In this engaging episode of the Energy Insiders Podcast, host Chris Sass joins forces with industry experts Jeff McAulay and Jess Melanson for a deep dive into the transformative role of AI in the energy sector. Jess Melanson, President and COO of Utilidata, outlines how their AI solutions are accelerating the evolution of utilities, enhancing grid operations, and facilitating the integration of renewable energy sources. Jeff McAulay, from Energetic Capital, discusses the financing side of technology deployment in energy, emphasizing the critical advances in distributed generation. Together, they explore the future of energy technology, the impact of federal funding on innovation, and the security implications of AI in utility management. This episode offers a comprehensive look at how AI is reshaping the landscape of energy utilities, promising a smarter, more efficient future.
In this engaging episode of the Energy Insiders Podcast, host Chris Sass joins forces with industry experts Jeff McAulay and Jess Melanson for a deep dive into the transformative role of AI in the energy sector. Jess Melanson, President and COO of Utilidata, outlines how their AI solutions are accelerating the evolution of utilities, enhancing grid operations, and facilitating the integration of renewable energy sources. Jeff McAulay, from Energetic Capital, discusses the financing side of technology deployment in energy, emphasizing the critical advances in distributed generation. Together, they explore the future of energy technology, the impact of federal funding on innovation, and the security implications of AI in utility management. This episode offers a comprehensive look at how AI is reshaping the landscape of energy utilities, promising a smarter, more efficient future.
00:00:01 Jess Melanson
So we are going to have a major uptick in adoption of this.
00:00:09 Jess Melanson
Technology.
00:00:11 Jess Melanson
In the next three years.
00:00:13 Jess Melanson
And I say that because it will be driven by big infrastructure choices that utilities.
00:00:19 Jess Melanson
Have to make.
00:00:19 Jess Melanson
They have to replace ageing metres. They have to upgrade Transformers and various equipment on the on the electric grid and so.
00:00:28
Cool.
00:00:30 Jess Melanson
So when they make those decisions, I think what we've started to do in collaboration with our early adopters is help utilities understand that they need to make a choice about the compute that's inside that infrastructure and they need to make decisions about how they're going to run AI models on the grid.
00:00:50 Chris Sass
Your trusted source for information on the energy transition. This is the.
00:00:55 Chris Sass
Guide to energy podcast.
00:01:04 Chris Sass
Energy insiders welcome to insiders, guide to energy. This week we have an exciting episode talking about AI and what that means and where it should reside in the utility and energy industry.
00:01:14 Chris Sass
Our guest today is the CEO and President of utility data, Jess Melanson. Jess, welcome to the programme.
00:01:22 Jess Melanson
Chris, thanks for having me.
00:01:23 Chris Sass
Well, you, I heard in your opening statement what your vision is. You and I met, I don't know. A couple months ago now. And and you showed me some prototypes and you got me really excited about what your idea for where AI lives and what it does. I think it makes sense to maybe start by telling our audience a little bit about what you guys are building and what you're doing.
00:01:43 Jess Melanson
Yeah. So we've built the first AI module for the.
00:01:49 Jess Melanson
Cred, and it's called Carmen. That's the name of our module in our platform. And when I say for the electric grid, I mean we've customised the product to run AI models on the electric infrastructure. And So what that means is we took an NVIDIA processor and NVIDIA is our partner in this in this product.
00:02:10 Jess Melanson
And we've customised it, so we made it smaller and lower cost we.
00:02:16 Jess Melanson
Made it cooler. It operates at a lower temperature, it uses less energy and so we've done all these customizations to take a processor and make it more rugged and and allow it to operate on the electric grid where things, you know, devices are out there for a decade, 2 decades at a time and extreme temperatures.
00:02:34 Jess Melanson
And the other thing we've done is we've added a a layer of industry specific software to that module. So we take all that really granular complex waveform data that many devices capture on the grid and we make sense of it. We put it into context, we philtre it, we make it usable.
00:02:54 Jess Melanson
To a platform layer that allows utility data, but importantly anybody else to build AI algorithms and models that live on that module. So it's a, it's a customised AI based module for the electric grid and it can be embedded in hardware, other people's hardware, not utility.
00:03:14 Jess Melanson
Is not invidious, and so that's the product. It's a first in the industry and you know our goal is to really transform the way utilities are able to buy, compute and and invest in AI for their infrastructure.
00:03:28
Sure.
