Kenneth Munson with Rhythmos.io

SUMMARY KEYWORDS

Industrial Talk Podcast, Ken Munson, Rhythmos, grid edge technologies, electric vehicles, load growth, distribution grid, machine learning, advanced analytics, utility visibility, service transformers, demand response, regulatory environment, smart devices, distributed energy resources.

00:00

Scott. Welcome to the industrial talk podcast with Scott Mackenzie. Scott is a passionate industry professional dedicated to transferring cutting edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hard hat, grab your work boots and let's go all right

00:21

once again. Welcome to industrial talk. Thank you very much for joining the number one industrial related podcast in the universe that celebrates you industry professionals all around the world. You're bold, you're brave, you dare greatly, you innovate, you collaborate, you solve problems each and every day. You are making the world a better place. Thank you very much for what you are doing. We are broadcasting on site, distribute tech here in Dallas, Texas, and it is a monster of a show. If you're in the world of utilities, transmission gear, stuff like that. This is the show for you, just because, well, you get great people like Ken. Is it Ken or Kenneth?

01:01

Only when I'm in trouble with my mom. Is it Kenneth? Okay, well, yeah,

01:05

your, your your thing says, Kenneth,

01:09

yeah. Well, I'm safe here. I'm

01:12

not gonna start chirping and barking at you. You're taller than I am. You got more hair, you know, just you're younger, you know, all of that stuff, having a good conference. It's just started.

01:22

Yeah, it has just arrived. Yeah, looks like it's packed again, lots of people, more vendors than ever.

01:30

Yes, I'm relegated to sort of the, I don't know it. I had to change my time. It's a time zone change here, yeah, just because it just big, big event. So anyway, it's all cool. All right, for the listeners out there, can give us a little 411 on who you are,

01:47

02:35

Rhythmos, that's Greek. Everybody, just FYI. All right, for the listeners, outside of the fact that you probably misspelled the name, R, Y, R, h, y, t, h, there you go, M, O, S, I'm looking at his car, and I still misspelled it. Yeah, that's, that's the kind of guy that you're hanging out with with right now, take us through a little bit about what that

02:58

means. Well, I guess we saw an interesting opportunity, having been playing around the grid edge space for a number of years, one of the untapped areas, I had to back up grid edge.

03:10

Grid edge define that right

03:12

04:05

I don't know how, being a recovering journeyman transmission lineman, I'm very linear in my thinking when it comes to power, power generation and the delivery of that power, you know, I've got a centralized power solution, transmission, substation, distribution, so on, and to the end consumer, whomever it might be, this whole distributive energy and and if I was a system operator, I don't know how you do it. It's a

04:39

challenge. I don't it's a bi directional challenge that all utilities have started to wrap their head around. And 10 years ago it was or 15 years ago, it was a big challenge. Today, it's becoming less so because of automation, because of AI, because of, you know, machine learning, all of those technologies are enabling the you. System planner, the distribution operator, the programs group within a utility to have better forecast ability, a better understanding of the assets on their grid. But one of the big challenges that we saw, frankly, was with all this new load growth, utilities, which is our primary customer, struggled with visibility below the substation, like there's tremendous amount of machine learning technology, derms, ADMS, that really helps solve for the central operation down to the substation. And there are some that focus on feeder as well. But for the most part, it starts to go, I'll use the phrase blind. There's a lack of visibility, at least granular visibility at the service transformer level. And if you look at the since, I don't know, since covid, basically, service transformers have quadrupled in cost. Have lead times that now are, yeah, 16 weeks, historically to now 172 weeks. And so there's a great challenge. When you couple that with this kind of on flux of new load, right? It's coming at a pace that's driven not by utilities.

06:13

I'm sorry, there's now we're doing, How about them apples? Look at you. You're just you're disrupting an ongoing number one industrial related podcast. And you know I would do that? Yeah, absolutely, you look fantastic. Shut the front door.

06:32

Sorry about that. That's all right. I haven't seen him in years. Yeah, no, no. So we saw, like I said, an opportunity to help build an enabling platform, really, that brought granular visibility for the utilities to the load that's impacting both spatially, so geographically, right, and temporally over time that how is that load impacting those Transformers specific to that asset nameplate rating, right? So in doing so, if we could use machine learning, advanced algorithm, a little bit of AI, then we could optimize that load, spread it like peanut butter over a broader period of time, so that you could have greater adoption of whatever smart device or electric vehicle below the meter, der right distributed energy resource, and not have it overload that asset prematurely, right? So our platform serves as a as a technology that helps planners, but it also serves as an operational element. We actually create a dynamic operating envelope on the distribution network that we can the utility can signal into, yeah, and from there, then have greater granular visibility on those assets that are wanted.

07:52

I was onto the grid. It sounds great, don't get me wrong, I think it's fantastic, and it requires that level of sophistication to be able to to manage that real time demand, load, whatever it so you're able to take your solution, your your edge, your grid edge, and be able to communicate with the system operator. How difficult is the setup? How do you, I mean, I get it, let's say I have my car and it is, it's charging and now it's discharging and it's doing whatever it needs to do. I need to have that ability to be able to sort of also communicate how quickly does your solution set up. Yeah.

