“Why isn't everybody that's using energy accurately collecting data on the source of their energy and also the use of their energy? And then saying, what is the accurate carbon footprint of that energy? And what, if anything, should I be doing about it?"
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Episode 113 is a conversation with Lincoln Payton, CEO of Cleartrace, a carbon accounting startup.
We dug into the three phases of ESG, why hourly energy supply and consumption data is so important for real estate moving forward, how Cleartrace’s product sits in the middle of those two sides of the decarbonization equation, and more.
So without further ado, please enjoy the Nexus podcast with Lincoln Payton.
Mentions and Links
- BNP Paribas (3:00)
- Cleartrace (3:44)
- Brookfield Renewable (30:33)
- EDF (45:40)
- Tenaska (45:43)
- Exelon (45:44)
- The Boys in the Boat by Daniel James Brown (1:00:14)
- The Energy Switch by Peter Kelly-Detwiler (1:01:45)
You can find Lincoln on LinkedIn.
- The founding story of Cleartrace (5:35)
- Why data is so important for decarbonization (11:22)
- How we go from old standards to gaining access to hourly energy and carbon data (27:15)
- How data can be used to plan out this roadmap (48:35)
- Integration into the real estate tech stack (54:55)
- Carveouts (58:32)
👋 That's all for this week. See you next Thursday!
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Note: transcript was created using an imperfect machine learning tool and lightly edited by a human (so you can get the gist). Please forgive errors!
[00:00:03] James Dice: hello friends, welcome to the nexus podcast. I'm your host James dice each week. I fire questions that the leaders of the smart buildings industry to try to figure out where we're headed and how we can get there faster without all the marketing fluff. I'm pushing my learning to the limit. And I'm so glad to have you here following along.
[00:00:31] James Dice: This episode is a conversation with Lincoln Peyton, CEO of queer trace a carbon accounting startup. We dug into the three phases of ESG. Y hourly energy supply and consumption data is so important for real estate. Moving forward. How clear trace has product sits in the middle of those two sides of the decarbonisation equation and then much, much more. So without further ado, please enjoy the next podcast with Lincoln Peyton. Hello, Lincoln. Welcome to the nexus podcast. Can you introduce yourself,
[00:00:59] Lincoln Payton: [00:01:00] James? Yes. Good, good afternoon. I'm delighted to, to be with you today. Lincoln Peyton. Uh, I'm talking to you here from Connecticut, just outside New York city. Uh, it's not a Brooklyn accent, as you can probably tell originally, born and raised in, in London.
Uh, very international parents though. And, and that kind of led me to, to moving over here with my. My first go around profession, uh, that I, I retired from a few years ago before, uh, before coming, uh, to this very exciting decarbonization technology opportunity space. So, uh, my background is investment banking.
I grew up in the energy vertical of investment banking. All right. Goes back to the city of London. Um, I'm dating myself here, but my first boss wore Ebola hat and had a full umbrella. So it's kind of Mary poppin style . But, um, but I grew up doing all the usual things, strategic advisory M and a all forms of capital raising around the energy vertical.
Okay. Cause over the [00:02:00] years that that evolved from purely a hydrocarbon type of, uh, fundamental to much more the electron and the renewable space. Mm-hmm um, I always like, you know, banks tend to be big platforms, James, and, uh, but I always like building. Um, new things in between the gaps of those big platforms, if you like.
Um, when energy became an asset class in its own, right built on and off exchange risk management platforms, um, principal investing businesses, specific advisory units, uh, moved over to the us, uh, 30 years ago with a young family expecting to be here for, uh, just a couple of years. Typical big company move and it worked out very well.
It worked out very well, family wise, uh, and it worked out well professionally and, and here we still are. I've now been in the us longer than I was in the UK. Okay. Um, uh, you know, retired from, from banking. Uh, three years ago, I was at that point running investment banking, uh, [00:03:00] for BNP par bar, the largest Eurozone bank in, uh, in the Americas.
Uh, I, I ran the energy franchise, uh, globally and sat on the XCO of the bank. So I saw it's fair to say. I saw a lot of banking, finance advisory, risk management around the energy space. Got it. Uh, and then I, when I retired from that wanted to, to be part of the very concrete, sensible. Evolution to a renewable world, not all the, the, you know, the, the hot air, frankly, metaphorically and literally, but, um, the biggest gap that I saw from those different tangents I'd been around the energy space was high quality data.
Uh, and that's kind of what brings me, brings me to clear trace and where we are today. Cool.
[00:03:48] James Dice: So you're from London. You grew up in London. I have to ask you what color
[00:03:52] Lincoln Payton: do you bleed? Blue Chelsea um, now I, and I have to say I'm very happy. You know, I was [00:04:00] a west London, a west London guy. Okay. And I used to go to Chelsea when it, it was not expensive to get in.
Uh, and you stood and got wet while you watched Uhhuh. And by the way, people were a lot less well behaved than they are now. yeah. Yeah. Um, but it was always a cause of consternation cuz my, my, my wife was a man United supporter. Okay. So you know, it, it caused conflict in the, in the family. I'm sure. I'm
[00:04:25] James Dice: sure.
Yeah. My best friend, uh, is a man United supporter and it causes conflict in our relationship
[00:04:33] Lincoln Payton: on a weekly basis. So tell me who who's, who is it that you are supporting? Uh, so I believe red,
[00:04:40] James Dice: uh, north London Arsen.
[00:04:42] Lincoln Payton: Oh yeah. Well, they had a lot of they've had a lot of success lately, so yeah, it was mostly
[00:04:47] James Dice: when I was a child, you know, I was growing up and there was a player called te Ray, uh, French guy.
That was just my hero. It was Michael Jordan of my childhood is basically what it was. Um, him and Kobe [00:05:00] Bryant. I was just there, they were my heroes. Um, and he still is he's he's he was an amazing player. So he got me onto the arsenal train. And then ever since he retired, it's been like totally downhill from there, but it's kind of like on the up again, I think
[00:05:14] Lincoln Payton: right now.
