How Electric Utilities Will Handle Booming AI Datacenter Demand

So you could have this great situation that because AI is a desirable activity, because it's profitable in many respects, that big tech ends up accelerating the energy capacity build out, maybe they even start building more green technology capabilities in

an ideal world. But then you have the polar opposite scenario where you need all this power to develop this technology there isn't enough and it's sort of a race to the bottom where you have tech companies just trying to get energy wherever they can, maybe they even start using coal and things like that. So it feels like there's two very different paths that we could be going down here.

how much are we really talking about here. We know the you know, the tech company is highly aware of it. There was a headline recently about Microsoft maybe wanting to do something with on site nuclear development. They also, you know, they did do something.

going to be speaking with Brian Janis. He is the co founder and chief strategy officer at Cloverleaf Infrastructure, a power development company that works closely with utilities on solving this problem. So, Brian, thank you so much for coming on out lots.

And the person that was recruiting me said, Hey, I think there is something to this, this whole cloud thing, and I think energy is going to start to be pretty central to what we're doing as a company. And you'll fast forward a decade and I remember having a conversation before I left the company. I was talking to the head of corporate strategy and he said to me, He's like, I don't think people quite realize the degree to which Microsoft is really just an energy company. We

need power and we need silicon. We need chips. That's it, that's the business. If we don't have one of those two things, we're in a lot of trouble and so it was it was remarkable to see the shift over that decade plus of maybe one or two people at the company starting to think that energy might be important to us, when day to energy is actually absolutely central to everything the business does.

of the first cloud data centers. It really was about being close to the network, and so that was the driver of strategically, where do you put data centers, Well, you put them where the biggest network cubs are. So that's why we have lots of data centers in Northern Virginia. That's why we have lots of data centers in Amsterdam. Everyone was chasing network. Probably middle of last decade, there was a shift and it started to go, actually, we

want to be close to eyeballs. So this started a sort of a land grab of all the cloud data centers starting to build lots of new data SISIs new countries because they wanted to be close to where the customers were. And so from about fall of twenty nineteen through probably spring of twenty twenty two, I think Microsoft added was adding close to a region a month in terms of new data center regions they were establishing around

the world. And then in mid twenty twenty two that's when the realization started to sink in that wait a minute, this whole game is about power, because that's when we were first starting to hear rumblings of what open aye was working on and the scale of what chat gp T three was going to be, which was sort of the first big release where everyone was like, wait a minute, this is this is kind of a big deal what

AI is doing and how fast it's moving. And then when we had that release of chat gpt T three in the fall of twenty two, and then shortly thereafter, three point five was released, and there was a massive increase in capability in that release if you recall, you know, in terms of what it could do on you know, getting scores on various tests and things. And it was that moment that I realized, this technology is moving way

faster than the utility industry is moving. If we can make this much improvement in this technology in a six month time horizon, we're in a lot of trouble because the power industry does not move that fast.

commercialization or sort of making easy in public CHATJEP. When it became chat GPT, they're like, oh, this is serious, and then we sell everyone rushing to buy in video chips and all these vcs pivoting to AI, et cetera. So talk to us about like the math there. It feels like there has been this sort of level shift up in sort of expectations of data center demand growth basically as a function of all of the excitement for AI.

mean you probably remember when when that was released. I mean it it really sort of surprised everyone, and it became this thing where suddenly, even though we sort of knew what we were working on, it wasn't until you sort of put it out into the world that you

realize maybe what you've created. And I mean that's where we realized we are we are running up this curve of capability a lot faster than we thought, uh, and the a number of applications that are getting built on this, in the number of different ways that it's being used,

and how it's just become sort of common parlance. I mean, everyone knows what chat GPG three is, and no one what it was the month before that, right, So there there as a bit of a I think of a surprise in terms of just how quickly it was going to capture, you know, the collective consciousness and then you know, obviously lead to everything that's sort of being created as

a result. And so we just we just moved up that curve so quickly, and I think that's that's where the industry maybe got you know, certainly the utilities were behind because as you may have seen there, a lot of them are starting to restate their load growth expectations and that was something that was not happening right before that.