00:03:30 Chris Sass
Alright, so you managed to get just about every cool buzzword in your opening statement there, and you got some cool brands like NVIDIA doing stuff with AI. So so got everyone's attention when you say in the electric grid, that's a pretty broad statement. Help help us understand what AI in the electric grid means. Where does it live and what are these chips that you're doing where?
00:03:52 Chris Sass
Where are utilities putting these?
00:03:54 Jess Melanson
Yeah. So, So what we we focused on the edge of the grid 1st and we did that for for two reasons. One that is where the most of the emerging complexity is on the grid. And so you guys and your listeners obviously know that distributed energy resources and you know storage and generation and things.
00:04:14 Jess Melanson
That are showing up at the edge of the system that previously weren't there, obviously, and that the grid had not needed to be concerned with.
00:04:24 Jess Melanson
And the second thing is that that's the area of the grid that had where utilities have the least visibility and the lowest sort of that they lack tools to manage all of that. So we started at the edge and we're embedding this AI module in electric metres. Having said that, this module can live at any part.
00:04:43 Jess Melanson
Of the system and really it can be useful to anything that electricity runs through. But we've started with utilities and we've started at the edge of the grid based on our experience as a company and the needs of our customers.
00:04:58 Jeff McAulay
Jess, can you tell us more about what you think the killer app is as in the application where you're going to use AI and this complex waveform data to deliver value to the end user?
00:05:11 Jess Melanson
So there are there are three broad categories that utilities who are are early adopters are looking at when they adopt this technology. So the first bucket is distributed energy resource integration and and I'll talk a little bit more about how AI helps there specifically, but it's this full range of.
00:05:30 Jess Melanson
Seeing where deers are understanding what they're doing to the.
00:05:34 Jess Melanson
Predicting what they'll do next, modelling different scenarios and making a recommendation for a better charge discharge. You know execution for DER, so that's one big bucket. The second I would just broadly call visibility, Chris, you were impressed by my buzzwords that add digital twin to the list.
00:05:55 Jess Melanson
But just this ability to sort of understand their assets at a granular level and get a better sense of their capacity, their health, you know their usage, etcetera. And then the third category, which I do think could prove the most valuable of all is.
00:06:12 Jess Melanson
Anomaly detection, understanding what's going wrong, being able to see in the waveform, things that are indicative of equipment failure or pre outage conditions, and obviously job number one for utilities is reliability. And so that could be really transformative. Any one of those.
00:06:32 Jess Melanson
Categories of benefits.
00:06:34 Jess Melanson
Pays for the device itself, but the benefit and the beauty of investing in significant compute and an AI based module is that you don't need to stop there. I mean we've we've already discovered things we didn't realise we were going to find in that data. And so part of what we're trying to lead utilities to with this product is the ability to keep doing.
00:06:55 Jess Melanson
More and more, and so that hasn't always been present in Gridman investments. And so so those are the, those are the first areas of killer apps. But in our mind, the real sort of killer capability here is is just the the full range of of AI models.
00:07:12 Jess Melanson
Utilities and many other partners are now going to be able to build right there at the source of the data.
00:07:18 Chris Sass
How is this different from maybe a smart metre strategy or a strategy where I already have some apps that run at the edge of the metre? How? How is this technology and is it overkill or is that what what we need to be doing today to?
00:07:31 Chris Sass
You know, meet a transition of energy.
00:07:33 Jess Melanson
Yeah. I mean, we firmly believe it's the latter. We are obviously betting on more compute and we're betting on AI being a transformative technology for the grid.
00:07:46 Jess Melanson
But that is certainly the debate, right. There are technologies out there that offer less compute at lower cost than they say that they're sufficient for the use cases that we're looking for. So it's really up to the customers in the market to decide. But we feel very confident as you look at not just the utility landscape, but other industries.
00:08:06 Jess Melanson
Obviously, AI is transforming other industries and I know we all our minds, or at least mine always goes to language models and ChatGPT, which is the most sensational version of AI that we see in our lives.
00:08:18 Jess Melanson
But there's all this sort of assist capabilities and human AI interactions that are really, you know, whether that's in our navigation systems, on our phone or in our cars or in the Amazon warehouses that allow us to get a, you know, product in a day that are already out there. And so that's more analogous to what we're talking about.
00:08:40 Jess Melanson
On the grid, which is this evolution of tools that helps utilities.
00:08:45 Jess Melanson
See things better. So I'll just use an example of electric vehicles. Know where all your electric vehicles are in real time and know where they're plugging in. There are ways to figure that out today, with centralised AI, with data, with customer programmes. It's not going to be as complete or good, but you can get an approximation for sure.
