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âThis is like the moral compass to our industry, right? We're totally fixated on customer benefits and savings; and in order to pivot so we are also considering grid benefits and GHGs, we need to make them valuable, and this is how we do itâŚâ
âMatt Golden
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Episode 35 is a conversation with Matt Golden, CEO of Recurve.
You can find Matt Golden on LinkedIn.
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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!
James Dice: [00:00:03] 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.
This episode of the podcast is brought to you by nexus pro nexus pro is an annual or monthly subscription where members get exclusive writing podcasts and invites to members only zoom gatherings. You can find info on how to join and support the Without further ado, please enjoy this episode, the nexus podcast.
Episode 35 is a conversation with Matt golden CEO of recurve. This episode is a bit of a change of pace from our normal topics, but it's an important one that all of you buildings, folks need to be aware of. As Matt says, if you're not aware of the grid benefits of your projects, you're probably leaving money on the table.
This is a deep dive into the past and present of energy efficiency. What's changed with COVID grid, flexibility, virtual power plants. Grid interactive buildings and much more, including more buzzwords without further ado, please enjoy nexus podcast, episode 35.
Matt Golden: [00:01:25] All right.
James Dice: [00:01:26] Hello, Matt. Welcome to the nexus podcast. Can you introduce yourself for everyone?
Matt Golden: [00:01:30] So, uh, my name is Matt golden. I'm a founder of recurve software, uh, actually recurve analytics, technically speaking. Uh, we provide tools for, uh, utilities and also a whole range of companies out in the marketplace.
We think of them as virtual power plant providers, or often call them aggregators that are providing all sorts of services too. All sorts of buildings, everything from solar to storage, to insulate and addicts, to IOT devices, we're totally agnostic. We think there's a lot of amazing stuff out there. Um, stuff that produces great benefits, that often and get paid for it.
So we end up with customers paying out of pocket, and we don't think that's right. We think the utility industry should pay their freight and that's better for everybody. So we provide, we actually sell mostly to utilities and provide a solution that helps them figure out which buildings are. Causing them, the grid issues where the peaks coming from, what end uses and enables them to engage the market, uh, sometimes through traditional programs, but increasingly through what we call marketplace approaches, where they work with the companies out there that have, are building the business models and the financing solutions and the broad range of types of solutions and technologies.
We need to serve building owners, uh, in a much more streamlined market-based approach that gets paid for the performance where we can actually track the impact that these projects are Having, I think it is. A new breed of really automated MNV on an hourly basis that lets us quantify that impact and also value.
What is that great impact? What is it worth in terms of transmission and distribution, uh, capacity, energy, GHG impacts, and so that these aggregators can actually monetize the value of what they're providing, like a virtual power plant and make more money and doing the right stuff and pass that savings back to customers.
So they buy more of it and everybody wins. Um, So by way of background, uh, I started in kind of think like an aggregator. Â and the audio workforce, you to know what I'm pointing at, but I have my sustainable spaces, which was my original company now, quite a while ago, shingle from our old offices, but, uh, I'm a contractor at heart.
So it was in the solar industry. Kind of a silly now, but got old fed up with rebates were coming and going and all. And, uh, and all of that and that the bug on energy efficiency and said, why are we putting panels on these buildings that are bleeding energy out everywhere. We should go fix the buildings first.
And so, uh, sustainable spaces was a full service building. Science-based home performance company. We also did some work in commercial and multifamily. Um, It started out thinking like, yeah, we're going to build software because I had a technology background and make this automated streamlined thing. And next thing we know, I got five contractor licenses and 10 trucks and we're vertically integrated because the only way to make money, it turns out.
Um, but really stymied, you know, uh, we worked really hard to get the utilities, to create programs, to make us go faster and they just cause pain. It turns out if you get paid in advance based on a rebate, which is the traditional method. If you're in the business and you're doing good work and you have engineers and blower doors and impaired cameras, you make less money than the average guy who doesn't right.
Everyone paid exactly the same amount, the way you make more money as you reduce your cost of goods sold in the low to the bottom. Yeah. Theaters, the folks producing the least value are actually getting the most profit and trying to get incentive structure. Conversely, you know, AC Tripoli and everybody's running around saying energy efficiency is the first fuel.
We should do it. You know, it's the most important resource, but it doesn't actually behave like one and it's certainly not valued like one, so it's not worth enough to be true. Um, and so that's probably trying to solve, how do we move from that pay for products in advance based on some average, regardless how it actually performs.
Pay that to the customer so that, you know, the market's not even making money through that channel. It's a witch misaligned, the incentives further. Um, and then the flip side of that, as well as, you know, and we call that paper performance, which is. That's actually the core of what we're going to talk about.
If you're going to pay for performance, the starting point, and really the core of our business is you have to know what you're paying for. What is the product? What is energy efficiency? And you, if you have it delve down this rabbit hole and it's comedy, it's like an onion dropped to the bottom of a rabbit hole.
So it sounds a little easier than it is because it's a derivative, it's a calculated value. So if you're gonna bet on a calculated value, you got to know what that calculation is, or you end up fighting over it and that's all you end up doing. Um, so everyone's got to believe it's real. We also got to put in a contract and generate an invoice and get paid and not end up just litigating how weather stations were chosen or things like that.
But okay. And on the other side of it, well, I'll give you one more piece. This is the other principle we'll talk about, which is when I was in the contracting business, we knew for sure that a two in the afternoon was peak, right? Solar was just solar and the duck curve hadn't really started. We had monthly meters, Different world entirely.
So in this transition, the pay for performance am I smart meter data started coming online. All of a sudden, Holy crap, this duck curve thing is real. It's not, it's actually happening and like, it's really going to happen, guys. So, um, as we talk about this pivot from like efficiency as a nice to have, do goodery to efficiency as a valuable resource, it's critical.
And like the big leap in value is moving from an average of by month reduction. But let me give you all a secret utilities. Don't want to sell less of stuff. but to actually quantifying when and where it's happening, so demand. And so everything we're doing now is on an hourly basis and a locational basis.
And that's really the turning point where instead of just writing white papers about how we're a resource, we start behaving like one and we can actually migrate from like programs to the resource stack to be a procurement, actual resource. And that's important because it's a lot more valuable.
Totally.
James Dice: [00:06:42] And the reason I wanted to have you on as a great intro, by the way. And the reason I wanted to have you on is because the nexus audience we're all thinking about things for behind the meter, but that's changing. We can't continue to think
Matt Golden: [00:06:54] we're going to connect
James Dice: [00:06:54] all that stuff. Exactly.
Yeah. Yeah. So we can't continue to, as, as a nexus community, can't continue to think just behind the meter, because things are starting to get a little bit convoluted,
Matt Golden: [00:07:05] at the neck, leaving money on the table. When you do that.
James Dice: [00:07:10] Yeah, that's a great point. So before we dive into all that stuff, cause I want to unpack basically everything you just said for everyone.
Um, I want to ask you about that shingle you have behind you, which is I saw a video on your LinkedIn profile of you at Ellen's home doing an energy audit. Can you
Matt Golden: [00:07:29] talk a little bit, a lot of time across spaces. I've done my dues. but yeah, I, you know, the context, it was, I think it was like an earth day show or something, but, uh, it was like a solid seven half minutes in my 15 minutes of fame.
Cause I did get recognized because like I did such a great job auditing our house, but it was Ellen's house. So like diehard, Ellen fans know that episode or knew that episode. So I would, I would actually get people being like, you're that guy, but again, it wasn't because they were super excited about energy efficiency.
Yeah. Yeah, it's pretty fun. And, uh, I don't know. She was nice enough to me. I don't know whatever everybody says.
James Dice: [00:07:58] Yeah, no, I enjoyed it. You were like trying to work in like the nerdy energy efficiency terms, like Phantom loads to an Allen, just trying to make jokes. So it was,
Matt Golden: [00:08:07] he did tell me, and actually some people, even this, all this like stuff that's been going on, I got the instructions like.