And so we've had massive changes just in the last two years of how utilities are one of the number cap So you know, if you take a look at a utility like Dominion in Virginia, so that's the largest concentration of data centers in the United States, so they're pretty good representative of what's happening. If you go back to twenty twenty one, they were forecasting load growth over a period of fifteen years of just a few percent.

I mean it was about it was single digit growth over that entire period, so not yearly growth, but over fifteen years, single digit growth. By twenty twenty three, they were forecasting to grow two x over fifteen years. Wow. Now keep in mind this is electric utility. They do

ten year planning cycles. So because they have very long lead times for equipment, for getting rights of way for transmission lines, they aren't companies that easily respond to a two x order of magnitude, you know, growth change over

a period of fifteen years. I mean that is a that is a massive change for electric utility, particularly given the fact that the growth rate over the last fifteen to twenty years has been close to zero, so there's been relatively no load growth in fifteen to twenty years. Now suddenly you have utilities having to pivot to doubling the size of their system in that same horizon.

capacity to consume data. And if you think about where we are in this curve, I mean we're on some form of S curve right of human data consumption, which then directly ties to data centers, devices, energy consumption ultimately, because what we're doing is we're turning energy into data. We take electrons, we convert them to light, we move them around to your TV screens and your phones and your laptops, etc. So that's the uber trend that we're

riding up right now. And so we're climbing this S curve. I don't know that anyone has a good sense of how steep or how long this curve will go. If you go back to look at something like electricity, it was roughly about one hundred year. S curve started in the beginning of last century, and it really started to flatline, as I mentioned before, towards the beginning of this century. Now we have this new trajectory that we're ringing, this new S curve that we're entering, that's going to sort

of change that narrative. But you know that S curve for electricity took about one hundred years. No one knows where we are on that data curve today. So when you inject something like AI, you create a whole new opportunity for humans to consume data, to do new things with data that we couldn't do before, and so you accelerate us up this curve. Right, So, we were sitting

somewhere along this curve. AI comes along, and now we're just moving up even further, And of course that means more energy consumption because the energy intensity of running an AI query versus a traditional search is much higher. Now what you can do with AI obviously is also much greater than what you can do with a traditional search, So there is a positive return on that invested energy.

So that's you know when when oftentimes when this conversation comes up, there's a lot of consternation and panic over well, what are we going to do? You know, we're going to we're going to run out of energy. The nice thing about electricity is we can always make more. We're we're never going to run out of electricity. Not to say that there's not times where the grid is under constraint and there you know, you have risks of brownouts

and blackouts. That's that's the reality. But we can invest we can invest more in transmission lines, we can invest more in power plants, and we can create enough electricity to to match that demand.

referencing that large language model and creating this response. And of course that process is more computationally intensive because it's it's doing a lot more things than a traditional searchces personal search just matched the words you put into a database of knowledge that it put together. But these large language models are much more complex, and then the therefore the things you're asking to do is more complex. So it will will almost by definition, be a more energy

intensive process. Now, it's not to say that it can't get more efficient, and it will. And Nvidio just last week was releasing, you know, some data on some of its next generation chips that are going to be significantly more efficient than the prior generation. But one of the things that we need to be careful of is to think that because something becomes more efficient, then therefore we're going to use less of the input resource, in this

case electricity. That's that's not how it works, because going back to the concept of human capacity for consuming data, all we do is we find more things to compute. And this is you've probably heard of Jabon's paradox, and this is the idea that, well, if we make more efficient steam engines. He was an economists in the eighteen hundreds and he said, well, if you make more efficient steam engines, then we'll use us coal. And he's like, no, that's not what's going to happen. We're going to use

more coal because we're going to mechanize more things. And that's exactly what we do with data just because we because we've had more law for years and so chips have become incredibly more efficient than they were decades ago, but we didn't use less energy. We used much more energy because we could put chips in everything. So that's

the trend line that we're on. It's still climbing that curve of consumption, and so no amount of efficiency is going to take us at this point at least, because I don't believe we're anywhere close to the bend in that s curve. No amount of efficiency is going to take us off of continuing to consume more electricity, and at least in the near term.

in that area. But I also imagine that that agreement looks very very different to like my household energy bill or something like that.

