Catalyst with Shayle Kann - Battery booms and the rise of flexibility [partner content]

Episode Date: March 30, 2026

Battery markets have a pattern: They boom, capital floods in, prices collapse, and then the cycle starts again. So as storage becomes more important than ever, how do we maximize revenue and deliver needed flexibility? In this episode, Stephen Lacey speaks with Sean McEvoy, chief product officer and head of commercial at GridBeyond North America, about how that cycle is playing out across global power markets — and what happens when batteries stop being scarce. As markets saturate, the source of value begins to shift. It’s no longer just about building assets. It’s about how precisely you can forecast, optimize, and trade them. GridBeyond sits between energy assets and energy markets, using AI to coordinate everything from industrial loads to battery fleets. It is increasingly bringing that model to data centers. These facilities are driving a surge in electricity demand, but they also introduce a new tension. The grid increasingly needs flexible loads, but data centers are built for reliability, not interruption.  The result is a wave of new approaches, from behind-the-meter batteries to “bring your own capacity” strategies that pair infrastructure with grid support. Learn more about how GridBeyond develops AI software that helps businesses unlock flexibility in their energy systems.

This is partner content from Latitude Studios. Sean McAvoy has spent most of his career building AI software companies. Energy wasn't part of the plan. Then one day, while working at a company called Veritone, someone handed him an unexpected challenge. Somebody said, hey, Sean, what can you do with these 20 patents around battery technology and forecasting? And all they were was patents. It was like little software. So I took the patents and built a software business around those.

So Sean did what software entrepreneurs do. He turned the patents into a platform. But as he quickly discovered, the power business, a maze of markets, machines, and regulations, is not an easy one to master. Of all the businesses that I've been in and software companies I work for, the energy industry is highly complex. And so that's how I got into the energy industry. But he and his team figured it out. And those patents became the foundation of an AI platform that sat between energy assets and energy markets. forecasting prices, controlling equipment,

and automatically bidding electricity into the grid. It was built to answer a set of deceptively simple questions. How do I get the solar to work with the battery? How do I get the battery to work with the EV? How do I get solar and battery to be able to work with my manufacturing process? And so that lands itself to, okay, we need more intelligence. While Sean was building that platform, an Irish company called Grid Beyond was developing another

critical piece of grid flexibility. The company had emerged as a leading demand response provider in the UK and Ireland and was beginning to expand globally. Grid Beyond was predominantly like a hardware company in terms of installing hardware control systems at industrial sites to uncover flexibility in energy systems at those industrial sites. So it was kind of like two bookends. One bookends was like controls that are on site at large industrials. And the other bookend was the ability.

to put energy into energy markets and make money. And over time, the whole middle piece between the two bookends became some very sophisticated AI-powered technology that is kind of like driving optimization. That middle layer was exactly what Sean's team had built. And in 2023, Grid Beyond acquired the Veritone energy business, bringing those capabilities together into a single platform. We uncover flexibility.

And once we find it, we ask the, customer, what do you want to do with it, whether it's revenue generation, cost savings, or resiliency slash reliability. The customers span heavy industry. Metal plants, cement plants, pulp and paper mills. Increasingly, they include data centers. Facilities that consume enormous amounts of electricity, but also contain systems that can be carefully orchestrated, cooling equipment, backup generators, batteries, and the computing workloads themselves. And Grid Beyond is increasingly being asked to orchestrate all of it.