You don't have to try to be funny. And I was like, thank you.
James Dice: [00:08:14] Thank you. Oh, it's got
that
Matt Golden: [00:08:17] piece go one or two little ones in there. But
James Dice: [00:08:20] the thing I wanted to tell you is it that you're the second Georgetown alum that's been on the podcast. I don't know if you know Logan soya from uh Agricor.
Matt Golden: [00:08:29] but I can help, but I should, because, uh, there was like a little G town clean tech crew.
James Dice: [00:08:33] Yeah. Yeah, totally. I can send you an intro. Well, so that was a great, intro into recurve. Um, so let's dive into some of that stuff you just, introduced us.
So, I want to give you my background a little bit, cause I think it'll help you kind of. Take us off into this next phase of the conversation. So I've done a lot in like the, what you just described as kind of like the old way to do energy efficiency. So, applying for incentives, submitting calculations to incentive programs, helping my clients, which are building owners.
Awesome. Uh, it was not awesome. No, it was actually not fun at all. I learned how to get kind of game the system and figure out how to build energy models really quickly to kind of like prove something that was happening. Right. so I think a lot of people are kind of familiar with that old world, especially in mechanical engineers that have been doing energy management sort of projects for awhile, retro commissioning, commissioning that, that type of thing.
Um, Can you kind of talk about like the old world and then the new world that we're coming into.
Matt Golden: [00:09:35] So the most important thing is it's not like one or the other it's about, you still have to like engineer a good solution. That works. Right. But the way we think about it is we also think about behind the meter.
Right. And we want to, we want to be open The diversity of solutions and engineering and stuff that goes on behind the meter, do its thing and hold it accountable to those outcomes, but not micromanage it. And that's really the difference. I mean, you know, energy models make a lot of sense for certain types of projects.
You should do them if it helps, right? Like whatever, engineering that you do, product selection, implementation, training, like instead of prescribing all of that. And micromanaging and double-checking it because there's no accountability to the results. Right. And so you put yourself in like the old world and the old world.
I put air, air quotes for the listeners. Um, it's not old at all. Like mostly still what we do almost everywhere. Most utilities are still, if you're going to submit a bunch of paperwork in a super complicated energy model that like, I can't even begin to understand. And then I'm going to pay a bunch of money based on that.
And then like, if I'm a utility, like that's what if that didn't work? And so they don't really have a choice. Right? How else, how else do I make sure you're not trying to screw me and you call it gaming. I don't even think he was gaming. Like, he'd give me crazy rules. He paid me to the wrong stuff.
Like I'm going to do it, but you know, that's like a job. And so there's a fundamental mistrust because everyone does overestimate. Cause like you're paid to do that at the end of the day and their shoes. What else are they going to do? Like give me everything. And I'm going to try to make sense of this bespoke nightmare you've given me and yeah.
And if I just micromanage every single thing you do, maybe it'll work. Which of course it doesn't because you either go out of business or you game the system and get around them. Cause your information asymmetry here. Right. So. engineering a good quality work. Doesn't go away at all. In fact, good quality, energy models, engineering, and high quality work now becomes a source of profit in this model because you're not crying, but the trade is you become accountable that it actually has to work to get paid.
Hmm, right. That's the trade-off, but you're training that for all the bullshit. Okay. So the basis of the model is like we have standardized M and V, especially the smart meter data. We have agreed to how it's tracked. We can measure how these things are doing transparently lightly. Um, and then you'll get agreed to pay for your, what we call pay for performance, which is we sent flexibly purchase agreements, which is.
you know, you're an aggregator, what do we call an aggregator company? Let's do. What do you mean by aggregator company? That doing stuff with customers, like get customers to agree to do it, what you're doing and assign this value to you. You can be a finance company, a large contractor, you know, lighting as a service company has got a phone with one of them, uh, provider, uh, it can be unconnected.
Can we Google? Like,
James Dice: [00:12:11] yeah. So, but aggregator is going to charge the customer to do something and then they're going to. Apply for these incentives or rebates on behalf of their customer,
Matt Golden: [00:12:21] which is the building performance payments. Cause it's only about incentives and rebates. Sounds like they're giving you something for free.
You're actually getting paid for something you're delivering. That's valuable. Um, and sort of thinking, this is like two things how you deliver your services to your customers is your business. And they're going to buy it based on benefits they receive, right? We're bills, often comfort, better lights that make their products look better, whatever it is.
And we want to just leave that. To be your business between you and your customer and how you get paid for that. Do they give you cash money? Do they do at least an energy service agreement of your business? That's the customer's cashflow. Got it. We're talking about a tertiary cashflow that says, you know, You've actually done lighting in 350 homes on a part of the grid. That has a peak problem, right? Or more accurately. How about this? I mean, he's a real pickup actually. You know, we have a peak problem in our blackouts in August happened, you know, at 7:00 PM or you know, actually between five and eight.
Right. And we have this coincidental HVAC peak with like a commercial peak. And if you, so you go in and put an air conditioners in and you insulate addicts. You're producing benefits that accrue not to your customer, but to the utility because they don't have to buy $1,400 megawatt hours, right. Or as we install electric vehicles and all this stuff, all of a sudden we're really stressing our distribution network.
They can spend millions of dollars on a new distribution system or potentially they can reduce load and not have to. That's a mutual benefit. So in addition to that customer benefit, right, we're creating a tertiary cashflow. That's the virtual power plant that says you as an aggregator now can get paid for the virtual power plant.
You're creating the transmission and distribution value, the capacity, the energy, the GHGs, the stuff that doesn't accrue to your customer. We don't want them paying with their credit card for the full freight. And then you shouldn't be giving that to PGD or a con ed or combat or whoever she could pay for that.
and so that's what this model is. And it's setting up that grid value. So that as an aggregator, you go out, do your work, and you're also building power plant getting paid for. And you can take that cashflow we're about all about aligning incentives, right? And you can figure what you're gonna do with it.
Are you going to buy down your customer costs like a rebate? Are you going to reduce their interest rate or you can do better marketing? How are you going to do in a competitive market? Cause we don't pick winners. Right. And that's the thing that's actually what. Keeps everybody honest, right? Is that we're not going to run an RFP and be like you win you're it you're the monopoly, which is also the fundamental flaw in the traditional system.
Right. Um, and so go forth. And so what that produces is a model that says as an aggregator, if you can figure out how to sell your product to a customer in a way that they value. That simultaneously delivers the, and you've kind of value engineer, right? It's not, how do I deliver the best benefit of the customer and maximize the grid benefits and the GHG reductions.
And if you do that right, you make more money. Your customer gets a better deal. And we get a stable, clean grip. That's the plan. Got it.
James Dice: [00:15:04] So just thinking about the, kind of the old way to do it, and I'm still kind of like all the way new way. Maybe that's not the right way to think about it because we're in a transition, right?
So
Matt Golden: [00:15:17] we're stuck in the middle or in the
James Dice: [00:15:19] middle of purgatory. The old way was I'm going to do energy efficiency projects. I'm going to upgrade something, right. And part of that is going to be this incentive, this free incentive or rebate check. So what's the new model. And I think I know it. I'll just try it.
You tell me if I'm wrong. So now I'm going to do that same project and I'm going to get payments on the backend for the actual calculated energy savings at the meter or demand. The change in demand profile at the meter. And so your software kind of sits there and says, this is that number that's Rob.
Matt Golden: [00:15:55] Okay. And what you do that money. So you create this, created a cashflow. So finding anything cash flows is called infrastructure investing. Yep. That's project finance, right? Not financing projects with a credit card. So you're actually, so you have this cashflow you're creating that in a portfolio is incredibly stay one consistent that you can finance and bring forward.