You've got to plug it into the grid, right, So there you're working with your local electric utility or transmission company and doing planning for how big is the facility to be, how much power is it going to pull off the grid at any given time, and then over a period of time, because these facilities just tend to grow forever, and so that's the physical nuts and bolts of connecting to the grid. Now, the second piece, of course, is there needs to be some generation source as well,

like where's the power going to come from? And so those two things are related, but they could be somewhat disconnected. And so this is where you see you know, these especially the tech companies who've really been leaders in this space, entering into all these power purchase agreements for wind energy and for solar energy and in some cases nuclear. You mentioned the project earlier that's actually an AWS project where

they cite it next to the Susquehanna Nuclear plant. Right, So all of that is around where are the electrons going to come from? And how can with that purchasing power of being some of the largest energy consumers in the planet, how can they begin to influence the mix of generation on the grid? Right? And that's the critical issue, is that you're trying to influence where that power is

being generated from. It's not. And one thing just to keep in mind is that you know the electrons you get, you know, whether it's at your house or the data center down the street, they're all the same electrons. You're all pulling from the same grid. But what you're trying to do is influence how that that generation is being created, and that's where these purchase agreements come in for all these different sources of energy.

the United States, all over the world. They've been some of the biggest drivers in the corporate focus on decarbonization, and so you really have to give that industry credit for all it's done, and all the big tech companies have done some amazing work there. The challenge though, that we have is the environment that they did that in. Was that no growth environment we were talking about. They were all growing, but they were starting from a relatively small

denominator ten or fifteen years ago. So there and there was a lot of overhang in the utility system at that time because the utilities had overbuilt ahead of that sort of flatlining, so there was excess capacity on the system. They were growing inside of a system that wasn't itself growing on a net basis. Yeah, So everything they did, every new wind project you brought on, every new solar project you brought on, those we're all incrementally reducing the

amount of carbon in the system. It was all net positive. Now we get into this new world where their growth rates are exceeding what the utilities have ever imagine in terms of the absolute impact on the system. The utilities response is the only thing we can do in the time horizon that we have is basically build more gas plants or keep online gas plants or coal plants that

we were planning on shuttering. And so now the commitments that they have to zero carbon energy, to be carbon negative, et cetera, are coming into contrast with the response that the utilities are laying out in their what's called integrated resource plans or IRPs. And we've seen this recently, just last week in Georgia. We've seen it in Duke in

North Carolina, Dominion and Virginia. Every single one of those utilities is saying, with all the demand that we're seeing come into our system, we have to put more fossil fuel resources on the grid. It's the only way that we can manage it in the time rise that we have. Now there's a lot of debate about whether that is true, but it is what's happening.

on the business model. Perhaps, and we could debate how transferable AI actually is at this point and how big a moat you have over something like chat, GPT or Claude or something like that, but there does seem to be the sense of urgency among tech companies where if you're not building something out right now and trying to dominate the market and really produce the best thing possible, well you're either losing, you know, billions of dollars or

you're going to be superseded by someone who does manage to do that successfully.

on where is the power going to come from? Because the ability to at least envision and on paper design training models that are absolutely enormous, just orders of magnitude bigger than anything that we've ever built in terms of a data center are coming in to start contrast with the reality of the power system of one, is that power even available? And two, if it could be available, is there a way to do it with a zero carbon approach, which is again what these companies are committed to.