00:09:05 Jess Melanson
But what AI helps you do is evolve that capability over time, so it's going to learn and get better and better and better, much faster than your other types of applications. And it's learning from data right there at the source, so you don't have to pay huge data transmission and storage cost to keep training that model and keep having it improve.
00:09:23 Jess Melanson
But then you can really keep progressing to what is that EV doing to power quality at a local level and at the University of Michigan? We've already found some surprising things about how different chargers and vehicles are negatively impacting voltage levels on the grid and could cause reliability challenges. So you get to this deep understanding of the operational.
00:09:44 Jess Melanson
Impacts of an EV. Then you can start to predict behaviours. You can you can model multiple scenarios. What happens if your heat pump and your EV turn on turn on at the same time. So you have that digital twin capability that evolves.
00:09:58 Jess Melanson
And then you can optimise assets you know, figure out what a better charging schedule might be. Given all that you know and all that you can predict.
00:10:07 Jess Melanson
So you we started EV identification. Yep. Lots of people are going to say that someone might say I can buy a cheaper processor and achieve that goal. But if you want a native AI capability and you want the ability to run that full spectrum of capabilities, you need a really robust module. And I just went through EV's. You could talk about solar heat pump. You can talk about resiliency.
00:10:30 Jess Melanson
You could talk about transformer loading. There's no end to the models that you could run locally.
00:10:35 Jess Melanson
And So what we're really selling is the ability to have a a software defined AI enabled infrastructure which is quite different than say MI one dot O which you mentioned.
00:10:48 Chris Sass
Now, AI is still early, right? I mean, we've been doing a I guess you know, when I was in university, we were doing machine learning and things that would be called AI today, but for for where people are going, you you just gave some interesting.
00:11:01 Chris Sass
Antidote of what could be so is this a tool that will be used by utilities to go and and adjust rates? And you see that the AI will help change like how how they're asking for approval to get higher rates for ratepayers and things like that. Is that part of what this will be used for?
00:11:19 Jess Melanson
Uh.
00:11:21 Jess Melanson
I mean, I think it will be.
00:11:22 Jess Melanson
Used.
00:11:23 Jess Melanson
For a more informed discussion on all sides right, there's a lot of guesswork and estimation in things like interconnection. That's why it's slower. That's why it's frustrating for many parties, there's a lack of information. You know, there's a there's, there's some kind of.
00:11:43 Jess Melanson
You know, low data scenarios being run about what what will be the impact of this system on the grid. For example, if you have AI based infrastructure, you don't have to really guess about those things nearly as much. You have visibility into system conditions, you have predictive models that can.
00:12:01 Jess Melanson
Help you understand what's going to happen next. And so in our view, the way that AI is going to impact things is more subtle than like, you know, suddenly the robots are talking about the rate case or whatever. It's more like.
00:12:17 Jess Melanson
You know, it's not autonomous driving where you go to sleep at the wheel, it's lane assist and brake assist and these this evolution that helps make things that the humans are already in control of, make them a little easier, make them a little more, well, a little better informed. And so that's that's sort of the the way we think this is really going to start to hit the regulatory realm.
00:12:38 Jess Melanson
And just utility operations as and planning. It's just a lot better information and predictive capabilities on their infrastructure.
00:12:47 Jeff McAulay
For those at home playing buzz buzzword bingo, I have one more to add, which is transactive energy. So we've we've talked about information out maybe from the edge to the utility. Obviously with your inherently safe distributed architecture where you're doing the compute locally.
00:13:03 Jeff McAulay
How much of this could also be control signals or pricing signals and to, to Chris's point, a lot of the smart metre 1.0 was hey, now we have 15 minute interval data so that we can charge you on a time of use basis which is maybe not the the great feature that everybody wants.
00:13:24 Jeff McAulay
In their home. But the promise here is maybe doing that where you don't have to pay extra attention to the rate and you can have two way communications and if not a direct control signal for like a demand response event, at least a price signal. How much is that included in the scope of your vision?
00:13:42 Jess Melanson
Yeah, I think that's sort of the end state of those Dr management tools that I mentioned earlier. But it is the end state in that. I think when we've tried to do transactive energy pilots and things before, we had the data and infrastructure and control architecture to do it.
00:14:01 Jess Melanson
You know, it ends up stuck in pilot land because the scalable model isn't there yet and also where it falls down is.
00:14:08 Jess Melanson
Well, what's the customer? How does the customer engage? What's their incentive structure? How do we keep various parties and the Dr companies happy about this?