we can then inform the data center, hey, we need to get prepared already because on Thursday at 4 o'clock we're predicting an event. Let's turn on our optimization to reschedule jobs at that time. We're going to reduce our energy on the chiller pumps. We're going to trottle down like some of these chips. We're going to prime our batteries from our solar. We're going to get our gen sets turned on 20 minutes so they're all warmed up and ready to go. That is all done by software. It's all done by intelligence, by having models built in a digital twin environment such that you can orchestrate and control all of the moving parts. Making all of that work requires extremely fast decision-making, because when something

happens on the grid, the response window can be tiny. That's where AI comes in, and the advances happening right now are unlike anything Sean has seen in his years working in the field. How does this period compare to other periods of acceleration in the tech industry? does this feel a lot different? Oh, yeah. There's nothing like this. Like the pace at which it's changing,

the pace of the capabilities that are at your hands these days, like to be able to develop like something new is I've never seen anything like it. Even like five years ago, you were like, let's pull all the data. Let's send it up to the cloud. Let's like have applications in the cloud,

make decisions. No, now you're doing it like right there at the local site level. And in some cases, you have to do it because when you're a spot, responding to extreme events or any event or even a grid event, you have to do it in milliseconds. The goal right now, I think for a lot of people, it's like sub-50 millisecond response. And so you want to reduce latency everywhere.

So you start doing your inferencing and decision-making locally, very locally on the ground, like, at the site level. And then once it's done, it's inferencing and decisioning, it then sends it back to the cloud so you can see what it just did. And so you're seeing innovation around that that is allowing the responsiveness of all of these things like batteries or fuel cells, etc. To be able to act before a blackout or a brownout happens. This week, Stephen Lacey speaks with Sean McAvoy, president and chief product officer of grid beyond, about the frontiers of grid flexibility. As the grid gets more complex, software is increasingly keeping it all in sync. Sean and Stephen talk about how battery markets boom and then saturate, the promise and limits of data center flexibility, and how AI software is orchestrating everything from industrial loads to giant battery fleets. So you have a unique window into how battery markets play out around the world.

From the UK to Texas to Japan, when we think about how these markets evolve from opportunity to saturation, is there a consistent pattern you see repeating itself? Yeah, we do. I mean, because we've been in Europe for quite some time, like 15 years, we've already seen saturation in, say, for example, like the UK market with lots of batteries, like coming online. And because you have the availability of batteries and they have a lot of capacity that can be put onto the grid, prices dropped because scarcity wasn't as much of an issue anymore. But when the prices drop, it also makes it hard for those batteries to actually finance themselves because they were originally put in there probably when the prices were high. Those batteries, lithium batteries, you're talking anywhere from like 50 megawatts, 100 megawatts, 200 megawatts of batteries, and you're talking hundreds of millions of dollars that has to be financed and you're expecting to get paid back through the monetization of that battery capacity

in the energy market. But once it gets flooded, then the degree. determines, hey, there's enough supply here. I don't have to offer my energy request at this price. I can drop that price. And so we saw that in the UK probably at least five to six years before we actually then saw it in Aircott, in Texas. And I think the last really good year of battery pricing, for example, in Texas was probably around like 2023. And then it started to really drop in 24. And then, like, we saw it further in 2025. There was a short kind of short spike in prices when Aircott brought out, like, a new service that was highly priced ECRS, but that only lasted

like a few, few months. And so we're seeing this in this cyclical part, like in Aircott. But it's, it is cyclical. Like, and I'll tell you, like, why. It's, what we see in Aircott now is, like, a lot of batteries came, came online over the last, like, five to six, six. seven years in Aircott, like a lot. And so when the grid operators looking at that are going, well, you know, we have a lot of solar, we have a lot of wind in Texas. We now have a lot of batteries in Texas. I'm not sure if we need to build any more generation. And it's not costing this as much money as it used to because there's so much supply coming from these batteries and renewables that we don't need to build like neutron transmission lines. And I don't need to build

out like more generation. But all at the same time, demand is starting to go up. mainly because of what I spoke about earlier in terms of like the electrification journey that customers and industrials like are on and even data centers like coming online. So the demand keeps going up, but we're not doing a lot in terms of new generation because the batteries are flooding the market. Then all of a sudden, demand is like, okay, it's outpacing what is currently on the grid in terms of batteries and renewables because people have stopped putting battery projects into Texas because the prices are not good enough. And if you then have an event where AI is exploding and there's new data centers like being built, which is really driving demand up, now you're kind of behind the demand curve. And so we see cyclically in another couple of years, the prices will start to come back in AirCod and people will start to make money again. And so what we're also seeing is like, you know, when I said like, you know, five to seven years ago, battery projects started to really explode in AirCard. We're seeing this in Japan right now.