And that's that's the tension that we're in right now of how do we quickly accelerate the delivery and growth of the electric grid? Which is which and I think I just want to the quick aside on this consuming electricity is in the context where it's talking about is a really great thing. I mean, this is something that leads to economic growth, it leads to job creation. All of this, I mean, this whole problem that we have right now of electric utilities having to think about this

whole new era of growth. It's all because we're on shoring manufacturing in the United States. We're building these data centers and creating all sorts of amazing tools and creating efficiency across all sorts of sectors. And we're also in the same vein we're also electrifying transportation and heating. Like, all of this is good. It's all goodness. And we didn't even get to things like hydrogen production and other

ways that we're going to use electricity. The real rub of this, though, is that we're in this situation right now where again the electric electricity industry was somewhat surprised by this. They weren't prepared for over a period of a couple of years. Again going back to the case of Dominion having to double their load forecast flexively, They're going to go to the one thing they know how to do, which is build gas plants because they know that works. That's the easy way out. There are other

things we can do, though. There are ways we can leverage the existing system more effectively. We can use things called grid enhancing technologies, where we through sensoring, through better dynamic rating of power lines, we can actually get more out of the existing system we have. There's ways we can use storage more effectively, because really what we're trying to manage is just these system peaks. Most of the

time there's plenty of power. It's really just during the modest summer hours or the coldest winter hours that the system gets constrained, and that's what's driving a lot of the need for utilities to want to build this new capacity. But we can manage it in other ways. And it's really incumbent upon the data center industry to lean in on this, to think through how can we be more of a party to solving this problem. Because data centers

have lots of opportunities to be more flexible. They have behind the meter generation, they have behind the meter storage. They can actually be part of the solution, not just part of the problem.

But I think one of the reservations people might have about this is the idea of you know, competition with large tech companies that have a lot of money and that potentially have a lot of influence over the utility companies, and the idea that maybe you could get a situation where I don't know, Amazon gets like one hundred percent off take from some power plant in whatever state, and maybe other people are left with either you know, not

enough electricity or more likely much more expensive electricity. Can you talk about that zero? I was being somewhat facetious in the intro talking about zero sum game. But there is this idea of like competition and there might not be enough to go around, at least at the precise times that everyone might want it.

percentage of overall energy consumption. And what inevitably happens is a move towards putting either moratoriums on data center build out or putting very tight restrictions on what they can do and the scale at which they can do it.

And so, you know, we haven't yet seen that to any material degree in the United States, but I do think that's a real risk, and it's a risk that the data center industry faces, I think somewhat uniquely in that, you know, if you're the governor of state and you have a choice to give power to a say new you know, ev car factory that's going to produce fifteen hundred and two thousand jobs versus a data center that's going to produce significantly less than that you're going to

give it to the factory. Right, the data centers are actually the ones that are going to face likely the most constraints as governments, utilities, regulators start wrestling with this trade off of Oh, we're going to have to say no to somebody. And that's the real risk that I think the AI and data center industry faces today is that they are the easiest target because everyone loves what data centers do, but no one particularly loves just having

a data center next door to their house. And so that's a real challenge for the industry is that they will start to get in the crosshairs of these regulators, leaders, whomever who's pulling the strings as these decisions start to get.

the lights and and all that stuff. And I thought to myself, Oh, it would be so great when they can just make all the movies on AI with Sora or something like that, and then you know, we'll also get electricity savings because we won't have to have human actors with actual lights and stuff like that, so that'll be exciting and then being a little facetious about the end of human actors, but you know, in theory that could be exciting, and then you could you know, you

mentioned it was like, well, the utilities got surprised by the low you know, this the spike in demand. But it sounds to me like we can't really blame the utilities too much because if even the people inside Microsoft got a bit caught unsurprised by the explosion of AI interest in the fall of twenty twenty two, then I guess like we can't really blame Dominion if they hit

they were private. Further away from the issue, you mentioned peak demand, and this gets to like power, the type of power, because people talk about like this sort of need. The problem with renewables as well, at least when we're talking about solar and wind, there's this intermittency problem. It's not always sunny, even if it's hot. When it's hot,

it's not always windy, there's nighttime, et cetera. How much does that constrain the ability of more renewables to be sort of the solution to the utilities problem.