00:14:18 Jess Melanson
So it's hard. It's hard to pull off. It's a, it's sort of a end of the evolution or toward the end.
00:14:22 Jess Melanson
Of the evolution state of things.
00:14:24 Jess Melanson
But this type of capability that we're talking about is foundational to being, to being able to do it, and it helps you along that path. And again, this progression of.
00:14:34 Jess Melanson
To do transactive energy, you need to know the state of your grid. You need to know the state of the assets, both sides the customer needs to know it, but the utility needs to have a sense of it as well. You need to be able to run better scenarios. You need to understand local conditions. FERC has required this of utilities and then you need to communicate that and get the feedback loop.
00:14:54 Jess Melanson
So what happened?
00:14:56 Jess Melanson
Even in more simple doctor, that feedback loop is pretty bad, right? You have you have aggregators who wait a day for the information about what happened. They don't know which customers to nudge further or not, right. So there's all kinds of sand in the Gears of this progression toward transactive energy that the root cause of which is.
00:15:16 Jess Melanson
Poor data, poor visibility, and pretty latent understanding of what's happening. I've been talking a lot about distributed AI and I just.
00:15:24 Jess Melanson
I want to.
00:15:25 Jess Melanson
Zoom out and say that that there's these features of having the AI running on the on the architect, I mean on the infrastructure itself that are really important. It is faster, it is lower cost because you have to ship all your data back.
00:15:40 Jess Melanson
There's a resiliency element there because it can operate, you know, at the edge. If it loses, you know, connectivity for for a period of time. There's a security element as we talk.
00:15:50 Jess Melanson
Talked about and then there's just a results element. Like if I'm doing Dr forecasting solar forecasting, for example, an edge model that can understand more quickly local conditions and and model those is going to be better, give you better results than if you're waiting for a kind of a centralised view of things only so.
00:16:11 Jess Melanson
This distributed piece of the AI architecture is really important, especially for critical infrastructure like the distribution grid.
00:16:22 Jeff McAulay
That's great. And what I love about this as well is there's a deep lineage here. So utility data as a company goes back to 2012, I believe you've been there since 2018. So this is not a rogue band of coders spinning out of open AI to try to figure out what other data they can feed the machine.
00:16:43 Jeff McAulay
This is coming from people you've you've been working with utilities.
00:16:47 Jeff McAulay
For over a decade, it's from those deep relationships, customer engagement, understanding of the sector that you're building something to fit a need. Can you talk about what the first generations of the company we're focused on and what led to this being the new focus?
00:17:04 Jess Melanson
Yeah.
00:17:07 Jess Melanson
Yes, you're absolutely right. This, you know, we started this company over 10 years ago.
00:17:13 Jess Melanson
And the first product was a machine learning based voltage optimization software package that ran at the substation and so.
00:17:24 Jess Melanson
The underlying premise of what we did is the same as today. How do I take all that grid data and real time make sense of it and use it to make better decisions and? And so we did that in a very operational context. That software is still running today and it it decides the voltage levels at the substation on on down.
00:17:45 Jess Melanson
So that is both a very hard you know it's it's hard to earn utilities trust to allow software to make operational decisions. So that took a lot of time and growth to be able to do that. But it also gave us this sort of unique skill set of how do you make sense of all this data? How do data scientists and software programmers take?
00:18:07 Jess Melanson
You know current and voltage and turn it into better outcomes. It's a it's a unit.
00:18:12 Jess Melanson
Ink skill set and we were applying machine learning and AI to that data way before most people that we ever ran into. So we were pretty early to that front. So we have this DNA of being able to understand grid data and being able to turn it into grid outcomes and having trust with utilities that we, we get their business, we understand their stakeholders.
00:18:33 Jess Melanson
We have a lot of folks who worked at utilities and worked at the Regulatory Commission, and so you just earn an appreciation for why it's so hard to adopt new technology in this industry and what constraints utilities are facing.
00:18:47 Jess Melanson
And so with all that experience, we gravitated toward the edge, and we decided we needed to build our own platform compute module for the grid, and we found NVIDIA as a as a partner in that, and they had a wonderfully relevant skill set that was totally different than ours, right? They've transformed industries.
00:19:06 Jess Melanson
Across the globe, they are the undisputed global leader in AI and accelerated computing. But they didn't understand the electric grid the way we did, and they didn't.