We're at the very beginning of it, like in Japan, where their markets are now open up to batteries. And the price of energy for battery is like sky high. Like in some areas, it is like $200,000 per megawatt with a service called FCR in Tokyo. And we're also seeing like another evolution happening in Australia where Australia has, They've encouraged and incentivized rooftop solar for many, many years throughout Australia. And then they started to cause problems on the grid, like big frequency issues because of cloud cover, etc. Now Australia is going through an explosion of sub-5 megawatts batteries going on the grid, not big ones, but small ones that are manageable in communities or in industrial parks. So we're seeing an explosion kind of there as well.

And so it's all kind of cyclical in terms of, you know, it'll get saturated. It'll be too, too many. And then demand will come back, like as it keeps growing over a number of years. And then you'll see the prices being more beneficial to batteries. But yeah, we see this kind of cyclical evolution kind of happening from the UK to, you know, the US to Japan and even Australia right now, which is fascinating to watch. And so what are you doing during that saturation period of the cycle? Are you searching for different revenue streams to stack on within that market? How do you typically change?

Yeah, so, I mean, there's two things. You have your existing batteries that are in a market. And I mean, physically located within the market, so you're not going to be able to move those batteries. But what happens is with saturation is that the spreads get really narrow between the high price and the low price. And you really have to fine tune your brain. predictive models to make sure you're accurate down to the minute in terms of when the high prices

are going to actually hit. You have to build models for shoulder seasons, for main season, summer, main season like winter, because the market acts differently across seasonality, mainly driven by weather. Gas prices is another contributor, but weather is actually a big one. And you can see from the different storms that we've had, Uri and I think like 21, you know, even like this year, we've had like some really crazy cold spells that are driving up kind of energy demand. And so like what you're really working on is getting your forecasting and your optimization really tight and really kind of fine tuned because the spreads are small. And like, you know, what our salespeople do is like, you know, they'll start looking to see, okay, they'll always want to follow the money. That's their job. Follow the money, find where projects are going to monetize greater. And usually it's kind of like, okay, well, where is demand outpacing

supply? And like if you look at like PJM and you see what's happening in PJM right now, the prices are going sky high capacity prices in the base residual auctions are at an all-time high. And coupled with that, you have long-term incentives that are. are at a local level, a state level. So like Illinois right now in the PJM market area has great incentives for batteries. And I think we're also kind of over the hump of, you know, where we were at this stage in 2025,

where we had a new administration come in. There was a new focus on energy and what that strategy should be. And the industry kind of stalled out a little bit in 2025 and then came back when you got more certainty. And now that it's back, we're seeing, like, you know, new markets like PJM with the capacity prices being high. Also, MISO now is starting to come back with their own higher capacity prices where it makes it attractive for people to be able to put batteries in those markets. So we're seeing now a big shift in our sales pipeline in terms of battery projects almost equal to what we have existing in AirCard, Texas.

We're now seeing like the same in PJM. How transformative do you think the expansion, rapid expansion, of data centers will be for battery storage? It is definitely going to have an impact. It is not the silver bullet. There is actually is no silver bullet right now, as far as I can see, that's going to help data centers get online quicker unless you can get your hands on some big gas turbines,

but it takes three years to build them out, and there's a waiting list for three years to even get them. But in the meantime, it's kind of like, what do I have at my disposal? And we look at what we call solutions around the meter. What solutioning can you do around the meter? What solutioning can you do around the meter to help out and provide supplemental power to these data centers if they have to sign an agreement with a utility, which enforces them to curtail at the peak times during the year, like just the peak times. And so then you're looking at a combination of, okay, generators, you know, whether gas or diesel generators, coupled with batteries, coupled with potential like solar if you have enough land.