08:41

So we saw an interesting opportunity in the market where the majority of the technologies required telematics or a custom API to integrate a vehicle or downstream technology onto the distribution grid. What we do is we went to the AMI. So to the advanced meter infrastructure, right? We grab the data that's already being used primarily for billing, right? There's 80, 90% of the utilities nationwide have smart meters in place. Ami, meters in place. So we saw the natural points to go there, grab that data, use advanced analytics, machine learning, to profile, characterize that data, right, and then act on it, assess what impact do those load curves look like, right? And disaggregate an electric vehicle or a smart device from the native load of the home, and then allow the utility to act on that right and understand what the impact would be. So our setup is actually we pull it out, of the operational realm. So we're not trying to build an algorithm that sits on a meter, that operates in real time, because when you do that, you're effectively trying to predict human behavior, which is, yeah, a very tall task it is. But what we've done is we've said, Well, there's better there's greater confidence in the data if you pull up a level right, if you begin to look at the. The temporal nature of load on the service transformer for an aggregated set.

10:05

So you're on the other side of the meter. We're on the front of the meter, yeah, we're above the meter. Yeah, right, right, exactly.

10:11

Sure, sure. And that's where we do our advanced analytics. And that gives us greater confidence it actually give it gives us greater defensibility in the regulatory environment as to what the characteristic of that load and the predictability of that load is going to look like in a winter peak or or a summer peak, right? What that growth curve actually and the growth curve what it actually looks like for the utility

10:34

you bring up an interesting point. Well, say, don't get me wrong. Well, Said, I believe, and this is because I'm very linear in my mind. The way I look at power, and way I look at the transmission of that power, there is a heavy regulatory component to whatever happens. And it, it's, it's, it's a level of risk. It's happening. All of this wonderful stuff is happening. But there's a risk if I come home, Joe, six pack me and I flip that switch and that light flickers, because all of this wonderful stuff is happening, I don't really care. How do you deal in the world of the regulatory environment and and sort of manage that risk?

11:26

14:21

How do you do with the historical data? How are you how are you populating that you can't just flip a switch and then be able to make those analytical decisions of saying, yeah, so

14:31

we'll ingest the AMI data. So we'll go and we'll grab the data that the utility already has, will then characterize that data, will disaggregate that data from the native load of the home, and then we'll look at what that load impact is on specific assets on the distribution network.

14:46

Yeah, what do you see it going, what's, what's your future hat look like? I mean, you're still, we're still at the beginning of this. I mean, oh

14:53

yeah, absolutely. I think so long, yeah, I think AI will. You know, that's a buzzword in a lot of ways, utility sector. But. It will continue to play an even more important role, and especially around forecasting, you know, but it also, you know, machine learning and the technologies, the cloud based technologies like ours, will further enable utilities to be more efficient in the way in which they get data. It will help their marketing programs and their program groups to have greater adoptability. You know, we talk about electric vehicles because, well, at least up until, you know, the inauguration, you know, there was a big push that's yet to be determined. How that will play out, but I think consumer demand for electric vehicles will continue. A lot of those initiatives are driven at the state level, and I think that train's already left the station in a lot of ways, so we will see that growth. But more importantly, you are seeing the electrification of everything, if you will, the smart device, right? That's going to continue to drive load growth, and that's going to need to be managed.

15:56

Yeah, you were awesome. You're smarter than I am.

16:01

I don't think so.

16:06

How do people get a hold of you there? Ken

16:07

Yeah, LinkedIn is the best way to do it. KENNETH Munson, at LinkedIn, and

16:12

also, you have a website out there, yeah? Rhythmos.io.io, I like that. Yeah. Yeah. It just says technology, yeah, you know, well, you were wonderful. Thank you very much. Sorry for the confusion in the beginning and rude interrupted by that guy named Alan. That's all right. Now I'm gonna interrupt him, because he's right in the middle of an interview. All right. Listeners, once again, we're broadcasting from distribute tech here in Dallas, Texas, who get great people just like Ken making an impact. That is what they're all about. We're brought to you by Siemens. So go out to siemens.com Find Out More they got. Siemens is

16:49

everywhere. So Siemens is a great

16:51

company, yes, all right, thank you. We're gonna wrap it up on the other side. Stay tuned. We will be right back.

16:58

You're listening to the industrial talk Podcast Network,

17:06

Ken Munson. The company is rhythmos.io, I hope I said that right the name is straight there. It's on a stack card right there. I'm looking at it. We're talking edge. We're talking about leading the edge. We're talking about using AI to be able to manage that. Ed, within the grid structure of utilities, it's cool. There's so much going on in the world of edge and all utilities and everything in between. That was distribute tech, that is a must attend event. I will be there. I will be broadcasting. I will be telling your story because it needs to be amplified. So look for me at this year's distribute tech in February of next year, 26 I can't believe I'm talking about that. All right. Be bold, be brave. Derek greatly hang out with Ken. Change the world. We're gonna have another great conversation shortly. So stay tuned. You.