00:19:17 Jess Melanson
Understand utilities and their regulatory constraints the way that the way we did, but they saw the exact same thing, which was infrastructure that needed to become AI enabled. And so it really was a perfect partnership and marriage of skill sets and so, so with this custom module we're building and our first hardware integrations.
00:19:38 Jess Melanson
That that's now exactly what we're doing together.
00:19:42 Jeff McAulay
I feel like the conventional wisdom from venture investors would include things like don't rely on federal funding. We can't invest in businesses that sell to utilities. You've proven an ability to scale despite the the naysayers.
00:20:01 Jeff McAulay
Is that still good advice to startups or aspiring entrepreneurs listening today? Or is there something you know where, hey, actually, if you do it right, selling to utilities actually isn't that bad?
00:20:16 Jess Melanson
That's a great question. Well, it's not for the faint of heart. I'll.
00:20:19 Jess Melanson
Say that.
00:20:22 Jess Melanson
You know, for us, this is just the space that we collectively know. Like I worked in the utility for almost a decade. You know, we, we've all a lot of us have worked in this space. So it's it's kind of what we know. So we sometimes say if we can't sell AI to utilities, no one can. And so that's kind of, you know, for better or worse what we have.
00:20:42 Jess Melanson
Set our sights on as an organisation, we're very mission driven. We're very.
00:20:48 Jess Melanson
Climate mission driven as an organisation and so really what gets us up out of bed every day is the idea that.
00:20:56 Jess Melanson
This infrastructure has to get smarter. It has to get lower cost that we can't just rebuild everything. You know, at the cost of 10s and 10s of billions of dollars in every jurisdiction to get ready for this low growth. And this complexity and so.
00:21:13 Jess Melanson
You know, sort of like somebody has to do this and we feel like this organisation is really well suited to do it. I will say to your question about investors, you know, obviously the the.
00:21:24 Jess Melanson
Utilities are really hard to sell to, but once you do, they buy in very big scale and if you can really prove a new industry standard, they don't compete with each other, they they standardise. And so we do think this bet that an NVIDIA based module which is the lowest risk AI infrastructure to standardise on by a long shot.
00:21:45 Jess Melanson
Is actually a risk mitigating investment for utilities. It is the lowest risk.
00:21:50 Jess Melanson
Most you know responsible way for them to start to get into AI, enabling their infrastructure and so.
00:21:59 Jess Melanson
You know, that's what. And we have a really good set of investors which include NVIDIA and Microsoft and companies that take a pretty long view of of AI and and industry transformation. And they see the same thing. This is going to happen and someone's going to figure it out and and they've placed a bet on us that we're going to figure it out with our utility partners.
00:22:21 Jeff McAulay
We've talked so much about utilities, it's clear that you have a depth of understanding and this really comes from you've spent over a decade working in and around utilities, and before that, you have a background in in a different kind of public service. So tell us about your personal journey before utility data, how you came to better understand and kind of really be.
00:22:45 Jeff McAulay
An insider in the utility sector and how that's informed what you're doing today.
00:22:52 Jess Melanson
Yeah. So my you know, I I went to public policy school and I worked in the public sector and and I was a policy generalist and I was working for the Governor of New Jersey as a policy advisor, and they handed me energy on my first day on the job, which, you know, the beauty of being a 20 something year old.
00:23:12 Jess Melanson
In a in a sort of a political policy job is there is no experience required, a substantive experience required. So they just handed me this area.
00:23:21 Jess Melanson
And I just was hooked on it because it touches everything. It's it's economic development, it's health, it's environment, it's really complex and it's essential, you know, it touches everybody every single day and in increasing ways, you know, when I started.
00:23:41 Jess Melanson
20 something years ago we were not as reliant on electricity as we are today. I mean everything from the Internet to charging your phone to now, charging your vehicle to your heat. We are really, really as a society for good reason. Getting deeply invested in in electricity, in the electric grid and so.
00:23:59 Jess Melanson
From the standpoint of wanting to make an imprint on the world, you know, I feel like when I talk to.
00:24:05 Jess Melanson
Policy students thinking about what area to to specialise in. I just think it's endlessly fascinating, and because it's at the centre of climate change, we need all the smarts and dedication we can get. And so.
00:24:21 Jess Melanson
You know it's it's it's a really unique, it's a really unique industry and I think utilities are certainly often misunderstood especially by technology vendors who are trying to sell them new tools. It's not easy to take a chance inside of utility. It's not easy to.
00:24:40 Jess Melanson
Adopt new technology inside of it.
