In this episode, Astrid Atkinson, co-founder of Camus Energy, talks about her company’s “grid orchestration” work of helping utilities see, track, and coordinate the distributed energy resources in their territories.
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Text transcript:
David Roberts
One of my favorite things I ever wrote was a 2018 piece for Vox on grid architecture — the basic structure of the electricity transmission and distribution networks. It was about how a top-down system, with one-way power delivery from big power plants to passive consumers, might evolve into a bottom-up system, driven by local distributed energy resources.
Thanks to all-star illustrator Javier Zarracina, it even has awesome animated illustrations.
One person who read that piece was Astrid Atkinson, who at the time was a senior software engineer at Google. She had managed a team that shifted Google search from a top-down system to a massively distributed system, back before the term “the cloud” existed and there was no template available. She and her team had to develop the principles and best practices of getting reliable performance out of millions of unreliable, loosely coordinated machines. By doing so, they radically expanded the scale and speed of what search could do.
She thought, wouldn’t it be cool if the power grid could make the same shift? Unlike some people, though, she didn’t just blog about it — in 2019, she left Google to co-found and run Camus Energy, a software company that helps utilities see, track, and coordinate the distributed energy resources in their territories. The company calls what it does “grid orchestration.”
Atkinson has been a thought leader in pushing for a new grid architecture. (See Camus’ white-paper series on “the rise of local grid management.”) So I was super-excited to geek out with her on this stuff. We talked about the conceptual shift from centralized to distributed and the drivers making that shift inevitable, plus getting more out of the grid we’ve already built through coordination and efficiency, and how the utility sector can evolve to better manage local resources. I really loved this one.
Okay, then. Astrid Atkinson. Welcome to Volts. Thank you so much for coming.
Astrid Atkinson
Thank you so much. I'm really excited to be here.
David Roberts
I'm so excited for this. Astrid, I have to tell you just by way of preface that I had a weirdly difficult time preparing for today's pod because I'm just so excited by this whole area, and I'm so jazzed. I have so many things to ask you about, so many things I want to say about all this stuff, and I'm kind of overwhelmed and fried my circuits. But let's start here: Let me describe for listeners what you did at Google and tell me if this is an accurate description. So you were part of a team, I think, leading a team that was shifting the way Google did things away from a model where computing was done on a relatively limited set of high-quality, extremely reliable data centers, tightly centrally controlled, to a model where computing is done not on a small set, but on thousands, millions of distributed computers living all over the place, any one of which might be unreliably connected or off periodically or weak or otherwise glitchy.
So basically, moving from a model of tightly coordinated, central control, limited number of entities, to loosely coordinated millions of entities, somehow getting aggregate reliability out of massively distributed, individually unreliable machines. Is that more or less accurate?
Astrid Atkinson
Yeah, that's about right. So my role was in the site reliability engineering team at Google, which is a function that nobody's ever heard of outside of the kind of tech industry. But you can think of reliability engineering as being basically Google's systems engineering function. It's the entity that's kind of responsible for pulling all of the pieces together between sort of software and operations and networking and hardware and everything, and making sure that you can get them to kind of work as a reliable system overall. And I was part of the original team that kind of — it wasn't a function that existed in the industry before Google made that transition.
I was part of that original team at Google and then led a lot of Google's work around scaling out that model.
David Roberts
And so now the idea, more or less is to oversee or encourage a parallel evolution of the electricity grid, basically, from a limited number of tightly centrally controlled entities to a loosely coordinated, massively distributed, huge number of smaller entities, basically.
Astrid Atkinson
Yeah, I mean, that's definitely the hope. And that's partly derived from the utility industry and the grid space's sense of the changes that are needed and also partly derived from my sense that there are a fair number of parallels between some of the approaches that we took and kind of had to make up on the spot to support massive growth and really significant changes in the way that we managed systems for that work at Google. And there are parallels with the changes that we need to go through on the grid side. So it's less like "there's this one piece of technology that we built at Google that will totally solve the problems" and more like "we had to develop a set of approaches and a set of kind of integrative and system level perspectives to figure out how to make that change happen."
And I think a lot of those can be helpful in the grid space.
David Roberts
Yeah, I mean, I think one of the most intriguing things about this is in doing that work, you extracted a set of principles for how to design systems like this such that they are reliable, et cetera. And it's those principles, I think it's like conceptually those principles apply to the grid. Obviously, the individual technologies might be different, circumstances are different, but the principles of how to make it work, I think are a weirdly neat fit. The reason I think we should maybe pull out, the reason that this is not something that the utility really can choose to do or not to do.
Utilities kind of have to do it for a couple of reasons. One is all these distributed energy resources, Volts listeners are familiar with these distributed — with these solar panels and hot water heaters that can store energy and batteries, et cetera, et cetera. All these sort of behind the meter distribution side, distributed resources are coming online. Whether the utilities like it or not, they are swarming —
Astrid Atkinson
It's happening.
David Roberts
online, it's happening. And right now utilities are just like kind of hoping it works out, we'll get into that. That's one reason. But the other reason is we're expecting, like you could say of Google, like it couldn't have scaled to the size it got, it couldn't do the amount of computing it's doing without going through this transition.
You just can't at a certain point with a centrally controlled system where you're tightly controlling a limited set of entities, you just can't get big beyond a certain level. You run into sort of computational limits of your computational resources for a central controller. And we're expecting a lot more out of the electricity system in coming years, as Volts listeners are also very familiar with. We're going to two or three x the demand that it has to satisfy in a much more complex way. So I think it could be argued, and you have argued, and I think it's pretty self-evident, that the electricity system cannot achieve the scale we want out of it without going through this evolution.
There's just no way for the way it's currently run to get as big as we want it to get.
Astrid Atkinson
Yeah, and if you want some simple examples of why that is, utilities have spent a lot of money and a lot of time in the last 10 to 15 years installing smart meters. Right? They were supposed to give us the kind of universal visibility into customer activity that I think we can all intuitively think that we would need to manage a rapidly changing grid with a lot more complexity. But most utilities don't really have particularly high-scaled data infrastructure. And so the idea of actually being able to do something useful with all of that meter data, SCADA data, kind of everything at scale on an ongoing basis in real time, using that as a foundation for analysis and visibility and those kinds of things.
It's really hard for them because usually the software systems that gather and process that data, they're on premise within the utility's own data center. They're typically not really using any kind of modern scalability approaches beyond downsampling the data, which means losing some of it. And they're usually running on a single machine. So it gets really difficult to incorporate very large amounts of data when you can only use one computer.
David Roberts
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Information
- Show
- FrequencyUpdated Biweekly
- PublishedNovember 22, 2023 at 5:00 PM UTC
- Length1h 21m
- RatingClean