So, yeah, look, I think so he was an amazing athlete and you know, I, cuz I spent a lot of time. Um, in and around France, he was, he was a national hero. Oh yeah. Of absolutely the Kobe and Michael Jordan proportion. So, oh, totally phenomenal. Phenomenal guy. Anyway,
[00:05:32] James Dice: this is not soccer podcast. Um, so I'd love to hear a little bit, so you, we were not one of the founders of clear trace you've joined since the founding.
Can you talk about the founding story a little bit and catch us up? What was it like when you
[00:05:46] Lincoln Payton: joined? Yeah, absolutely. So, um, When, when I retired from banking, I was looking around for something to do that would, would frankly be productive. Also keep me out from under my wife's [00:06:00] feet. And I was helping a, helping a friend who runs an energy risk management platform, uh, down in the Austin, Texas area with a, with some things good friend we'd worked together before.
Uh, and he basically said, well, look, if you, if you don't wanna go back to banking, um, here's something completely at the other end of the spectrum. yeah, they had spun out. This little startup. I think it was eight people at the time in a very cool, uh, like a caricature funky, cool little office in a refurbished warehouse with a spiral staircase and a beanbag, uh, this little startup in, in east Austin.
Um, and it came from a couple of rocket scientist, energy traders guys that were risk managing around, uh, comp the complex grid and structure that we have, um, the electricity place, um, and also, uh, an MIT professor, um, with blockchain and, [00:07:00] um, and data and life sciences skills. And they had come together and, and put the concept of being able to trace and identify in a very data based factual way.
Uh, energy and carbon. So when I said the big gap around, uh, the energy space has been the ability to have high quality data, significant part of that is being able to say, well, okay, yes, electricity is fungible. The electron doesn't even move in some respects, but how do we, how do we apportion responsibility and ownership and clarification around that space?
So they had this concept, but it was a startup in every sense of the world, which was boot every sense of the word, which was bootstrapping from a financial point of view, but also relatively unstructured and open and, and brilliant, um, needed some help. I, I went on the board and started advising and, and helping them great people, um, but very different skill [00:08:00] sets, um, being brought together.
Uh, needed to raise some money. So clearly I've got a little bit of that in my background, so that was helping them with that mm-hmm and, uh, the first, the first, this, this was interesting, cuz it was right at the rollout of COVID. This was February, March of 2020. So not only did they have a brilliant idea, not only did they have to raise some money, um, and try and get some shape in what we were doing, but we also had to deal with a world that was changing dramatically at that point.
Yeah. Um, and, and, and work very well because I think the fundamental concept and the people phenomenal, uh, we, we managed to raise some money from, uh, a Boston based clean energy sector, VC firm, and together with that, very importantly. Cause I think it's, it's part of the validation that I hope continues with what we do.
From Brookfield renewable because they saw what we were doing. And I'll explain why, how and why in a second. So we [00:09:00] raised money from, um, from that VC and from Brookfield, uh, and one of the conditions of their financing was, uh, that I came on as CEO. So, um, uh, that we raised that money in July. I came on August 1st, 2020 in the heart of that first wave of COVID, uh, as CEO.
So for me, um, interesting on a number of levels, first of all, I've gone from a 200,000 person global organization. Yeah. Um, to an a nine person. Pretty local Austin organization. Okay. Secondly, a totally virtual world, because at that point, no one was traveling anywhere. Um, and, uh, and, and really a technology space when that, wasn't my background.
I built businesses where technology was important in the equation, but, uh, not the principle, uh, fundamental of the business. So very, very exciting for me. Uh, as I say, and, and, and we'll talk about how [00:10:00] it kind of evolved in a second, but, um, I loved it straight away because I am passionate about fixing the problem.
And I did believe, and I still do believe that the clear trace technology is world changing because it enables accurate. Measurement monitoring footprinting around the energy space, which opens the whole panacea of regulatory change, genuine comparison, um, genuine, uh, voluntary, good behavior that can actually be monitored as opposed to the vagueness.
That's um, that's out there frankly, currently. So I'm passionate about what we do, phenomenal group of people, even at that first stage, and we've added to it. We we've, we've grown quite considerably, um, and planned to continue doing that. And the culture is great because when you've got a nice core culture to add into that is, is relatively easy, cuz it kind of attracts [00:11:00] similar-minded people and we've also just got great people.
We are working with. We, we we'll talk about some of the. We've aimed at high quality names, blue chip for our validation by way of investors and by way of clients. Um, but we are working with great people there as well. So mm-hmm, , I, I remain passionate and excited about it.
[00:11:20] James Dice: Cool. Very cool. So let's kick off a little bit of the details around, so you you've come from outside the real estate space.
Now let's think about the real estate space as you've come into it. Why do companies today need better access to data? So you said data is key in the energy space and the decarbonization space as a whole, but within real estate. Why is data so important for decarbonization
[00:11:47] Lincoln Payton: specifically? Well, look, great question.
So, first of all, um, it's, it's not just the real estate space. I think the real estate space is at the front of the line and for us a very [00:12:00] major segment focus. Um, and that's because. It's leading in many respects, the regulatory and the awareness profile in this space, but okay. What clear trace does in terms of accurately in real time, measuring, monitoring, displaying, um, sources, moving movement.
Consumption and the carbon footprinting related to energy supply is applicable across in frankly, every industry. Totally. Um, but for us, in terms of focusing at the, the places that are, um, very receptive today, real estate, so commercial buildings, you, you and your audience know is a very significant part of the GD footprint, whichever way you wanna slice and dice it, it's towards 40% of, of GHG footprint.
Um, it's also, and this is, I think very interesting where the [00:13:00] industry is, is leading. You've got a lot of players who are very responsible and they take the, um, the carbon footprinting targeting very seriously. Mm-hmm and they, they look for it to be accurately and clearly reported. And the last element, which is key is it's, it's kind of the leading edge from a regulatory point of view.
Mm-hmm , you've got the, the couple of examples, local law, 97 Buro in Boston. There's other states, Maryland, California coming up with similar regulations and many others coming. They, they are basically carbon footprint regulations, hurdles. They are at real estate is at the front of that regulatory hurtling, um, stage.