00:24:42 Jess Melanson
Utility, which makes sense. They serve a they they deliver to customers, deadly products that need to have constant, you know, reliability that that is a very difficult thing to do and you know their economic structure says that doing something imprudent is about the worst thing you could do.
00:25:02 Jess Melanson
Right. So we totally understand why it's challenging for them to adopt new technology. And I think that understanding helps us collaborate with utilities because we're not coming in there saying, come on guys, look at all these other industries using AI, you're just behind, we get, we get that we need to make a case to regulators.
00:25:20 Jess Melanson
There and that we need to talk to DOE about the importance of helping accelerate this type of technology and so.
00:25:28 Jess Melanson
So for me, just having kind of grown up in the industry, I think it really it really helps what we're doing that so many of the folks at utility to have done the same thing and they they understand the partners we have to work with to get.
00:25:40 Chris Sass
This done all right as we bring this together, we're up at time. I'd like to have a crystal ball question.
00:25:48 Chris Sass
And in your case, you're bringing new technology out. You've got this NVIDIA chip.
00:25:53 Chris Sass
I I guess the question I have is how soon do I see this mass adoption of this technology? I mean obviously as your role in your company you would love it to be today.
00:26:03 Chris Sass
You're still early.
00:26:05 Chris Sass
12 months, 24 months, 36 months. When am I seeing this across major utilities?
00:26:13 Jess Melanson
So we are going to have.
00:26:17 Jess Melanson
A major uptick in adoption of this.
00:26:21 Jess Melanson
Technology.
00:26:23 Jess Melanson
In the next three years.
00:26:24 Jess Melanson
Yes.
00:26:26 Jess Melanson
And I say that because it will be driven by big infrastructure choices that utilities have to make. They have to replace ageing metres. They have to upgrade Transformers and various equipment on the on the electric grid and so.
00:26:42 Jess Melanson
So when they make those decisions, I think what we've started to do in collaboration with our early adopters is help utilities understand.
00:26:49 Jess Melanson
That they need to make a choice about the compute that's inside that infrastructure and they need to make decisions about how they're going to run AI models on the grid. And so there's a forcing function here, right? It's not like we just have to go door to door telling utilities, you know, here's the Carmen module. They're making big decisions and the utilities.
00:27:10 Jess Melanson
We work with understand this. They understand that the choices they are making in the next two to three years about about how, where and how and what to buy on their own.
00:27:20 Jess Melanson
Infrastructure are going to determine whether or not they become a bottleneck for this energy transformation or not, and so the stakes are the stakes are pretty high. I should mention one more thing, which I didn't I didn't mention our our most our our hardware partner, our first adopter hardware partner which is Hubble.
00:27:41 Jess Melanson
And so we're embedding this module in an A Clara metre, and Hubble is a company that makes almost everything you see on a distribution grid. They make all this equipment and so.
00:27:53 Jess Melanson
You know the the the other reason I'm confident in the.
00:27:58 Jess Melanson
Accelerated adoption. This technology is we have great partners, NVIDIA stands really strongly behind this. They are going to produce the modules with us and these hardware companies like Hubble are going to produce for really reliable hardware. And we're just going to put this technology together and give utilities a lot of choice and you know.
00:28:18 Jess Melanson
Much more of an AI easy button than they've ever had, and so we think that the adoption is going to really accelerate both as they make those.
00:28:27 Jess Melanson
Technology investment decisions and as they see the adoption or the use cases and the applications that start to develop over the next year or so, if you put those two things together, we feel really bullish on the the pace of adoption.
00:28:43 Jeff McAulay
Jess, thank you so much for the conversation today. I feel like this has really been an insider's guide into the interface of utility decision making the next generation of truly smart.
00:28:54 Jeff McAulay
Leaders and we covered a wide range of applications, voltage management, rate design, M&V, distributed generation, EVs. We touched on all of it with a new lens of how hardware is going to improve the lives for ratepayers and also utility programme managers. I can't imagine anybody else.
00:29:14 Jeff McAulay
Giving us that kind of guided tour through so many different topics on behalf of our listeners. Thank you so much for joining us today.
00:29:22 Jess Melanson
Thank you. It's a great conversation.
00:29:24 Chris Sass
Thanks for our audience. We hope you've enjoyed this conversation. If you enjoy what we do here at insiders guide to energy, please like us, subscribe to us and follow us on YouTube. That helps us get more guests. It helps us bring the content you want. It's the best thing you can do to thank us for bringing you this content and we look forward to seeing you again next week.
00:29:42 Chris Sass
On the insiders guide and energy, bye for now.