And so we look at like solutioning around the meter to help solve for that for potential curtailment of data centers so they can get online. And batteries are part of that solution. And batteries are like evolving as well, not just like one, two hour batteries. Now you can go like between four and eight hour batteries, depending on the chemistry of the battery that you want to invest in. But long duration batteries are a good fit for data centers if they have to curtail for like 30 minutes, like all. or an hour. You can get like a four-hour battery, six-hour battery and make sure you have enough coverage. But it's not optimal. Like, data centers need firm, base, low power, wherever they can get it. That is number one on their list. It'll always be number one because reliability is their number one

concern for data centers. They want to maintain high levels of uptime, your five-nines. You know, that's what they're aiming for, regardless of whether they're public or their private data centers uptime and reliability is key. There is an open question about curtailment for data centers and how much they'd be willing to curtail. And certainly, I think if they can get faster interconnection, many of them would be willing to, but not for very long. What do you think the optimal curtailment is?

How much are they willing to accept and do bigger batteries allow them to play a little bit more? Yeah. I mean, I spoke to quite a number of kind of data center developers, data center owners, and basically they don't want to curtail full stop. I mean, they have fitted out their data center with the best infrastructure. They've paid a lot of money for GPUs and CPUs, extremely expensive. They want to maximize those chip assets, like, as much as possible. And curtailment for them is like something that they just do not want to do unless they are forced into it.

And some of them will even consider like relocating or changing their plans in terms of where they cite their data centers so they don't have to curtail. Senate Bill 6 in Texas is kind of like an example of that where if you're kind of 70 megawatts and over, you need to have the ability to curtail. And other states are adopting like similar measures as well. And so like you can move where you don't have to have that kind of restriction. But then you're still probably time to power is still an issue for you. Big batteries can help. But 30 minutes to an hour, I think, is something that you can work within in terms of the data center in order to curtail. You can get really smart.

And there's like some solutions out there that will be profiling all of the internal jobs within the data center that is being sent to kind of your CPU, GPU kind of platforms. And if events can be predicted, like people like us, we can predict an event that's on the grid that's going to, like, cause a curtailment event, you can then optimize and reorder your jobs going to your CPU and GPU. So your non-critical jobs are going to the CPU and GPU at that time because you're not going to turn them off. You're going to throttle them down. And you're probably going to trottle down all your chiller pumps at the same time who are also consuming energy. And so there is that kind of, or if you're like, you know, even more. sophisticated and you have sister data centers. You can move jobs between data centers if you know

in advance when a energy event is going to happen that's going to warrant that you will have to curtail. And there's a lot of different types of data centers. Does curtailment work for any of them better than others? Yeah. I mean, we have all, we have all types of customers. The ones that are the most flexible by far are the crypto data centers. And there's lots of them in Texas. And they're the ones that have like flexibility in terms of, well, if the prices are super high, I don't need to curtail. I'm making more money like mining than I need to be participating in energy markets. But then when crypto is kind of like, you know, the prices fall, which we've kind of seen in the last couple of months, the cryptos are coming back and saying,

hey, put me into the energy markets. And they can also avail of batteries as well. They can put like a lot of batteries around their sites. And, you know, they can continue. you to maintain power as well as participating in the energy markets. And that kind of like irks Texas like somewhat in terms of like, hmm, these crypto guys are double dipping. You know, they're mining Bitcoin, but are also playing in the energy market because they have all these batteries like supplementing power. It gets harder like when you're a public data center and you have multiple tenants

within your data center. The only way that you can curtail is like you have to actually ask like each of your tenants or have an agreement with each of your tenants to see. see if they can actually curtail. That means putting sub-metering into your data center, so there's a meter by tenant, and that meter can then be curtailed. But there's then data centers as well that are not what are called real-time data centers.