And then again, your customer doesn't even really necessarily have to know it's there ultimately, but you figure out how to use that cash flow to grow your business and get more customers.
James Dice: [00:16:24] Okay. So if I'm an aggregator, I'm just thinking about this totally different now, instead of being like, uh, In the past, I was like, you could call what I've done an aggravator. And I was like a trade ally and the local utility program. So what would be the new model for that, with the setup.
Matt Golden: [00:16:40] So again, we're, you would get a flexibility purchase agreement, which gives you access to these markets. you go about your business, you figure out how to sell to your customers.
You enroll those projects, you get paid for their performance over time. Basically it, And so what our role on that is we are not an aggregator ever, that would be a conflict of interest. So, so we spent the last decade coming out of sustainable spaces, trying to figure out how to solve this problem and starting with the fact that you can't, this shit is not real and you can't pay for performance.
For sure. If you don't have an agreement on what it is in the first place. And the problem is a bit of a joke, but it's true. You take IP VIP option C or evaluation methods, anybody, and you. There's there's flaws in it to begin with. But the real problem is if you ask five engineers to give you the savings on the same 50 buildings, you're going to get 17 answers.
And the punchline is there. All right, because we haven't agreed to anything. Okay. And it's really profound. There's hundreds and hundreds of choices that would blow your mind. And I'd have to explain on Benning methods and, you know, balance point temperature, but a big one. So I didn't put a heat pump my own house.
Right. And if you use the nearest weather station, you end up with Napa I'm in Morin. Okay. Close to me, but it's hot. My savings 15%. If you pick the closest in weather in climate zone, which is what the methods we deploy, use B you get SFO, which is 1.2 miles away, San Francisco airport, further away than Napa.
And I say 23%. Okay. Right. I says, who's right. So. You know, we spent the last decade building open source methods through like excruciating public processes, mostly funded by folks like the PUC and the CDC and DOE and those utility. And then on-prem, but these are open. They're all mine still ongoing actually to apply a new idea, which is, this is math.
We have lots of data. Let's get everyone together and go through all of these little decisions and test all of the options. Anybody can come up with publicly against real data and agree how we're going to do it and not perpetuity. There's a process. We can get better, but we need a consistent standard, right?
There was a time in the U S when every state had a different definition for a bushel of corn. Which is one of the reasons why weights and measures is in the us constitution. You can't trade interstate. If you don't have, now we have one definition. You can't trade this shit and it's different. Everybody you ask.
Um, and so we built what are called the CalTRACK methods. Okay. Which is a set of methods. Actually, the hourly methods come from. Cause we looked at all the existing approaches. We could find a, something called a time of week temperature model. This is how we create a baseline, which came from LVL in the first place.
But we improved a considerably in the process because we opened it up and use real data to test it. And which generates an hourly baseline condition for every building. the looks at every month of the year, generates temperature bins for that month for that building, and then generates a regression model that correlates how that building opera in, closing open States uses energy relative to weather, highly predictive.
It turns out surprisingly predictive. Okay. A very standard way that you can verify. And we call those being able to verify and standardize. We call a revenue grade calculation. You can put it in a contract. We can approve, we followed it. Right. So that those methods and that code are open source, the open E meter code, which is what runs a CalTRACK methods as part of that is now in the Linux foundation.
So we're the primary operators, but we don't own it. Lots of people use it. It's well documented. Uh, we implemented, we implemented at scale and that's what we do particularly well, how do you take this code and implement it in a way that you can audit and how do you do it so that you can measure every meter on the grade every single night, you know, on a thousand servers.
That's what we do.
James Dice: [00:20:12] Okay. So what does this mean for all of us? Uh, certified measurement and verification professionals out there that have spent years in our spreadsheets. Um,
Matt Golden: [00:20:24] it's, we're in a transition. That's math. Okay. Yep. Paralyzed computing in a spreadsheet. Yeah, but there's still a lot of stuff.
That's not exactly math. Especially in individual assets. So we at the portfolio level utilize something called the law of large numbers to wash out most NRAS non-routine events, things like that. We want to do math on individual buildings, and you want to be like an energy services being, you have to be right on that building.
And something changes fundamentally in that building. Then you have to do stuff that's not actually that much math, which is make an adjustment and use an energy model and figure out what do we think happened and give everyone it's a con, I think of that as a changeable contract, actually. And acknowledging what it is.
Um, and so it's, so the core, like routine calculations, if it's routine, we're going to beat you every day grind definition. Right. Um, and we're gonna do a better job of it too, but there's all the non routine stuff. Which is a different story though, as you get it. But again, as you get into portfolios, we can wash most of that non-routine stuff out because some people buy hot tubs and some people, you know, have their kids go to school and some buildings Google moves into and some buildings go secant and like it washes out in a very predictable way.
Got it. Okay. But yeah, don't compete with real software in the cloud to do math. If you're doing it on a spreadsheet. A local server. Um, and that's, you know, some of the calculations where you doing would take 14 months on normal servers, run them on 10,000 at a time. Got it.
James Dice: [00:21:48] 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 want to understand how technology is changing things.
This course is also for you. The alumni are raving about the content, which they say pulls it all together, and they also love getting to meet the other students on the weekly zoom calls and in the private chat room, you can find out more about the course@courses.nexus lab. Start online. All right, back to the interview. All right.
So well, real quick. I wanted to ask you about like, there's a lot of companies out there, especially on the building software analytics software side that have their own ways of doing these calculations. So what would be the benefit of kind of standardizing on these smarter, more open methods that you guys are sort of promoting out there
Matt Golden: [00:22:43] because you're not allowed to measure yourself and get paid on your own measurement.
And it's like, there's always like, so back away from our shit for a minute, like I learned this stuff. Because after doing recurve, I did a bunch of other things, including spent a bunch of time during really sobered securitizations in that process. And what we're bringing to the table is we were like, Oh, you're so innovative.
And I'm like, not innovative, but we're trying to copy how this should actually gets done totally in the real world and the standardizing amount and be like, I like that kind of stuff. I'm a bit of a nerd, but I don't actually care. We just need a consistent weights and measures. Like it has to be good too, because we have to use the grid.
People have to believe it's real. I'm going to know is real, but like. In terms of like making this all happen. The important thing is it's consistent and replicable and definable, you put it in a contract, so you just can't do it, especially if like you were honest about how sensitive these calculations are.
And I just mean that in a general sense, like there's always a third party, like an asset classes, underwriting criteria with documentation and third-party verification all the time. Right, right. Whether it's your appraiser for behind your mortgage or your FICO score behind your credit score, you don't get to be like, no, trust me, I am credit worthy.
It doesn't carry weight. So I would just say like, all these companies who say like, we're going to go implement your work, measure it. You're going to pay us based on what we said happen. That's part of why we can't scale. And like the building owners are like, well, what? and so. And it's a terrible business anyways.
I don't really like, we can do it at scale, but like, why do you want to be an MNB? It just makes you less credible. And again, the more you know, about M and V and I think your audience does, and these hundreds and hundreds of little decisions. And I would encourage people to go to the CalTRACK website and look at the look at the actual technical requirements and ask how many of them you even heard of, how many of these decisions do you even know exist?
Most people that run the code don't even know what's going on behind the code. Right. Black box. So where are the anti-black box? Everything we, every method we use and all the coding, Ron is open to all parties. Anybody can run it these engineers can absolutely run these companies who are doing this can just literally pick it up and use it.
and then we can verify it. Cause he's still actually in implementation. It's so sensitive. you just, shouldn't, it's a conflict of interest flat out, and it's a big barrier in an industry that we just need to leap over. Totally.
James Dice: [00:24:57] Yeah. Yeah, absolutely. As someone who's done those calculations on the side of the ESCO, uh, it's just, it's, it's very different.
Matt Golden: [00:25:07] That's trust, trust. I can give you any number you want and I'll never know exactly.