And because those are regulations that are actually on the books being replicated. You see some similarities in Europe. Um, real estate is extremely receptive to what we are doing. Got it, got it.
[00:13:58] James Dice: And [00:14:00] talk to me about the data piece. So, you know, you've talked about greenwashing a little bit, uh, here. How, how does that connection of.
Source carbon intensity and building energy usage. How does that provide value given the real or the regulatory environment? The, the fear of greenwashing and really the marketing value, right? As well of decarbonization. How does that connection sort of,
[00:14:28] Lincoln Payton: how, how
[00:14:29] James Dice: are people like Brookfield viewing that connection?
Like why do they need it? You know what I.
[00:14:34] Lincoln Payton: Yeah, that's a great question. So first of all, let, let's talk about greenwashing, which you raised there and, and we see it every day, whether it's people, frankly, these days being led out in handcuffs for making statements around state, uh, you know, financial instruments or, or ESG investing, um, or just people making a mess of their PR.
And that's because the vocabulary allows that today. Totally. How many [00:15:00] people and you must come across it all the time. How many people are making statements about we're a hundred percent renewable, we're this, you know, we're carbon free on a Thursday. I mean, wonderful delightfully, vague vocabulary doesn't mean anything.
And this is kind of goes back to when you're asking, like, why I'm doing this. It that's why, because people make these statements. Uh, and it's a little bit the, um, The evolution of the decarbonization world. And I do think of it in three phases, which is the first phase was the world wakes up and says, oh yeah, this carbon's a problem.
And we need to be aware of it. And we need to start doing some things about it. The, the birth of the popularity of ESG. So phase two for me is, um, kind of where we still are, but I hope the later parts of it, which is okay, anyone who does anything that's remotely green, let's give them credit for that.
Let's [00:16:00] applaud it and embrace it. And that's very good. I, I, I love that. I'm not decrying it at all. Yeah. Well, that's kind of. The offset world, if you want to think of it that way. Yeah. Which is okay, I'm burning electricity. And at the end of the year, I say I used X amount of electricity. Um, and you know, I get some pretty basic average data from some of my utilities, which show me that, um, you know, 58% of that electricity was very horribly carbon creating.
Yeah. So I'm now gonna go out and buy 58% Rex, which are completely unrelated to what I do and use and it, and some of them are really frankly, sketchy, you know, some mm-hmm , I didn't cut down some trees in Guatemala that might have otherwise been cut down. How does that help Midtown Manhattan at peak load?
I don't know. Um, but because I I've got an equal balance there on what is kind of my carbon using volume and [00:17:00] my offset volume, I can say I'm a hundred percent renew. Well, okay. As I say better that people do the, the offsets than nothing. Yeah. There is consistent data out there that shows that is very not close.
The a, between, um, that and being actually a hundred percent renewable is very significant. Okay. Google published data it's out there. Uh, I think it was 2019, not being temporarily and regionally matched in your offsets or actual supply was a difference of, instead of being a hundred percent, you're only 61% massive difference.
Um, and that's across the world. Yeah. So that's kind of phase two, which is people are still out there. And legitimately, because this is a voluntary process. Um, making statements saying I'm a hundred percent renewable because I buy offsets of any shape, color, size, whatever it is. Totally phase three. So phase one, [00:18:00] Realization of E ESG phase two, anything green is, is good, which is good.
I, I love it. But phase three is yeah. Now we go to a little bit more, um, focused solution here, which is the technology like clear trace has evolved. So we can actually do the homework of matching green energy supply temporarily, regionally, um, to the actual consumption. And therefore you end up with a genuinely greener world.
If everybody is matching their green energy supply to their consumption, Q E D the world is green. We don't get there overnight. There's a blend. There's a, there's a shading as we move that way. But, um, that's kind of, for me, the three phases of, of, of the green washing, um, reporting compliance stage and that third phase.
Is where I think we are coming into [00:19:00] now. And we can second about the, the 24 7 carbon free concept, the load matching that we do. Um, but that that's the progression as I see it. And that's why I'm, I'm doing this and I'm very happy to be part of it. So that was kind of stage one year question there was, was green, the green washing issue.
Does that kind of work for you? Um, James mm-hmm yeah. Before,
[00:19:21] James Dice: yeah. Before you get into stage two, and I think you kind of answered stage two, but, but I wanna circle back on it. Will you talk about real quick? What you mean by, uh, temporally and regionally? Just so, I mean, I understand what you mean, but people might not, let's just bring everyone into the conversation.
They might not know what that means.
[00:19:38] Lincoln Payton: Yeah. A very good question. So when you buy an offset, it may not be most likely it will not be, um, the. Value of energy, renewable energy, um, that has been produced [00:20:00] at the same time and in the same region, even on the same grid system, as energy that you are using. And let's, let's take a, an example, uh, I'm in New York city and I am, uh, using energy off the grid, which is particularly at peak because that's all that's available.
Mm-hmm is, is relatively brown. Um, I then go at the end of the month or the end of the year and say, oh, there's some megawatts that were produced by brown energy and I'm gonna buy some wrecks, some offsets, renewable energy credits for the same volume of electricity. Um, Where are they coming from? Well, most, a lot of people don't ask that question, but E even let's say they're coming from a Texas wind farm in the middle of the night, in the middle of nowhere.
So it's it volumetrically it's equivalent. Mm-hmm X megawatts, brown X megawatts of, [00:21:00] of certification of green energy production. You know, that put them together. They offset I'm a hundred percent renewable. Well, no, you're not because the impact of the offsets from a, a, a Texas wind farm in the middle of the night, which makes very little impact on the overall picture.
Is not the same as buying Rex that might be in New York, similar zone, or at least even in the New York ISO operation, um, which are at the same time as you are using, uh, the, the brown energy, because we know that Pika plants kick in they're very often brown. Um, you know, so time is relevant, totally location is relevant and, and it kind of goes to, to be fairly simplistic.
