data, that could tell anyone where should I put my money and when should I consume electricity? How should I electrify? Then we’re basically doing the best we can to fix climate change.
[00:12:19] Tom Garrison: How do the power generators feel about this kind of information? Do they readily share the data or is this something that is really difficult for you guys to get?
[00:12:28] Olivier Corradi: Yeah, so the data availability and accessibility is an interesting topic. At the core, what we have to remember is that, the power system, as an industry, is an older industry than we’d like to think.
Uh, you know, it’s assets that have been running for a very long time. There is of course the exception of the newer assets that put in wind turbines and so on. The newer assets, they are monitored because they’re equipped with all the new IOT and digital infrastructure; but the older assets, they’re not as well equipped, and so that means that the heterogeneity on the data that we get is very, very different. So that’s one of the reasons why we sometimes don’t always have perfect data. The other reason is that the market operators are, you know, also responsible often for the stability of the electricity grid; if you make available all of the underlying data of the grid, you might have market participants who might bid differently in sort of cheats on the market itself.
So there is a sensitivity to the data and there’s a limit on how granular these data providers, generators, market operators and so on, are willing to share openly about the system itself. But I mean at the scales where we’re operating at– hours to days ahead–there is a general consensus that the more the demand side can help play this flexibility role, the better it is for the electricity grid because it just lowers the need for dirty power systems to go online or the need to install more batteries on the system.
[00:13:57] Camille Morhardt: What is sort of the big next step for you or the next major evolution required to kinda get your platform to the next level?
[00:14:05] Olivier Corradi: To me, the biggest bottleneck is actually about incentives. I mean, if the right incentives are in place, then you know, industries can be disrupted and change very, very rapidly. And what we are seeing right now is that there is not enough incentives to actually start accounting for your electricity usage at an hourly level, and that is really caused by the way that the whole carbon accounting space is wired together.
Right now, most companies are measuring their carbon footprint at a yearly level. They’re not looking at what time did I particularly use the electricity? and where did it come from? Did I use it during the night when there was no sun? Or did I use it during the day when there was sun? And if these incentives start being put into place, then you see a whole range of use cases that start appearing.
You know, we mentioned the dishwashers, the data centers and so on. But if these incentives furthermore gets priced in the market such as the electricity price truly becomes, you know, much cheaper at the times where the green electricity is present, then you have the ultimate win-win scenario for most companies, which is by exhibiting flexibility, I lower my cost and I help the environment. That’s ultimately where we wanna be. So there’s still a little bit of a hurdle on the regulatory side of things to get us there, but it is.
[00:15:19] Tom Garrison: You mentioned something there that when the energy is the cheapest, implying that that’s when it’s greenest; but isn’t that the opposite of the truth? Isn’t the greenest electricity right now some of the more expensive energy there is?
[00:15:34] Olivier Corradi: So it really depends. I mean, and, and it gets tricky to formulate a general answer there, but in many of the places where there’s a large share of renewable energy that penetrates the market–wind and solar–we typically see that there’s a higher correlation between the price and the footprint of the grid. And the reason is that wind and solar, once installed, and when the wind is blowing and when the sun is shining, these are some of the lowest cost marginal cost technologies around. Um, if you have to shove, you know, a bit more coal into a coal power plant, first of all, you’re gonna pay the fuel price. That doesn’t happen with the wind turbine.
So in most places where you have wind and solar at the moment where the wind is producing or the solar is producing, then you tend to have cheaper prices on the system. And there’s, of course, always exceptions, but this is a little bit a generalized case that I’m highlighting.
[00:16:24] Tom Garrison: Where are we at with accounting? So you, you said, you know, companies use this for his sort of historical purposes. Where did my electricity that I burn come from in their carbon accounting? Where is the industry in general? And I’m thinking about our listeners here who are probably trying to figure out like, “how should my company be acting right now? and what sort of state of the art when it comes to accounting?”
[00:16:48] Olivier Corradi: Yeah, so I would say that current accounting principles are facing two big challenges right now that most companies should be aware of in order to be future proof; and both challenges actually revolve around a credibility issue. So the first thing is, in current accounting principles, you can claim that your electricity origin can come from a grid which is disconnected physically because you could procure electricity from an island, and then you can be on the mainland and use that. So the disconnect between the procurement activity and the physical electrons moving on the grid creates a little bit of a credibility problem. You have the same thing in time where you can buy electricity from a solar farm and then you can consume it in the data center during the night.
So these two credibility problems are things that are trying to be addressed, reconsidered right now in the Greenhouse Gas Protocol, which is the instance, which is, you know, setting up these rules for how you’re doing accounting. And so we are really motivating all companies to start thinking about these things. We wrote a guide on our website that tries to highlight how you are counting the benefits of your procurement and how you are counting where your electricity comes from, because these are two different sets of problems.
And without getting into it too much detail here, we are looking at a revolution or change of paradigm in the way that we’re taking action and counting electricity for a company. So if anyone has any questions, I’m also very happy always to jump on a call and, and help educate a little bit around this extremely complicated topic.
[00:18:20] Camille Morhardt: Are they global standards or global accounting, or is that vary by country?
[00:18:24] Olivier Corradi: So there are global standards, and we’re seeing more and more now countries point to these global standards. Hence why it is so crucially important that these global standards are done correctly.
[00:18:36] Tom Garrison: Where are we at in the maturity curve here? Like how many companies are using the kind of information that you provide? are changing their behaviors? Is this very much in the infancy stage or are there companies that are pretty mature in this line of thinking?
[00:18:52] Olivier Corradi: We’re not as far as I would want us to be. Uh, we are still, I think, in the early stages, specifically because the regulation hasn’t completely caught up. Right now, we have the early adopters, a bunch of customers that are using our signals to charge an electric vehicles at the right time. Some of them are starting to do their carbon accounting, and this is starting to push a little bit on the regulatory side of things.
The rules on how you can claim the greenness of the hydrogen you’re using to store electricity, all these things are up in the air, and I think as soon as this will have been settled, then we can get into, you know, the bulk of the growth that will happen after. So I still think we’re early, but I think it is happening now and it’s happening very soon.
[00:19:35] Tom Garrison: Well, Olivier, this is a real thinker of a topic where it gets you thinking about, “geez, uh, that’s really interesting data that I never knew I needed, but now I know I need it.”
So thanks for coming in and sharing electricity maps with Camille and I. It was a really interesting.
[00:19:52] Olivier Corradi: Thank you. It was a pleasure to join.