James Dice: [00:25:12] Yeah, exactly. I, yeah. And I've also, so I've been in a situation where I've been the MNV person, right. Doing the calculations to show the savings. Uh, I've also been in a situation where I've had a black box provider. Try to get me to, uh, give my rubber stamp on their savings calculations.
And I've tried to reproduce them. And I've always been in this, like, you can't send the
Matt Golden: [00:25:35] box, it was worthless. Like we've looked at like managing models, these boxes, you can test them in a lab all day long, but how do you know how they were actually used as like, it doesn't even, it doesn't matter what it does in a lab when they're highly motivated, you can be super accurate and alive and we've seen it.
So like, we looked at like Ani building modeling side, which is a similar problem. That's where a lot of this came from, it was like, and I might recur, we built energy modeling software. And so we took all these molecules. He said, well, how do we let them in the market? we don't let people pick their tool.
So we created this like empirical test let's test. All these we'll have the providers, the software prove it works well. Here's a bunch of buildings, model it and look at actuals. Hey, here's a whole bunch of software that didn't iLab or great. They were very motivated to use it. Well, right in practice, the, we only delivered 30% of predicted results using the same software that can totally perform in a lab.
Wow. Why? I don't know, lots of reasons actually sent it to me. Like it's super freaking hard to use the software. People didn't give a shit. The people who were using it were just like, how quickly can I get a rebate, right? Or more than that. And the more savings their model showed the bigger the rebate. So like, what are you gonna get?
Crappy models with high savings.
James Dice: [00:26:38] So this with one another, one of the patterns that shows up on this podcast over and over again, which is there are so many people in the buildings industry that are doing the same thing in different ways, basically solving the problem. Same problem in different ways in different silos.
And building owners are paying for each. Each one to do it all differently across the whole entire industry. This is just one example.
Matt Golden: [00:27:00] Yeah. We're heavily there's way too much overhead, which is a massive drag on our scalability. And so like one challenge is there's a lot of people that make money in what we consider fat.
Totally. However, that's holding everybody back. So everyone's like, no, don't take my fat away. I need this fat to live. We would all go home and look the other way and say, let's go build muscle. And if we build muscle, everybody makes way more money and we're going to scale. And there's still like, when I talk about like, you know, are you an IPM, BP certified, you know, there's shit, tons of work out there, like.
But kind of like being 6% overhead on a small project in the stack, like let's make it really efficient and let's go get 60 more projects instead of that one. Right. And cause like the drag is insane. The complexity it's crazy.
James Dice: [00:27:43] This gives me a justification for what I did last month, which is let my a C a BP labs.
Matt Golden: [00:27:49] Uh, so we are completely IP MBP company. Well, yeah, but I'm going to say that's a problem. We're like, yeah, exactly. It's nothing. Right. Like you guys handle it. Principal. People are always like, Oh, we use IPM BP. And like that w you know, it doesn't mean a whole lot. It's like four general principles.
James Dice: [00:28:07] totally. Uh, all right, so let's talk about a couple of these, concepts that are enabled by. Hourly data, like you said, I just want to make sure I understand some of these terms. So you mentioned CalTRACK um, is that the same thing as open E meter? Is that,
Matt Golden: [00:28:25] well, there's a weird history there about how it came about, but Cal tracker methods that count triangular Caltrain, or it says like, here's how we're going to do it.
You're going to get hub. Here's all the research, blah, blah, blah. But here's, it's a finds, a set of methods and a technical reason why. Okay. And then open IE meter. Which, uh, got actually got split out because people who had black boxes were super pissed that we were building open method code. And so like politically we had to separate the two, never lived it, but it was because we got attacked by all these people being like you can't, you know, open source is going to kill innovation, which is total baloney.
So opening a meter in CalTRACK CalTRACK and the methods, but you can have methods up the wazoo. How do you know if they were followed in like we're rounding matters, you know, order of operations matter? So opening meter is the open source and what that means is anybody can use it for any purpose without restriction in the Linux foundation implementation.
That was Catherine. I see. Okay. And that's actually one of, really three major tools that we use. And it's actually, by the way, this is really important. The real problem with M and V is nobody can do it anymore, especially in commercial period. Okay. Why not? COVID okay. Yeah, the methods except for what I'm about to describe no longer work period.
And so the problem being is that I ended up, by the way, it doesn't matter a deemed savings from like utility sense that based on our work paper from two years ago, useless Uh, option C based on an energy model of last year,
James Dice: [00:29:50] doesn't make sense.
Matt Golden: [00:29:51] Yeah. And energy model in general, for any purpose, what assumptions are you going to use?
Right. How would I verify those assumptions? You're just guessing that's, that's a major issue. We've got to confront that these things are completely screwed and useless right now. All you measure is COVID and the problem is, is that there's this, especially in commercial, when we look across NACE codes, categories of buildings, like.
You know, a grocery is down by 4%, but 30% are up. And some of them up a lot, because like, you know, maybe they're open at 6:00 AM now to let you know people that have community issues in, um, some are closed. Um, you just, the ones that are like 75%. So. Very complicated. And they're all recovering at different rates, right?
Like everyone in Moran, I Aaron's recovering and some buildings are opening some aren't depends. What's in them very hard to tell, Oh shit, we have a stay at home order gang. One's going down again. Right. The beacon he's like, Oh, well, you know, we have our NRA handbook, which was another 150 pages of stuff you might want to do.
and they're like, well, just use that. you know, we just apply that and like, honestly, if you had an army, if you could camp out an engineer in every lobby, I don't think you can do it.
James Dice: [00:30:55] Yeah. If an engineer was just adjusted and they're making adjustments every time something changed it
Matt Golden: [00:31:00] too crazy.
Right? So when you say, well, what are you talking about? Cause you just described CalTRACK is option CIPM, BP, which it is so we don't have to, we always needed to, but now we have to have a two-step process. The second step is to And this is us. more concerning for everybody?
Accuracy and M and V on an individual building is no longer possible flat out. However, what we are able to do is provide revenue grade what we call settlement quality numbers on a portfolio or population. And we do that by using something called the grid meter. And, uh, this is we've been working on automating population, comparison groups, and the tools to get access to that data, which I'll describe next for the last few years.
So beginning of the summer, as some friends at DOE they've been funding a lot of our work and I was like, Holy crap, this is an emergency. Nobody can do MNV anymore. we have some ideas on how to do it. So they, they were good enough to fund us. We worked with a research partner, a CCA in California called MCs, made use of all their data smart meter data.
And that we generated a big working group of like top evaluation, thinkers and whatnot. And we said, all right, we know how to do this. We're going to use these methods. We developed two comparison groups and we'll be able to normalize for, uh, for COVID. So we got going and nothing worked, nothing even came close to working.
I couldn't come up with any way to make it work. We tried this, we tried that. We tried simple. We said complicated let's match. It. Let's match each individual customer to a portfolio of their bad doesn't work. Didn't work. Um, that was a worried, it was not ever going to work, but luckily in the middle, not really luck.
I got a really smart group of people. Um, we came up with a different approach, a really fundamentally different approach. Well, a lot of the words are not fundamentally different, but the approach is quite different, which is so we've created a, in the grid model, a set of methods and code all open source, same thing that allows us to look at a treated population and create something called a stratified sample, which is not a new idea in and of itself, except for how we're doing it.
So stratified samples like a political poll, right. You don't just pull it. You gotta, you gotta have a sample that represents your voters, you know, 20 year olds don't vote this, you know, maybe at the same rate as, as six year olds. Yeah. and so what we do is we run the opening meter on every single meter on the grid treated and untreated customers.
And then the difference we have is we know our voters are. That's the treating customers. Okay. And then we run because we have large-scale computing and you mean treated customers in terms of the company where we have projects, right. Projects, there's a group that has liked those folks so that we can deal with things like COVID or, you know, it's a peak event and they send out a, you know, there's radio ads or electric cars are happening, or, you know, the economy changed.