It kind of goes to the, the premise, which is, um, be responsible for yourself. Okay. Which is at one [00:22:00] point very relevant that any offset is, is good progress for the world. Today. Let's go to that phase three, which is be responsible for yourself. I'm a corporation. I use this much energy and I, I. Ideally use green energy for my requirements.
And we clear trace can prove that that's the secret. I, I, if you like in, in our progression, we can go outside in, in the real estate case, outside the building to source track where the, the energy is coming from so that you are actually buying green energy and able to prove that you are using green energy in your facilities, building factory data center, whatever it may be.
Um, if everybody takes those standards, we are solving the problem because what does it do? Ultimately it pushes out the demand in the little example that we were talking about, James for, um, [00:23:00] New York at peak green energy because you, as well as me and every other real estate owner wants green energy at that time, because otherwise it's gonna impact their carbon footprint.
Um, so what do they do? They go out and they buy green energy. What does that do? It bids up the price. What does that do? It means more people look for ways to build green energy supply that will be available at peak in that location, which is good. We want the market to move that way because it means there'll be more green energy in that space at available at the time when it's being demanded.
Um, rather than more green energy available in a grid somewhere on the other side of the world, where that actually makes very little D.
[00:23:43] James Dice: Totally. Totally.
Hey guys, just another quick note from our sponsor Nexus labs. And then we'll get back to the show. This episode is brought to you by nexus foundations, our introductory course on the smart buildings industry. If you're new to the industry, this course is for you. If you're an industry vet, but [00:24:00] want to understand how technology is changing things.
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Okay. So then the second half of my question earlier was around why is data important? Right. So therefore, if I think about all the things you've said so far, data's important for procurement, data's important for proving what you're doing to your stakeholders.
Data's important for proving to regulators, what you're doing, right. Um, Yeah. It, it, it seems like it enables all of these things that are just requirements for the world moving forward. Is that how
[00:24:50] Lincoln Payton: you're thinking of it? Look, yes. And, and again, as, as I, I try to contain my enthusiasm. That's why we are, we are excited about it and we're enthusiastic [00:25:00] about it.
And, um, and we've got some very smart and visionary shareholders and backers and, and clients because mm-hmm, , um, you know, it's probably a good point for me to, to, to touch a little bit on what that data is and what we actually do with it that unlocks those points. Yeah. Yeah. Your point is absolutely right.
Because the, to what's from a business point of view, what's the total addressable market. The total addressable market is everybody that's using energy. Yeah. Because why isn't everybody that's using energy. First of all, Accurately collecting data on where the source of their energy, the I'll come to the transmission, but also the use of their energy.
Mm-hmm and then saying, what is the accurate carbon footprint of that energy? And what, if anything, should I be doing about it? Should I be trying to reduce it? Am I fine with where I am? Have I set targets to my shareholders, my stakeholders, my employees, um, [00:26:00] my ESG fund investors that say, Hey, even if I'm a, a relatively dirty.
Industry or an old building. I can change that by gradually buying more green energy, fixing my windows, changing human behaviors on the thermostat. I can adjust those things. And even if I'm not great today, I can plot and map a, um, a progression that is very positive and should be embraced by everybody.
Mm-hmm because if you've got an old building, that's not easy to manage. Okay. You can't always just overnight change everything, but you can map out if you can measure it and monitor it, you can manage it. You can map out where you're gonna go and show constant improvement. None of that. Can you do without a really high quality data set?
That is not only. In the building, we'll talk about connections to other systems and building management [00:27:00] systems, but not only in the building, it actually goes where we are unique as we go outside the building to source track and originate and carbon footprint, the energy you are using. And that is a big lever to improving your actual carbon footprint.
[00:27:15] James Dice: Yeah. Yeah. Well, let's talk about that data. So there's two sides of it, right? And you've been, you've been saying it it's, I need data from inside building and I need data from the grid. I think another piece of this that you've also said is I need very granular data, right? I need the ability to say this hour, the carbon intensity of the grid is this much.
And this hour I'm using this much in my building and then be able to marry those two data streams together. Can you talk about how hard it is on both sides of that to get hourly? Because the standard today is. Mostly right. At least throughout my career, the standard in the building has been one data point per month, monthly utility bill.
Right. And maybe [00:28:00] some unreliable, other meters in the building. Um, and the standard on the grid side is like annual DOE numbers that are published way after the fact or annual averages or just random regional carbon footprint numbers per K H right. From energy star. Right. So can you talk about how we go from those old standards down into
[00:28:27] Lincoln Payton: hourly?
Yes, I can. And I'm also gonna add in one element there, that's important to your, to your question because you're absolutely right. That we are looking at, um, load utilization and we are looking at grid data, but we are also looking at, um, Supply data. So where you get your energy and also that can be virtual in terms of evaluating Rex, or it can be actual in terms of PPAs where you've gone out and bought green energy, [00:29:00] that, that to one degree or another matches where you're actually burning things.
So, okay. Let me give you an example. I, I, and we've got a couple of, um, very great visionary clients and, and investors that we're, um, that are in the public domain that we are very happy to talk about. And, and I'll give you this example, cause it kind of goes back to, um, it kind of goes back to our initial capital raises and shows itself again in the recent one.
Um, JP Morgan, we work for JP Morgan, very proud to do that phenomenal organization and very forward looking in their data and digital, um, and energy and carbon footprinting. Um, we basically, uh, they saw the oncoming of local law, 97. Significant New York real estate players. They also saw, um, the complication [00:30:00] around a large corporation's entire energy profile and picture, very siloed information, a little bit of rooftop solar here, uh, a little bit of community energy here.
Um, some PPAs, some PPAs, uh, some wreck buying. Um, and then the grid mix. Whenever you've got a balance that you need to draw down by just turning on the lights sort of thing. Um, how do you pull all that together? So we were working on that. With JP with JP Morgan. And that's when we came across Brookfield renewable because Brookfield renewable, uh, was supplying and is supplying from the upstate New York hydro systems that they own and operate, um, renewable energy under PPA, uh, in, down into zone J Midtown Manhattan for JP Morgan.