And this is the role of the system planner is to look at all these different resources and figure out how can we assure that we have the sufficient reserve margin to ensure that we're not going to have things like rolling brownouts or black eyes. Now there's a lot of tools though, that we have to help manage that uncertainty, and we have increasingly, you know, month after a month, it seems like lower cost battery options which give us more duration that we can deploy to solve some of

these issues. We have the ability of even the loads through like virtual power plants to be more responsive during these times of system peaks, right, So we have tools that we can use to manage that uncertainty. The problem

is that it is a very complex problem. I mean, you're talking about, you know, millions of different data points that you're trying to manage, and the way that utilities have historically managed these things has been fairly rudimentary in terms of their sophistication, and so they're having to go through this learning curve of how do we ensure that we can achieve the load growth that all these industries you know, are expecting and meet the reliability, cost availability

expectations of our customers. And that's where that's where the challenge comes in. And this is where the whole problem, it's frankly really interesting, is that there are lots of levers that we have and we don't just have to throw more fossil fuel plants at this problem. Does that mean we're not going to build any new gas plants in this country? I certainly will. I don't think there's a way around this problem, at least in the short run,

without having some incremental addition of fossil based resources. But there's also a lot of other things we could be doing that would significantly reduce dependence on fossil based resources to achieve the growth objectives that we have as a country.

is designed. Its designed like a power plant with an energy storage plant that just happens to be sitting next to a room full of servers, right, And so when you when you break it down to those components, you say, okay, well, how can we better optimize this power plant to be more of a grid resource? How can we have to optimize the storage plant to be more of a grid resource? And then in terms of even the servers themselves, how can we optimize the way the software actually operates and

is architected to be more of a grid resource. And that is that sort of thinking is what is being forced on the industry. Frankly, we've always had this capability. I mean, we were doing I mean we did a project like twenty sixteen with a utility where we put in flexible gas generators behind our meter because the utility was going to have to build a new power plant if we didn't have a way to be more flexible.

So we've always known that we can do this, but the industry has never been pressurized to really think innovatively about how can we utilize all these assets that we have inside of the data center plant itself to be more part of the grid. Right, So that's I think the most important thing is really thinking about how data centers become more flexible. There's a whole nother line of thinking, which is this idea of well, utility is not going to be fast enough, so data centers just need to

build all their own power plants. And this is where you start hearing about nuclear and SMRs in confusion, which is interesting except it doesn't solve the problem this decade. It doesn't solve the problem that we're facing right now because none of that stuff is actually ready for prime time.

We don't have an SMR that we can build today predictably, on time, on budget, So we are dependent on the tools that we have today, which are things like batteries, great enhancing technologies, flexible load reconductoring, transmission lines to get more power over existing rights of ways. So there's a number of things we can do with technologies we have today that are going to be very meaningful this decade, and we should keep investing in things that are going

to be really meaningful next decade. I'm very bullish on what we can do with new forms of nuclear technology. They're just not relevant in the time horise and the problem we're talking about.

We have to relearn these things. And as a country like we do not have a supply chain, we don't have a labor force, we don't have people that manage construction projects that know how to do any of these things. And so when you look at what South Korea is doing, you look at what China's doing, you know, they are building nuclear plants with regularity, they're doing it at at a very attractive costs, they're doing it on a predictable

time horizon. But they have actually built all of those resources that we just simply don't have in this country that we need and we need to rebuild that capability. It just doesn't exist today. You know.

want to raise the prices this much, et cetera. Are there regulatory hurdles or things about the regulatory system right now that are going to make that doubling of demand more challenging than they need to be?