They are doing large language model training. They're doing batch processing. They're not real-time critical. They're not doing inferencing AI in those data centers. And you can curtail those data centers, like very easily. But when you're talking about like real-time processing and inferencing, where you're consuming large amount of energy to power these GPUs, you do not want to curtail those. And so you have to be, you know, smart and like very strategic if you're a data center developer. And we speak with a lot of them in terms of based on what you're doing in your data center, are you like a hyperscaler?

Are you not? Like, what tier are you? Where are you going to put your data center? It kind of determines like what you can actually do with it. There's a lot of hope and enthusiasm among clean energy professionals and advocates that we can deploy as much solar and batteries together to serve data centers. What is the role of solar and storage together in serving these new loads relative to all the other resources that these data centers are going to be utilizing? Yeah, well, number one, it's like I go back to it. It's like they're not the answer.

they are supplemental energy that can help. And they're kind of filling a gap until, you know, more jet generation comes online. And depends on what form of that generation can be, everything from solar plus battery, plus nuclear, for example, plus gas turbines. But what we are also seeing is like, we are seeing data centers like, you know, and even retail energy providers who are coming to a utility hand in hand and saying, look, we want to put a data center here. I'm the retail energy provider.

I'm going to provide this data center with energy. I need to get an interconnection, but we're also willing to put batteries down in areas of congestion on your grid to alleviate that congestion on the grid. And it may be kind of close to where the data center is, but it's not directly on the land of the data center. So you can use batteries to alleviate congestion in certain areas. and data centers are willing to pay for that.

I mean, if we're going to pay for a battery to provide supplemental like energy to the data center, maybe it's better to go talk to your utility and say, where would you like me to put this to help you give me an interconnection faster by my batteries helping to decongest the grid? And this is like the bring your own capacity model? Bring your own capacity, more collaboration between data centers

and utilities, data centers, and the grid, data centers and what I call gen tailors, like big retailers, whether it's an energy or a constellation energy, who can also generate their own energy, they can supply it to a data center, but they also want to help out

the local grid as well, because the last thing that people want to see is that the cost of the energy for the data centers is getting passed down to the raypayers. That is like what would give everything a pretty bad name because it sounds then like that the the raypayers are paying for all of this, but they

don't typically see the benefits of it, of a big AI data center. So more collaboration between everyone. And really what we have right now is like we have a deployment problem. When I was working way back in whenever at Sun microsystems and, you know, we were doing the first like web applications, it was kind of like, how do we deploy these things at scale? You know, cloud was like, you know, starting and it was like, how do we deploy everything at scale? And that was our big problem that we had way back then. But now, like, we have the same problem. We have the solutions, like, to solve the problem,

but how do we deploy it at scale in a fast enough time to get these data centers online? Because the U.S. wants to win the race of AI. And there's other countries out there that are also going at a super fast pace. And right now, our problem is getting these data centers, like online and, you know, new generation being built and new transmission lines being built.

So we have a deployment problem, which I saw a long time ago as well. Yeah, I mean, energy is all about trade-offs. So can you walk me through some of the benefits and trade-offs of other resources when you think about how these sites are being powered? Obviously, a major push toward gas, but huge constraints in the supply chain, enthusiasm about nuclear but long timelines, same with geothermal. How do you see the resource mix? And what are you seeing customers pursuing? Like, everything is being looked at again. Nothing is off the table right now.