And that's where Brookfield saw what we were doing were. Very supportive remain supportive. I was actually in their [00:31:00] offices this afternoon, um, and, and wanted to help us invest in us and, and work with us on certain and use us in certain ways. Wh what, how does it work? So the data, where are we collecting data from each point of an entity's generation?
So for a company like a JP Morgan, that's usually three sources. Okay. One is power. You go out and buy and it's PPA in location, physical power supply in today's world. It's usually green, but it doesn't have to be, I mean, you can, you can do that with, with any source. The second one is, um, Own production and increasingly big companies, real estate players have rooftop, solar.
They have windmills in the parking lot. They mm-hmm , you know, there's some type of own gen, uh, you know, JP Morgan is certainly put, fitting out rooftop solar in, in most of their locations. And then the third is the grid, that grid element. What do [00:32:00] we do? We digitally collect in real time data from each of those sourcing situations, sot revenue, grade meters, Brookfield's upstate hydro.
Um, we are reading each turbine in each tributary of the Hudson river in real time, showing energy being. Generated. We collect that data skater, telemetry, um, revenue grade, high quality OT meters. We are similarly collecting that information from any rooftop, solar that may be in the picture on the top of a, of a retail outlet on the top of a data center, collecting that data real time as well.
We are also, um, collecting the data on any res that are being bought. And, uh, very often we will rate those res, but that's up to the user at this point voluntary system [00:33:00] again, mm-hmm um, we then. Check the grid mix at all locations at all hours, that data is now available and we are able to scan and collect that data.
So all of the sourcing we have in near real time, it's pretty much real time. Each megawatt of that energy is given, um, its own unique birth certificate. So we use a form of blockchain in our complex, um, tech stack, uh, blockchain and, and the whole, uh, crypto system gets a lot of attention these days, either good or bad, depending what day it is.
Uh, we use it because it works for what we do. It's very applicable handles high volumes of data. It's self auditing, it's auditable. It's immutable. It's accessible with permission. So what do we do? Each megawatt that is being produced. Being born gets [00:34:00] its own unique NFT. If you wanna think crypto language, it gets its own unique identifier, its own birth certificate.
What is in that birth certificate? Well, where. When the nature of generation. So hydro carbon free this location, this meter, this time, um, weather temperature and carbon coefficient for each single megawatt out. The good thing is once you put that in there, that's immutable. It can't be tempered with the, the whole wreck.
And the offset world has a little bit of a history of human error, inaccuracy, and a little bit of fraud and replication here and there, as well as being generally handled like, you know, months in arrears in batched up Excel spreadsheet type information. yeah, this is, this is when I say phase three, the new world, this is real time, hour by hour, granular data with that information in it that can't be played with and can't be fooled [00:35:00] around.
We then do the same. We scrape smart data from staying with our example. The New York ISO to basically show, uh, the New York ISO and the New York gaps, the transmission systems that show that that energy has both been scheduled and bought and transmitted, um, from its location to zone J in Midtown Manhattan, we then are doing with the revenue grade meters, um, at the load point.
So let's take JP Morgan's 3 83 Madison, um, building, uh, we are, we are reading the meters there as well, real time, skater, telemetry, um, IOT revenue, grade meters. And from that, you build up a full digital picture of creation of the energy sale scheduling transmission. [00:36:00] Into consumption and load particular floor of a particular building.
All of that data is digitized is tokenized using that, um, blockchain element mm-hmm um, and then we have a unique load matching engine. So first of all, you have the data very useful. Secondly, you have the ability to basically connect the generation to the consumption and say that energy carbon free all whichever energy it is.
But in the example we are talking about was actually used and consumed in 3 83 medicine. So you can make the statement. Digitally, because we all know electrons are fungible and don't flow. It's more of a magnetic field, but digitally that you can make the statement that this is the energy that was produced.
Mm-hmm, scheduled for moved from a carbon feed, free background, hence, uh, you know, a number of the press articles that we've had [00:37:00] recently for JP Morgan, but also for, for Brookfield properties, one Manhattan west. We'll talk about that's another cool example, um, is a hundred percent carbon free in its supply.
One is able to make that intellectually. Prove it, um, digitally. And it's also acceptable for, uh, the pretty strict, um, guidelines for local law, 97 and Buro. So it's, it's it passes master, um, in being an acceptable load matching engine for proving green energy, um, or carbon footprint into a consumption point.
[00:37:37] James Dice: OK. Yeah, that makes, that makes perfect sense to me. One of the follow up questions I have there, when I was listening to you talk, there is like, so take 3 83 Madison, for instance, it's not like there's a wire running from there to the hydroelectric dam. Right? So if you picture like the hydro, Hydro's great because it's a big river right.
Coming off of there. [00:38:00] Not all of those molecules, right. Are producing. Electricity at 3 83 Madison. Right. So how does, and maybe this is a problem for when this concept grows, but how do we make sure that, um, there's not more, um, claims on the load side than there was water molecules to begin with? How does it go backwards to that once there's a bunch of buildings that are doing
[00:38:27] Lincoln Payton: this?
Yeah, a absolutely. Well, um, you know, that that's where the system, the immutability and that quality of data granularity is, is key because, um, and, and for, in the example, we are talking about Brookfield, renewable saw the benefit because as energy producers, as generators, they are able to say to their clients, okay, we can supply you carbon free energy.
Brookfield renewable is actually supplying JP Morgan and. And, and their [00:39:00] sister company, Brookfield properties, but it's pretty separate operation. Mm-hmm with carbon free energy for, for certain buildings. And just for that very reason why people don't say, yeah, yeah, yeah. But you could be saying that to a hundred people.
How do we know? Um, you've got the picture there that says no, this hour, this energy is spoken for and it is being used in this building and we can load match it back to that. And you couldn't reload that hour of energy, Jen, from a particular location to a, to another building at the same time you fit the system will, will just won't allow it because it's self and self balance.