This is all stuff that doesn't get picked up in M and V and it can be profound in it's increasingly profound. With the grid transition going on and electrification, and like, can't just be adjusted away. Totally. So we look at those customers that actually got the retrofit done. We look across these 150 key metrics, like percent cooling, all this, these derivatives that CalTRACK spits out about these customers.
And then we look at the population and we run a process. You know, if you've heard, you've heard of like 40 chest. Â That's a joke actually, but it's a thing 40 10 days. Like something's really complicated 4d chess. Anyway, this is five D stratification. I, like I
James Dice: [00:34:06] said, 40 chest for DHS. Got it.
Matt Golden: [00:34:08] Okay. Cool. Look across in like in an automated way, look at every binning combination and also every combination of these 150 potential metrics in the population to generate a comparison group that matches that, that control group or the treated group. And it's crazy predictive. Um, okay. You know, we actually thought, we thought we had screwed up at the beginning.
Cause we, when we first got the first results out, cause it was a lot of work to be able to do it in the first place. A lot of cutting kind of coming in. Um, the comparison group was so close to the tree degree that we thought we had screwed up. Cause he couldn't see the difference until we zoomed in. And so what we do is we run that comparison group.
Uh, and then we difference the differences. So we. Say all right, you changed 17%, but the general population increased by 2%. And the difference though is when you get the net impact, net of the population changes that are current got out of COVID it works perfectly. It works amazingly well through COVID in commercial.
You do have to know NACE code because you can't be comparing beauty salons and grocery stores. But if you do with that one key thing, which, um, we always know, cause you can buy that in pro if you need to. Um, now we can do M and B. That's a nice
James Dice: [00:35:13] code. It's like what type of building it is this basically what type of space.
Matt Golden: [00:35:16] Exactly. Um, and then we, you suddenly called also funded by DOE something called energy differential, privacy, which is a privacy technique that Google uses on location data. It's actually being used in the us census Bureau, but it's never been used in energy, which is a method to inject random noise into datasets that allows us to use population data.
And obscured in such a way that it's not a privacy violation.
James Dice: [00:35:37] Got it. So if I'm a nail salon and I was supposed to shut down and I didn't, um, you can't, you know, out me basically,
Matt Golden: [00:35:46] right? So we're using samples. So like these are real customers, but there's no way to know who they are. And beyond that, there's no way to know what is true and what is actually just noise.
We're injecting. Okay. Um, very cool. It's how to break that stuff free. This is the excuse they add for not letting us use it right. Privacy. You can solve. So anyways, that is a freaking complicated way to say that we, well, one is question M and V right now people are not talking about this because it's an existential problem and no one wants to talk about it.
James Dice: [00:36:14] I've put it in the newsletter a few times. We'll put it. I I've been asking this question since about April, because when I was at Enrail, a couple of our projects got really derailed by the fact that we couldn't, we couldn't measure before and after effects of the software, we were testing and piloting.
So yeah,
Matt Golden: [00:36:29] I'll, I'll, there are P for P programs running in this traditional market. Like they like site based and like it's fricking nuts. So talking about that original point of like people measuring themselves right through, COVID like, We have companies who are retrofitting buildings, measuring your own shit, trying to make all these adjustments, and then someone's going to pay them directly for that,
James Dice: [00:36:45] especially when it's in their benefit that
Matt Golden: [00:36:48] people close my mind.
I I find it just so strange that nobody else that so many people don't seem to find that this is a problem. Oh, I,
James Dice: [00:36:57] yeah, I I'm a hundred percent with you. And a lot of people have responded. Like, I, I don't, I don't know what we're going to do. So what do you think we are going to do from like a single building?
And if I have a customer and they're an office building and we did say a performance contract two years ago, what am I doing right now? Like, what are we doing to say what the savings were?
Matt Golden: [00:37:18] So in that case, I think you have to stipulate to some degree. You're kind of just have to, I mean, again, or you. Again, I'm highly skeptical. If you take egos, NRI recipe, book of things, you can do that. Like, you, so you can come up with something, but really it's just a contract, not math. So, when you really need to do is go to the customer and agree to a contract team that says like, shit COVID, maybe we'll use last year's in stipulate, or here are the 16 adjustments we're going to make, but there's no, I mean, there's no way to verify it.
Yeah, no, it's just, and so, and it's log diminishing returns and it's another onion in a rabbit hole. It gets worse and worse and worse as you dig into it. Um, but at a different level the way, and this is, this is what we should be doing anyways. Is customers one of the reasons they don't tend to buy ESCO agreements except for like mush, municipal utilities, schools, and hospitals and fed federal, um, it's freaking complicated.
No one actually believes it. So, you know, w I see a big trend and I think we need to be looking at this as like cold beer and warm showers and looking at how risk is managed and like every other industry. And so again, there, and there are these energy services models, like the Mesa model managed energy service agreement, where instead of like trying to be perfect on each building and treating on each and every asset, you get a portfolio and you can buy insurance for that portfolio.
And you say, yeah, you know what? We're going to, you know, your bill was 1200 last year. It's going to be 800 this year. You're just going to pay me and I'm going to win and I'm going to win some, lose some across my portfolio. Yep. Sometimes that 1200 old bill ended up being $1,300. Sometimes it'll be $600, but in a very consistent way and give the customer something very simple and manage the risk.
Like an adult, let's take it to market. Risk is good. Risk is good. If it's manageable, individual buildings are not risk it's uncertainty. Hmm. But you package it all up into a building. Right. So if I'm getting a car loan, right. I would say I go scores of $700, have a 6% default rate. If I was doing that on one customer and they lost their job in default, I am screwed.
Right. You do that across a thousand customers. You're gonna get 6%. So. That's how risk is managed everywhere else. And contrary to popular belief, energy efficiency works the same way. And with the exception of like the most bespoke applications, the industrial buildings, the large-scale commercial buildings where you got to get a bit fancier because they're one-offs, um, it works really well in Rezi for sure.
Small business, no problem. Office buildings, retail. Groceries food services much more predictable. We wait, we wave our hands at this, that everything's a bespoke nightmare and it's not in our opinion. Um, and often we do, we generally know in advance by the way, who is a bespoke nightmare. And so the other thing is like, instead of building our whole industry around the 6% outliers that are really, really hard, let's build everything around the 94% that are down the middle and then decide what we do with the other 6%.
That's our approach on it. There are companies like we will look at buildings and like, If we can't model the baseline, they have, I don't know. I just, this is an actual example. I was just looking through it and I'm like, why is this one so wacky? And it was a, it was in the bottom floor was like one of those art studio things where you can like paint dishes.
And so it looks like, and we can't predict counts. Right. So if it's worth it. So the question then is what do you do? So this is a small enough asset stipulate. It who cares? It's like 1% of the portfolio. Or you could go in and hire an engineer to like figure it out when they run their killing or make an adjustment.
If it's big enough, just not big enough to bother, like we'll wash it out. It doesn't matter, but that's a, that's a business decision, not an SUV. Got it. Okay.
James Dice: [00:40:45] So I think a lot of what you described so far is sort of pinned on our. Sort of newfound hourly data. Right. Um, and this hasn't gone a whole all the way across the world yet.
Like not every building has hourly data yet, but a lot of this sort of depends
Matt Golden: [00:41:01] on that. So Caltrate has two sets of math, three sets of methods. Okay. Uh, monthly, daily and hourly.
James Dice: [00:41:08] Okay. So you can do it. If you just have your tilt,
Matt Golden: [00:41:11] we rarely ever touched daily because if you have daily, you generally have hourly.
Yeah, exactly. I went that way. We started with monthly because we didn't have hourly in them anyway. Okay. So, uh, we run monthly models are standardized, totally consistent. I mean, essentially prison months, you know, if you know the prison model like, and for just base-load heating, it's not rocket science, but doing it consistently did take three years because even though like the basic heating, cooling baseload model is not rocket science and construct with monthly data.