I mean, if you, you know, if you were like two, three years ago, yes, there were things off the table. Like, sustainability was number one on everyone's list. In the U.S., it is not anymore. And so people are willing to look at, like, all types of energy generation that can be leveraged to help solve, like, the problems. And, like, you know, natural gas, you know, that is now coming back. And people are like, oh, firm base load power. If I can get a connection, I'm going to, a gas connection. if it's available and where I'm going to cite my data center,

I'll be able to get online faster. Geothermal is now being looked at, like you see, like some big sites around geothermal. Texas is putting a huge amount of effort into geothermal as well. Nuclear, you see some plants reopening that were dormant and being retrofitted. So nuclear, in terms of like what we had and closed down, is now starting to reopen. Not all of them will because they,

because they can't. And then you're looking at like, you know, the future, maybe five to ten years from now, which is like these small modular reactors that can fit on half the size of a football field, you know, but they could power like, you know, 10,000 homes, for example. But that's kind of out there and it has to be tested. So everything is on the table right now. There's a lot of, there's a lot at stake in terms of the AI race

and how you get these data centers on the grid, fast enough. And it's all about combinations. It's not just one thing. You're going to be looking at like every type of generator, turbine, long duration battery, lithium, solid state, like, you know, whatever's going to give you the mix you need to get up and running as fast as possible. But these are kind of like short term until newer generation is built and transmission lines improves. So you were going through this kind of like chaotic phase at the moment and it'll last for probably like three years where whatever you can put together to get yourself online, you are going to do it.

You mentioned that you have a lot of different types of data center customers. Are you seeing customers becoming more sophisticated because they're being forced to think about energy in different ways? Absolutely. I mean, time is money in terms of like not getting these data centers like up and running. And especially like, you know, even the likes of like meta and, you know, you have your articles of the world and your Microsofts. and everyone else who are trying to build, build, build these out,

they're investing even in their own teams, like they now have their own big, sophisticated energy management teams that we talk to and we deal with, and it is all about technology being implemented to manage energy. It's not so much like that there's somebody there flipping switches and going to turn this on that off. It is all kind of fully automated. It is all predictable.

It is all based on models. it is all even like site load modeling in terms of like how the AI is consuming energy and at what times of the day is there spikiness in the consumption of these chips. So what we do a lot is we build digital twins of everything that we look at, whether it is an industrial site or it is a data center or it is a big battery and solar plant. We will build a digital twin like off that plant so we can see data flow, energy flow, everywhere in the plant.

I mean, it's both a nerve-wracking and really exciting period. I think if you really care about driving down emissions or you're worried about affordability, certainly a lot of people are concerned about, you know, the increasing use of fossil fuels, particularly gas, to power these data centers. But it's also unlocking just extraordinary innovation and contracting and a huge collection of how to deploy

different kinds of clean resources. He talked about using distributed batteries under a just bring your own capacity model. How do you think that this period is going to influence the energy transition? Where are we? The energy transition is still happening. It has gone through a couple of bumps. They're like speed bumps and you're forced to slow down.

You know, and I spoke about early 2025 with brands being taken away, cancelled. And that's kind of like we'll see like a drop in innovation. But filling that void is what I call the private, privateers. So it is the likes of, you know, the big hyperscalers or these big companies, like whether it's Nvidia, whether it's like Microsoft, whether it's Apple, etc. They are now, I would say, filling that gap in terms of creating their own energy management systems, their teams, partnering with people. We saw, we can see consortiums today, even like around DC Flex. And the fact that, you know, you can now do so much more, so much faster with AI, solutions

are being developed at a rapid pace. Like my own engineering team, everything is built like AI native and the efficiency of the engineers has just gone through the roof in terms of like whatever kind of tool of choice that they're actually using to help develop software and code so much faster.

It's amazing. But you hit a speed bomb, but you will solve around it. And as the AI continues to get faster and better, those solutions are also coming quicker. Sean McAvoy, thank you so much. This is a great conversation. Thanks for having me. It was a lot of fun.

Sean McAvoy is the chief product officer and head of commercial for Grid Beyond North America. GridBeyon develops AI software that helps businesses unlock flexibility in their energy systems, connecting assets like batteries, generators, and industrial loads, and connecting them to electricity markets. Learn more at gridbion.com.