[00:39:40] James Dice: requires you guys as the sort of intermediary to work with both. Brookfield renewables, the generation side and the load side, you have to have both correct in
[00:39:51] Lincoln Payton: order for that to happen. Got it. And that's the unique thing, because a lot of, a lot of your listeners, um, who are very clearly very real estate [00:40:00] focused, there's, there's a building management systems, um, have been out there for quite a while.
Mm-hmm and they talk about, um, energy efficiency of course, a lot. And some of them talk about, you know, carbon footprinting and, and this type of thing, looking just at the load side of the picture, which is okay, we are gonna read your, your meters in, in your building. Um, and we are gonna append, as you mentioned, uh, you know, some average carbon data to that and give you, you know, simple math, we're gonna give you a carbon footprint that is not at all.
What we are doing. What we are doing is saying we are gonna hour by our location by location source track. Where your energy is coming from Cub and prove it into your locations if you bought it, or if you're just taking a grid mix or if you've got your, your, your own, um, your own gen particularly valuable when you've got several different sources.
[00:41:00] Cause sounds like it complicated. The critical thing to understand is we are going outside the building. We are going to the source of the energy carbon. Footprinting it, proving it into the building and then giving you you a carbon footprint. So it's really okay. Um, a genuine, a genuine analysis of, uh, of your carbon coming in.
And I think where that is so important looking forwards for the real estate space is, um, as you see these hurdles and these regulations coming, um, as well as the, the, the good citizenship. Targeting of trying to, to set yourself goals and hit them. Um, you can do certain amount in a, in a, in a building by fixing some of the physical attributes of the building, the windows, the insulation, the chiller, whatever, whatever it is, you can, you can make good progress with that.
And that's a, not what we do, but certainly very [00:42:00] valuable. Um, you can also get some human behaviors that can be helpful. Um, When there's only a, when the building is only partially being used, have everybody on one floor rather than in their offices. So you have to chill or, or heat every floor in the building change the thermostat, couple of degrees.
All of these are good things. Okay. Um, You generally speaking, when you look at the, where, where the regulations are going, those won't fix it. If you're just taking grid energy in big cities, that won't be enough. You need the ability to say, okay, we're gonna try and do those things and reduce the amount of energy we use.
And there's other ways of doing that as well, um, around the electricity industry, but where the big saving on carbon footprint comes is from actually bringing in green energy. Okay. And being able to prove it.
[00:42:56] James Dice: So you're saying even if I install all the energy [00:43:00] efficiencies, I can, I can install. Even if I electrify all my loads, even if I install the latest, greatest controls, you're saying still the point that you get down to in the big cities, you're still gonna be buying some power and therefore.
You're gonna be buying dirtier power yeah. Than you need
[00:43:17] Lincoln Payton: to. And obviously over time, we all hope that's gonna change as grids gradually get greener. Right. Let's be honest. That's not happening overnight. We got, we got infrastructure implementation problems. So we are gonna be being faced with some, you know, brown grid situations for quite a long time.
So, um, uh, yeah, I, I think the way to, so, and it, and it's, it's true. When you look at the harbinger of this regulation, which is local law, 97, those physical adjustments don't get it done on their own. Mm-hmm . For buildings, they don't, and it tightens every year as well.
[00:43:57] James Dice: And it, and it gets even worse when you start to make, [00:44:00] um, when you start to take it hourly.
Right? So you mentioned the 24 7 carbon free energy goals that a lot of corporations are implementing these days started with Google than Microsoft than I think there have been more since then. Um, it gets even more difficult then, cause you there's still gonna be that time when the grid is a little bit dirty on that one hour rate on, you know, whatever depends on what grade you're talking about, but there's still gonna be hard to curtail.
And I always like to talk about in. Buildings, you can't decarbonize at the expense of an occupant's productivity. Right? So there's gonna be that time when, like, I need to have the lights on. I need to be fully ventilated in here in this conference room when we're having this meeting. Right. Um, that it's always gonna be difficult.
And so therefore that's when the matching comes in.
[00:44:48] Lincoln Payton: Essentially. Exactly, exactly. Got it. And, um, and you know, to your point, um, you, you, you also, you're getting the point now where there's more sophistication and more [00:45:00] awareness around these concepts of 24 7 matched granular hour by hour green energy supply, um, and, uh, consumers, the CNI world, as well as the, the real estate world are asking for energy suppliers.
To supply them on a 24, 7 basis or some degree of that. And, um, that's where you need the granularity of data that we have to prove that. And that's why, frankly, in our, our latest capital raising round, we do have a number of world class, um, energy supply players. We have Brookfield renewable. Again, we have EDF north America.
Um, we have Tenaska, uh, we have Exelon who see the benefit of being able to say to their clients. You are asking us for some structure, some shape of curve, um, of either 24, 7 or partially 24 7. Um, [00:46:00] we wanna be able to show that and demonstrate that to our clients that are buying energy.
[00:46:05] James Dice: Go ahead. Brilliant.
Okay. So if I repeat this back to you, if I, if I were to give the pitch for what you guys do back to you, , um, you guys don't really buy Rex purchase PPAs, um, get into anything like that. That's already being done for your customers. You're just saying, what are all the sources of energy you have today? And it's a data problem at that point.
Um, you mentioned a lot of metering. It sounds like maybe you're doing your own metering, but you're also leveraging what meters are already there. Right? So it's a data problem of metering problem. Um, and then layering in this blockchain piece to make sure it's provable, um, All the different reasons why blockchain's important, but basically saying, um, this is the ledger for, um, these, the transactions [00:47:00] that have happened in this building for energy being able to
[00:47:03] Lincoln Payton: prove it.
Absolutely. So your two points there. Yes, we are a very sophisticated carbon accounting process. That is a, is a single source of truth for all around the energy and carbon profile of, of an entity. Um, this, we are not. Buying energy, supplying energy, changing windows, um, reevaluating, um, HVAC. That's not what we are doing.
Um, what we are are then enabling people to do is with that data is to go out and manage better. There mm-hmm carbon footprint and their energy profile. So, um, absolutely we advocate efficiency in the building. We advocate efficient use of the building, but then there is at where our data really [00:48:00] drives people today, especially in the real estate real estate space is you gotta sort out your supply mm-hmm um, and historically people have used Rex or virtual types of energy supply.