Squeezing out all the details and all the data cleaning rules and everything is hard and it sits on top. That's the same set of rules that both sit on, so you can get a consistent answer, but you can't fix the grid with that. And there's always more uncertainty because you're fitting to 12 data points, right.
It's tough. And there's also an inherent biases. Uh, it tends to underestimate certain shoulder months and overestimate other periods. And like those are inherent biases. Every time you do a monthly model that is baked in. Yep.
James Dice: [00:42:05] Yep. And then on the, on the other side of things doing the traditional way with hourly data is also really difficult.
It's just like too much. It doesn't work.
Matt Golden: [00:42:12] Yeah. It's just too much what everyone's doing, everyone that says that he was doing interval with traditional data. What they're actually doing is adding it up to month traditional models. Yeah, exactly. So yeah, the time of week temperature model is really a Dr.
Model. We're using it to unify EMDR. Like we don't care. We can actually tell the difference between long-term changes in short-term responses within the same signal. Um, we think of what we're doing as a unified field theory. We don't care what it is. We care, what did it do? And what's it worth? What's it worth as a function of what you're responding to?
Is it a market signal from the CAISO cause we're having a blackout or is it fighting the duck curve every single day, blackouts worth a lot more, but there's not much of that. Riding the duck curve every day is worth less but worth a lot. But a lot of it
James Dice: [00:42:56] let's talk about that. So. Well, let's kind of start high level for people like, like we talked about before we hit record, if I'm a building owner or I serve building owners, why should I care about demand?
Flexibility? Why should I care about everything you just said about the duck curve and the time of day and things like that? Can you, can you just like maybe
Matt Golden: [00:43:17] trying to fight climate change and carbonize put that aside? Cause nobody does this shit because of polar bears. In my experience, you had to write a big check.
Yeah. So I've had crazy environmentalist scoff at the big check when it comes down to it, right? So money you're leaving money on the table. That's why you care. So at a fundamental level, your customers investing in all this stuff in their building, that could be potentially doing harm or good actually to the grid and GHD is.
And you know, the thing we're fighting is that the, and the, really the reason to do this at a macro level is that as we decarbonize the grid, as we bring on renewables, Um, you might've noticed the sun rising and setting every day. Right? And so you ended up with like the supply of generation, not being coincidental with our peak, which is the most, it varies a lot, but in California, it's that seven to 9:00 PM window.
It's pretty common that you get like a late afternoon, coincidentally peak resi and commercial the same time. So the big idea, and what makes us valuable is that shifting load around is the new game in town. Right? We have to figure out how to use the clean energy we're generating at the times when it's most, when otherwise we'd be buying really expensive, dirty stuff.
So, you know, all the, obviously we think about storage and EVs and all that we have to actually, we think what's behind the meter. It's the same thing. Um, But there's also really simple other valuable stuff, right? Like if you've got a air conditioner and no attic insulation, there's no such thing as a flat reduction that will produce really valuable load shape impacts during the peak window.
Very reliable. It's not, it's not dispatchable, but it's valuable right there really isn't such a thing as a flat nothing, right. Refrigerators can be turned off, open connect does this, right? Like you can return, you can turn off frigerator for two hours. No problem. Right. It's not flat. So like, you know, a new refrigerator will be kind of a flat reduction, but you can also control the damn thing.
Okay. Okay. So, so the opportunity is to help solve that problem, which is a very expensive problem, which may, and there's not enough of any of the storage and EVs and all this crap. That's mostly aspirational anyways, not even close to enough of it. And the demand is going up up up, which means value goes up with it because there's not a supply.
Okay. No. Why. Because if you're not doing it, you're leaving money on the table, potentially really big money. Why should your customer use their creditor asset value to buy a set of benefits that goes to a utility for-profit utility in most cases? So the opportunity is to value that correctly so that you can reduce the cost to the customer, make more money scale your business.
And then the policy objective is that we want to give you a reason to do that. one of our aggregators does. refrigeration controls and they do utility programs, right. Left and center, but they're all based on averages. And so showing them the avoided cost in California, which is what drives our, when savings are valuable, you know, even though they're in all of these utility programs, no one ever asked them to reduce peak.
It didn't matter. Everyone was paid on averages. Right. So they're like, well, wait a minute. You're telling me if we just move our compressors as much out of those three hours in the summer, that's worth a lot or the whole lot. And so. You know what I, sometimes I don't mean this in a net negative, it comes up, this is like the moral compass to our industry, right?
Like we're totally fixated on customer benefits and in savings and in order to pivot. So we are also considering grid benefits in GHGs. We need to make them valuable and that's just how we do it. And like what we end up with and why this is great policy, is that now the market, you know, everybody that's touching buildings.
And, you know, there's all the cool people doing work out there today, but I also want to engage, you know, United technologies and all the big folks that control huge loads that like will never screw around with the utility program. I mean, like you're in the virtual power pamphlets and it's now, and you're going to make more money and get more customers, if you can figure out how to also deliver on grid benefits and GHG reductions.
Right.
James Dice: [00:46:48] Got it. And so what about the, buildings out there that don't have the incentives to. Take advantage of those so that they have, they have rates that are either flat or the rates are
Matt Golden: [00:46:59] today. Yeah. Rates are always a laggard. They never expressed the two grid value. You've all sorts of like edge case equity issues that are real.
And if a customer is getting savings on their bills, they end up with a savings cash flow, which largely they have to pay with their credit card. Um, So I think there's moral hazard and focusing entirely on bills now, you know, reasonable time of use rates is a good thing, but, and also just the complexity, like even large buildings, don't have people like you push this on the bills, you're making everybody an energy trader.
That's what you're doing. And people like the retailers, right. Like, you know, and it was like, Oh, they're on the market. They're like, they hedged their heads up to their eyeballs. And customers can't hedge. Right? So,
James Dice: [00:47:39] so if I'm doing a project,
Matt Golden: [00:47:42] so this is a wholesale signal, right? This is a signal between utility and the aggregator.
Okay. Well, you can manage that risk and, and not retail rates.
James Dice: [00:47:53] I see. Okay. So, so right now today, if I go do a demand, flexibility project, the utility for the most part is seeing the benefit of that. Unless there's some way for me to capture that value. Right? And so what you're saying is, as an aggregator, I can capture that value.
And then I could figure out how to provide that in the right way to my customers, which are the building owner.
Matt Golden: [00:48:15] Right. And it aligns the incentives to the whole system. Now you've got a reason to invest in this stuff. It allows you to finance it properly, like an integrated asset, manage the risk. Um, and to be honest, for all the MNV reasons we just described, we're never sure what the hell is happening on vintage real assets.
Right. Right, right. Right. And so the signal ends up being really messy to the customer anyways, like you saved energy and like, no, my kid went to college. You didn't save energy. I had a baby. Right. Like. This does not shift the customer should be dealing with. Right. Right.
James Dice: [00:48:43] It's also too complicated. They don't
Matt Golden: [00:48:44] care drastically too complicated.
James Dice: [00:48:46] So, okay. So you guys are basically saying here's
Matt Golden: [00:48:49] the thing. Yeah. Oh yeah. You're right. By the way, in complicated, it's worth like cappuccinos to the individual. Right. So you gotta roll it up to make it
James Dice: [00:48:55] useful, something like that, some terms that they actually care about. So, so you guys are coming through with software and saying, we're going to align the incentives in this system.
I think I'm starting to picture it now that for this whole conversation, I'm starting to get it, uh, get it fully, which is the point of this podcast. Can you talk about a couple of different terms? So what is a virtual power plant? And you've talked about it a bunch. I know what you're talking about,
Matt Golden: [00:49:20] and then it's a big, big idea.