this concept of like we easily forget things. No one who's a regulator today or the head of a utility today has ever lived through an environment where we've had this massive expansion of the demand for electricity. So everyone now including the regulators, are having to relearn, Okay, how

do we enable utility investment in a growth environment. It's not something they've ever done before, and so they're having to figure out, Okay, how do we create the sort of the bandwidth for utilities to make these investments, because one of the fundamental challenges that utilities have is that they struggle to invest. If there's no customer sitting there you asking for the request, right, so they can't sort

of invest. I mean, if I'm in Vidia and I'm thinking about the world five years from now and think, wow, how many chips do I want to sell in twenty thirty, I can go out and build a new factory. I can go out and invest capital, and I can go do all this. I mean, I don't need to have an order from a Microsoft or an Amazon or a Meta to go do that. I can build speculatively. Utilities can't really do that. They're basically waiting for the customer

to come ask for it. But when you have all this demand show up at the same time, well what happens. The lead times start to extend and so instead of saying yeah, I'll give you that power in a year or two years. It's now like we I'll give it to you in five to seven years. And so that's an unsustainable way to run the electric utility grid. So we do need regulators to adapt and evolve to this new era of growth.

investment requirements. And while there is clearly demand for electricity and maybe new types of electricity, it's not always certain and you're sort of managing these day to day cycles

and things like that. But if we know that AI is booming, and we know this is a future area of growth, and we see these headlines like AI servers are going to require like one hundred tarawatt hours per year and things like that, does that potentially give utilities more certainty or more confidence in the future investment outlook.

up at their door and say that they want. Right, they say, well, okay, I talk to X y Z data center and this is what they say they want. But they don't necessarily have view to the long term, like what really is the demand behind that? Like I'm getting a request because one data center bought one parsonal Land and they need five hundred mega loots of power, and then they're trying to extrapolate from that, well, what is that underlying demand for data? Right? How much more

growth should I expect after that? And that's where the utilities I think are really struggling is that they don't they can't see much beyond the requests that they have, and so they're trying to then extra appolid Okay, what is it? What are these trends? You know? And really the only the only way to get a good sense of the the real demand for data and the trends is you have to actually go back to the probably to the NVIDIAs and the intels of the world and

go what's the forecast for chip sales? Like, what's the forecast for how many chips you're going to make? Not I mean not even sales, but really how much they produce because frankly, I think every chip they can produce, it will get plugged in something. Someone will buy it and it will get plugged in. So that's that's probably the best estimates that you can come up with for what utility load growth should look like, at least as

it relates to data center. Right. But you know, you have thousands of utilities in the United States, so you don't have you know, there's not even like a single source you can go to to say, Okay, what's the forecast next year for electricity loads? Like nobody has that. I mean people, there's numbers out there, but they're not

really based on anything other than speculation. So this is the challenge that utilities is that they don't have a good view into what load growth really is going to look like over the next five, seven, ten years.

unpredictable demand. No one knows like what the steady state demand is going to be for this stuff, and yet the utilities are sort of legally constricted in the degree to which they can say overbuild now or sort of operate or plan for that demand.

thought it was interesting. So I think there is a sense among a lot of commentators that there is going to be competition for power at least at certain times. But I thought Brian's point about how, in some respects data centers might be the easy target for politicians to kind of ignore, I thought that was really interesting. And again his example of what, well, if you know, if you're a governor or something, and there's a Tesla factory that wants energy versus a data center that probably has

I don't know, like a handful of employees. Maybe that's an exaggeration, then you're gonna go with the Tesla factory.

I thought that was interesting. You know, again, I do think it's like striking, and I think this is not even just in the energy context, But I still a sort of fascinated by this idea that like open Ai was this company, I think it was founded in twenty sixteen, and people saw GPT one and GPT two and then GPT three, which came out before Chad GPT.

terms of energy and maybe even additional green capacity. But the other path is kind of depressing, where you have a bunch of big tech companies that feel existential pressure to do whatever it takes to win the AI race, and maybe whatever it takes includes getting energy through coal or something like that.

But you could sort of understand it in the context of very little growth, right, So why make these like really big investments in anything when obviously at the time there wasn't as much concern or awareness about climate change and the effects of fossil fuels, and there just wasn't

much demand growth, So why make these big things? And so you think about like South Korea and China having never really slowed down on the nuclear construction, but they're also because they're developing countries or poor countries becoming richer, they never presumably had that sort of demand plateau just by dint of having started from somewhere lower.