Increasingly I think folks should be aware that's gonna be looked at, and it's not gonna be looked at as favorably as actual. Temporal using my phraseology again, same time, same place, green energy, physical supply. It's not gonna be looked at as well. Got it. Got it. All right.
[00:48:33] James Dice: Um, can we talk about real quick?
The, so you mentioned planning a little bit, and you mentioned, um, efficiency and electrification throughout this conversation. How can this data then be used to. Um, plan out the roadmap. So I would imagine once, once you offset or offsets the wrong word, once you match all of your consumption with, with renewable energy, right.[00:49:00]
I would imagine at some point, you'd say, well, how can I do this cheaper right. Over time? Cause at that point you're, you're zero carbon, right? You've, you've reached your goal, but over time there's gotta be cheaper ways to do it. Right. And so how do you then use that data to then say, well, what if we do this project and that building and that project and that building, or we switch the source from hydro to solar over here.
How do you then make decisions moving forward in, in a real estate organization?
[00:49:31] Lincoln Payton: Absolutely. A really great question. Um, our data. Enables the modeling and we, we have some modeling, we're still building out some of that modeling mm-hmm , but it basically enables exactly what you just mentioned, which is I want to get.
Uh, and, and this is, uh, what I would describe as an AI layer that we are working on, uh, in our product roadmap right now. And I think of it a little bit like, um, the navigation system in your car, if you're right. Okay. Which is, [00:50:00] um, you, you sit in your car in, um, You know, in Boston and you want to get to New York.
So you put in the DEC, you put in where you are, you put in where you want to get. Um, and, and a couple of criteria there. I don't wanna pay toll roads, or I don't wanna go over bridge, whatever it might be. Yeah. And it'll show you some options and then you hit the button and it, it will kind of lead you down that path.
Okay. That's, that's stuff that we are working on right now, which is I I'm operating. First of all, is collect, I'm operating a building or a real estate portfolio. Um, first of all, where am I? So the data collect all the data and I'll come back to your metering question cuz it's, it's a very relevant one.
Um, I, I collect all the data sources, applications, transmission, and movement to, to the extent that you're load matching, um, But collect all that data. Digitized tokenized. It's ready. It's there to use now. Where do I want to get? Okay. I've [00:51:00] got this much, this percentage of renewable energy on a, on a daily, monthly annual basis.
Um, granular proof of it. I've got this carbon footprint, actual tons of carbon put in the air by virtue of my energy activities, my scope to clear energy activities. Mm-hmm what do I wanna do? Am I happy with that? Is that fine? Because I'm doing pretty well. Or do I want to improve and set targets and do that?
You do that. You put it in and it shows you the, the best ways to do that. Where is it? Is it actual power supply? Is. Rex or offsets, which in our process. And we have academic involvement in that, because this is the, the first element of qualitative in there. If you like, um, is maybe certain offsets, don't get a hundred percent value, you know, X megawatts doesn't match X megawatts.
It's 62%. It's 50%. It's 10%. If it's, you know, [00:52:00] something not very, uh matchable um, but how's the best way and best can mean different things cost effective. Mm-hmm um, regionally sensitive. I wanna do this all in north America, or I'm happy to do things around the. How do you factor all those elements in, and then how do you get there?
You hit the button, the AI will actually implement it for you could also work the other way to be perfectly honest. You could be very, very renewable and very low carbon footprint. And just, uh, think of it like, um, like capital in a, in a, in a company, in a business you never want to have too much equity because then, you know, you're not using it fully.
Mm-hmm imagine that someone has set a target that I'll be 90% renewable, uh, with this many tons of carbon by. 2025. Right? All of a sudden you realize that you've actually gone past that. Now maybe the real answer is that's Julie. Good stick with it. [00:53:00] Congratulations. But maybe you need, you, you're having a hard time business wise.
You can take something back out of that and still hit your targets, but you can now manage it. You can think of it actively, um, to, to manage it. So, so that's definitely, um, what we're doing. So your question's about modeling and people saying, well, okay, if I want to get to this target, um, the best state for me to make these, uh, these investments in power supply is this one.
And this one, because it has the highest impact and the most cost effectiveness. That's absolutely what our, our data allows that modeling and we're doing it and we're doing some of it internationally right now, which is kind of cool. Um, The the second point I'll come back to is you asked about the metering mm-hmm and data availability because historically, um, the energy world and the real estate world has not had this kind of data availability, collecting data is, is one of the challenges we we're.
I would [00:54:00] say we are good at that, but that's one of the things we need to be good at. Um, we are not a hardware company in any way, shape or form, so we are not supplying energy. We're not selling Rex and we're not selling hardware. We're a software company. We collect data, we do smart things. I hope with that data that enable people to take actions that, that are clever.
We do work with, um, uh, you know, people who are in the hardware space. So metering, uh, very often is implemented as part of someone's PPA. They will be saying, um, I, in that RFP for power supply, they'll be saying, uh, your supply needs to have metering of quality that will give clear, trace the information.
That's, we're seeing that in, um, in RFPs for power supply to major companies that we.
[00:54:54] James Dice: Uh, well, last final question. I I'd like to circle back on the integration. So you [00:55:00] mentioned building management systems, you've mentioned metering systems. You mentioned IOT a little bit. These are all the topics that we normally talk about on the podcast. So I always like to circle back into, okay, we have this new technology.
How does this perhaps integrate with, how does this data help those systems? How does systems from those systems or data from those systems help what you guys are doing? How does this integrate in the real estate organization's overall tech stack? And one of the things that I think is interesting is that there are companies out there that are already looking at the load side analytics quite a bit.
Right. And, um, I think they could use a lot of the insights that you're providing to provide better analytics on the load side. So that's just one idea I have, I guess, but what are you thinking about in terms of how this integrates in with other technology that building owners buy?
[00:55:54] Lincoln Payton: Yeah, it's a, it's a, a really, really well-informed question.