So if you install installation, you're building a virtual power plant. If you put the controls on a building, you're proposing a virtual power plant. If you replace HVAC systems or installed storage or solar behind meters, you're building virtual power plant. If you send somebody an email they change their behavior for some event, you're building a virtual power plant.
If you're doing EMDR, it's all virtual power plant, we don't care. So it's really just a way to talk an integrated way to talk about all this stuff. So we stopped putting it in silos. first? It was a portfolio of buildings in a place affecting the grid in some way.
Right. And, uh, how you get there as beside the point it's that you've aggregated this, this resource it's reliable. We can measure its impact. It's a virtual power
James Dice: [00:50:03] plant. I can plug a bunch of interval meters in, you can do your calculations in your software and there's some sort of power being.
Matt Golden: [00:50:10] Well, what we're doing is we're measuring the change, right?
Like, so change virtual power plant. Like This, this aggregation of 500 buildings that have my controls and whatever our responding either to a long-term system. Like Hey, we want you to reduce, so we don't have to build that's distribution system, or there's no grid event.
That's responding like a power plant, but it's virtual. Yeah. And it's flexibility. So it doesn't have, you know, it's not exporting necessarily. It could. Um, but you're responding to the signal and it's equivalent to, right, like instead of building a power plant where deploying virtual power plants that do the same thing, because.
Producing electrons and using less of them has the same impact just happens to be producing less than, than tends to be cheaper, has no GHG impact. And also as a co-benefit, which is that it actually helps customers because you get better buildings too. Not just gridscale investments.
James Dice: [00:51:00] Totally. Well, okay.
So that's, I think that's a good intro to VPPs for everyone that does, hasn't heard. What about grid? Interactive buildings? So what about that concept?
Matt Golden: [00:51:10] You know, if you ask our buddies, we love cause they've funded a lot of our work. We have a different opinion. Like, you know, there's one aspect that there's one school of thought that says, this is kind of a, we have a very specific opinion about this, that, um, we need every building and every device in the building to be automatically controlled and some utility or somebody in the middle is gonna.
Control it all remotely. Okay. we think that's all true. Like, you know, but we just are not as diabolical about it in that, like we think control is going to come from the aggregator, like, okay, the derms system, the control system, isn't going to be some centralized. We're not going to replace like utilities.
We think are distributing, not, you know, distributed resources. They're not then going to be centralized to control, but you know, I'm not going to let the utility control on my smart toaster oven. Right, right. Yeah. I want that control or my contract with somebody to control it, but it's not going to be a one size fits all.
Um, and so we think we are absolutely doing great interactive buildings. We think we send a price signal to an aggregator that enables those buildings to react to the grid in whatever way makes the most sense for customers that they'll actually buy. And we think there's going to be lots of different ways.
That's going to look. That's the alternative view to like, everyone's going to use this DOE standard and, you know, PGD is going to control all my stuff. Right, right. Totally unreasonable. I mean, many of these utilities don't even know where their meters actually are. Like, I mean, I dunno, I'm going, I'm putting a lot of work on my own house and it's like bespoke nightmare for me to do it.
In my own house, right? The five contractors licenses, like I,
James Dice: [00:52:39] okay. So there's gonna be aggregators that are gonna basically design the grid interaction for their customers. And that they're going to have an agreement with our customers that there's trust involved in what's happening.
Matt Golden: [00:52:52] And I'm going to pick them.
They're not gonna afford it. Like, you know, I use OhmConnect for example. Fair warning of an advisor too, but like I connect, you know, sleep with truly, I've been connecting shit to controllers and they'll turn off for me during great events. But then I was like, I don't want you to, you know, I don't know.
But then I decided I don't want you to turn that thing off. So I have control over it. Like, I don't know. It's mine. Yeah. Yeah. So I believe, we believe fundamentally that the meter is the customer right on one side of the meter is the grid meter is the grid asset. That's where all the telemetry comes from and then everything behind the building.
Like, I'm pretty sure I own all the shit in my house. Yeah. Okay. You know, we don't think the grid extends into the house or into the building. And we think the utility monopoly has to have an edge also. Like, are we going to let utilities control transportation heating and cooling of all buildings, lighting refrigeration?
Where does that, like, where does that monopoly? And given everything runs on energy, are they just allowed to control the economy? Yeah. And that sounds hyperbolic, but like where's
James Dice: [00:53:50] the edge. So with this gap concept, do you picture there being multiple aggregators that serve different buildings?
So each building having multiple aggregators, like, do I need an aggregator for my electric vehicle charging systems? And then my  for
Matt Golden: [00:54:04] my age, it depends what the measurement barrier is. Some things we can isolate, but in general, we think like you will. At your master meter, have an aggregator that you'll choose to work with.
They may subcontract with others because how you break the savings out between devices is kind of a contractual agreement. Um, things that have meters on them, you know, car charging or solar can be isolated. We can take that out of the equation. That's a little bit of a sloppy answer. There's going to be different iterations of it.
Okay. Got
James Dice: [00:54:32] it. Cool. All right. So as we kinda wrap this up, this has been super helpful for me. Um, I want to ask you about. Your your answer to my favorite question. Uh, so I always do one question, ask everyone the same question So my question for this year is what's the number one thing you think needs to change, to unlock smart buildings, and you can define smart buildings, however you want.
Uh, you have a different perspective than most people on the podcast, but what's the number one thing you think needs to change to just sort of blow things up.
Matt Golden: [00:55:01] Boy, there are so many fun barriers to talk about here between, uh, access to large scale capital and competitive markets. And, um, I guess the, the fundamental thing that I believe we need to put in place is market access and competitive market access, right?
that, um, I believe businesses, whether it's the customer and the building or the aggregator, figuring out how to invest millions of dollars to build a business model and deploy it, um, respond to something called money and other things too. But we have to align incentives around what makes money, what is valuable.
And so, you know, it's pretty consistent what we've been talking about here, but I think. Having a price signal that makes doing good for the grid and the climate, outside of the four walls of the building is the critical thing that aligns interests. So that again, producing stuff that actually works becomes a source of profit to the market and a better deal to the customer.
And then everything flows from there. Right.
James Dice: [00:56:01] Yeah. So basically a cashflow stream that everyone agrees upon the calculations like we've been talking about that then creates the marketplace around.
Matt Golden: [00:56:09] And under that there's a, in a competitive market, we're not going to pick the winners and make more monopolies.
And then everyone's competing on the right grounds to go out and figure out how to build business models and deliver valuable solutions that actually work. And if they do that, they're gonna make more money and grow. Customers are gonna be happy. We're going to scale. Love
James Dice: [00:56:27] it. Love it. Cool. So last question.
What are you excited about for 2021?
Matt Golden: [00:56:32] Well, I'm no longer running around trying to convince utilities to give us a hundred grand so we can prove they have a problem. Um, we have a new administration coming in, which isn't gonna hurt either by the way. But, um, this is the year of the virtual power plant. We are decarbonizing rapidly in many places now.
Um, even prior to our new administration that just a hour or so ago happened. so I think we're in a quickening. and when I say like, we don't have to convince utilities to have a problem anymore. I think there's, you know, things move very slow into it. No, they don't. And I think we're approaching a inflection point where, you know, this is, we're not just going to write reports about barriers and, you know, run $6 million, pilot programs, but.
Things are going to start going faster and get bigger quickly, hopefully.
James Dice: [00:57:16] All right. That's a great place to kind of sign off. Thanks, Matt. I want to get an update from you at some point on this inflection point. Uh, but thanks for coming on the show. Thanks for educating us.
Matt Golden: [00:57:26] That was good. Thank you.
James Dice: [00:57:31] 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@nexuslabs.online. You can find the show notes for this conversation there as well. Have a great day.