So, um, yes, [00:56:00] it's the short answer we work with. We are very happy to work with building management systems because they're, um, first of all, and it, the two subjects link together pretty well at our last two. Your last two questions there. Mm-hmm James, you must have done this before. Um, the, uh, the, the fact is collecting data is not always easy.
Okay. There's not always exactly the kind of metering or it, it all, it takes time to collect, to connect up to those. Yeah, very often. If there's a building management system in place, they're already scraping data from. Some of the, all of the meters in the building, maybe doing water, maybe, excuse me, maybe doing waste or other things as well.
But they're collecting data from the, um, the revenue grade meters, the, the utility meters we talk about. So we are, we are very happy, um, to work with, uh, apps and, and management systems on both ends of the equation, whether it's in the building. So there's a [00:57:00] building management system. We have partnerships with a couple of.
What I would consider the leading, um, technologically building management system players, um, to basically take the data from their app for the load information. Cause they've already got it. Mm-hmm and we have similarly, uh, we work with a number of the energy management, um, software companies that are already collecting and managing data on the generation side of things.
So we, we can do that. I mean, if I'm, if I'm honest from a, a purely perfectionist point of view, we would rather eventually get to the stage where we are taking that data from the actual IOT revenue grade meters. Yeah. Again, both the generation side. And the load side, because it's, it's the horse's mouth because we then believe that we, you know, there's no, we are controlling the whole data set.
There's no human touching. It's, it's fully automated and fully it's as high integrity [00:58:00] as there is available. Yeah. But in the short term, very happy to work with, with, um, the good building management systems and the good energy management generation systems as well. So we, we are set up to integrate with other players around the real estate space and, um, and very happy to do that and very respectful of what some of those other processes are bringing and, and doing.
[00:58:25] James Dice: All right, Lincoln, this has been super educational. Thank you for putting up with all of my long drawn out questions. Um, let's end with some carve outs. I'd love to hear from you on, uh, this could be personal and professional. What link can I share with the audience? What could be a book podcast?
Um, newsletter. Movie TV show that you think we should share with the audience that has made us an impact on.
[00:58:51] Lincoln Payton: Wow. Um, well, first thing I'm gonna, I'm gonna unashamedly, um, plug the fact that we are gonna be doing some tech type [00:59:00] podcasting around our, our topic. So, um, and that's gonna be called the, the decarbonization race.
And, um, because we do try and look at it as an urgency is needed here, not in real estate, but not just in real estate. So broader. Totally. So that's from a, from what podcast do I, like, I love that one, even though it hasn't come out yet. Um, you know, from a book's point of view, I'd certainly read, read stuff around this space, but, uh, again, kind of goes back to your opening in terms of what was my main career and what I'm doing now.
I've gone from that really big, um, organization to a, a pretty small organization in terms of, of size of people and, and capital base and, and footprint. Um, and people ask me, well, is it, is it worse? Is it easier or is it, you know, what, what's the difference? Um, and I would actually go as far [01:00:00] as to say in many respects, it's easier cuz it's more agile.
Um, but it's similar and it's similar because. It's it's working as a, as a team and trying to get the most out of people. And so the book that I think about, I don't know why, but I just reread it recently is what I really consider kind of like a team building type book. Okay. And it's also shows my, my, my Brit growing up on the river thas history here, where I used to row, um, crew, as you call it here in, in America.
Okay. And it's, it's the boys in the boat, which is, I can't remember who the author is now, but it's a phenomenal book. And if you haven't read it, I recommend it for me. It's a really, it's a, it's a team. Um, hang in there, make it work, believe in what you're doing. Mm-hmm, have a vision and a dream. Uh, and, and that's what we're doing.
We're doing this. I would say everybody in our, in our, on our platform, um, certainly wants to make a fantastic [01:01:00] commercial success of what we're doing. Um, because the total addressable market, the, the, the uses are, are, you know, are superbly large and superbly exciting, but also there is that altruistic ambition here, which is by having accurate data that people trust the man in the street trusts and understands enables regulation, enables transparency, uh, enables people to really move concretely in the right direction.
Um, that altruistic ambition is, is very team spirit driven. Mm-hmm . So I kind of go to that book and it's partly cuz I reread it recently. Um, you know, the boys. That's
[01:01:41] James Dice: great. I'll have to check that out. Um, mine that I'll share this week is very relevant to our conversation. I just started it, so I can't speak on whether it covers everything we talked about today, but it's called the energy switch.
It's a book by, um, the guy's name's Peter, or I can't remember his last name, but it's all about this [01:02:00] transition in the electric grid that we're talking about. So it's one of the books that I've read that has really. As a building's mind, you know, you can get very behind the meter focused. And I feel like that's another phase that has sort of ended for there.
There are no behind the meter energy professionals anymore. That that is a Mirage right now. Um, that is, that is disintegrating before our eyes. So we have to acknowledge that this is all one grid, and I think that's one of the books I'd point people to, to start to figure out where we're at in that
[01:02:32] Lincoln Payton: transition.
So, okay. That's, I'm, I'm gonna note that down and, and grab that one because, uh, had a couple of very interesting conversations recently around we around some think tanks, um, on the future of the grid and that's, there you go. That's maybe another conversation and, and maybe we'll, we'll, we'll pick your brains on that.
Given, given the depth of reading you're doing, because. You know, there's some real questions on, on how particularly the [01:03:00] us grid evolves in the next five years, because with, um, you know, the, the, the decentralization with the, um, you know, the micro capabilities with the, um, you know, the fragility of a lot of the infrastructure, mm-hmm how should it evolve?
So that, that's a, that's a cool one. I've noted it now.
[01:03:21] James Dice: Very good pleasure
[01:03:24] Lincoln Payton: for coming. It's really a pleasure to talk to you as well, and, um, enjoy the rest of the day. And we look forward to talking to you again soon.
All right friends, thanks for listening to this episode of the Nexus Podcast. For more episodes like this and to get the weekly Nexus Newsletter, which by the way, readers have said is the best way to stay up to date on the future of the smart building industry, please subscribe at nexuslabs.online. You can find the show notes for this conversation there as well. Have a great day.