âThis is like the moral compass to our industry, right? We're totally fixated on customer benefits and savings; and in order to pivot so we are also considering grid benefits and GHGs, we need to make them valuable, and this is how we do itâŚâ
âMatt Golden
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Episode 35 is a conversation with Matt Golden, CEO of Recurve.
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James Dice: [00:00:03] 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.
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Episode 35 is a conversation with Matt golden CEO of recurve. This episode is a bit of a change of pace from our normal topics, but it's an important one that all of you buildings, folks need to be aware of. As Matt says, if you're not aware of the grid benefits of your projects, you're probably leaving money on the table.
This is a deep dive into the past and present of energy efficiency. What's changed with COVID grid, flexibility, virtual power plants. Grid interactive buildings and much more, including more buzzwords without further ado, please enjoy nexus podcast, episode 35.
Matt Golden: [00:01:25] All right.
James Dice: [00:01:26] Hello, Matt. Welcome to the nexus podcast. Can you introduce yourself for everyone?
Matt Golden: [00:01:30] So, uh, my name is Matt golden. I'm a founder of recurve software, uh, actually recurve analytics, technically speaking. Uh, we provide tools for, uh, utilities and also a whole range of companies out in the marketplace.
We think of them as virtual power plant providers, or often call them aggregators that are providing all sorts of services too. All sorts of buildings, everything from solar to storage, to insulate and addicts, to IOT devices, we're totally agnostic. We think there's a lot of amazing stuff out there. Um, stuff that produces great benefits, that often and get paid for it.
So we end up with customers paying out of pocket, and we don't think that's right. We think the utility industry should pay their freight and that's better for everybody. So we provide, we actually sell mostly to utilities and provide a solution that helps them figure out which buildings are. Causing them, the grid issues where the peaks coming from, what end uses and enables them to engage the market, uh, sometimes through traditional programs, but increasingly through what we call marketplace approaches, where they work with the companies out there that have, are building the business models and the financing solutions and the broad range of types of solutions and technologies.
We need to serve building owners, uh, in a much more streamlined market-based approach that gets paid for the performance where we can actually track the impact that these projects are Having, I think it is. A new breed of really automated MNV on an hourly basis that lets us quantify that impact and also value.
What is that great impact? What is it worth in terms of transmission and distribution, uh, capacity, energy, GHG impacts, and so that these aggregators can actually monetize the value of what they're providing, like a virtual power plant and make more money and doing the right stuff and pass that savings back to customers.
So they buy more of it and everybody wins. Um, So by way of background, uh, I started in kind of think like an aggregator. Â and the audio workforce, you to know what I'm pointing at, but I have my sustainable spaces, which was my original company now, quite a while ago, shingle from our old offices, but, uh, I'm a contractor at heart.
So it was in the solar industry. Kind of a silly now, but got old fed up with rebates were coming and going and all. And, uh, and all of that and that the bug on energy efficiency and said, why are we putting panels on these buildings that are bleeding energy out everywhere. We should go fix the buildings first.
And so, uh, sustainable spaces was a full service building. Science-based home performance company. We also did some work in commercial and multifamily. Um, It started out thinking like, yeah, we're going to build software because I had a technology background and make this automated streamlined thing. And next thing we know, I got five contractor licenses and 10 trucks and we're vertically integrated because the only way to make money, it turns out.
Um, but really stymied, you know, uh, we worked really hard to get the utilities, to create programs, to make us go faster and they just cause pain. It turns out if you get paid in advance based on a rebate, which is the traditional method. If you're in the business and you're doing good work and you have engineers and blower doors and impaired cameras, you make less money than the average guy who doesn't right.
Everyone paid exactly the same amount, the way you make more money as you reduce your cost of goods sold in the low to the bottom. Yeah. Theaters, the folks producing the least value are actually getting the most profit and trying to get incentive structure. Conversely, you know, AC Tripoli and everybody's running around saying energy efficiency is the first fuel.
We should do it. You know, it's the most important resource, but it doesn't actually behave like one and it's certainly not valued like one, so it's not worth enough to be true. Um, and so that's probably trying to solve, how do we move from that pay for products in advance based on some average, regardless how it actually performs.
Pay that to the customer so that, you know, the market's not even making money through that channel. It's a witch misaligned, the incentives further. Um, and then the flip side of that, as well as, you know, and we call that paper performance, which is. That's actually the core of what we're going to talk about.
If you're going to pay for performance, the starting point, and really the core of our business is you have to know what you're paying for. What is the product? What is energy efficiency? And you, if you have it delve down this rabbit hole and it's comedy, it's like an onion dropped to the bottom of a rabbit hole.
So it sounds a little easier than it is because it's a derivative, it's a calculated value. So if you're gonna bet on a calculated value, you got to know what that calculation is, or you end up fighting over it and that's all you end up doing. Um, so everyone's got to believe it's real. We also got to put in a contract and generate an invoice and get paid and not end up just litigating how weather stations were chosen or things like that.
But okay. And on the other side of it, well, I'll give you one more piece. This is the other principle we'll talk about, which is when I was in the contracting business, we knew for sure that a two in the afternoon was peak, right? Solar was just solar and the duck curve hadn't really started. We had monthly meters, Different world entirely.
So in this transition, the pay for performance am I smart meter data started coming online. All of a sudden, Holy crap, this duck curve thing is real. It's not, it's actually happening and like, it's really going to happen, guys. So, um, as we talk about this pivot from like efficiency as a nice to have, do goodery to efficiency as a valuable resource, it's critical.
And like the big leap in value is moving from an average of by month reduction. But let me give you all a secret utilities. Don't want to sell less of stuff. but to actually quantifying when and where it's happening, so demand. And so everything we're doing now is on an hourly basis and a locational basis.
And that's really the turning point where instead of just writing white papers about how we're a resource, we start behaving like one and we can actually migrate from like programs to the resource stack to be a procurement, actual resource. And that's important because it's a lot more valuable.
Totally.
James Dice: [00:06:42] And the reason I wanted to have you on as a great intro, by the way. And the reason I wanted to have you on is because the nexus audience we're all thinking about things for behind the meter, but that's changing. We can't continue to think
Matt Golden: [00:06:54] we're going to connect
James Dice: [00:06:54] all that stuff. Exactly.
Yeah. Yeah. So we can't continue to, as, as a nexus community, can't continue to think just behind the meter, because things are starting to get a little bit convoluted,
Matt Golden: [00:07:05] at the neck, leaving money on the table. When you do that.
James Dice: [00:07:10] Yeah, that's a great point. So before we dive into all that stuff, cause I want to unpack basically everything you just said for everyone.
Um, I want to ask you about that shingle you have behind you, which is I saw a video on your LinkedIn profile of you at Ellen's home doing an energy audit. Can you
Matt Golden: [00:07:29] talk a little bit, a lot of time across spaces. I've done my dues. but yeah, I, you know, the context, it was, I think it was like an earth day show or something, but, uh, it was like a solid seven half minutes in my 15 minutes of fame.
Cause I did get recognized because like I did such a great job auditing our house, but it was Ellen's house. So like diehard, Ellen fans know that episode or knew that episode. So I would, I would actually get people being like, you're that guy, but again, it wasn't because they were super excited about energy efficiency.
Yeah. Yeah, it's pretty fun. And, uh, I don't know. She was nice enough to me. I don't know whatever everybody says.
James Dice: [00:07:58] Yeah, no, I enjoyed it. You were like trying to work in like the nerdy energy efficiency terms, like Phantom loads to an Allen, just trying to make jokes. So it was,
Matt Golden: [00:08:07] he did tell me, and actually some people, even this, all this like stuff that's been going on, I got the instructions like.
You don't have to try to be funny. And I was like, thank you.
James Dice: [00:08:14] Thank you. Oh, it's got
that
Matt Golden: [00:08:17] piece go one or two little ones in there. But
James Dice: [00:08:20] the thing I wanted to tell you is it that you're the second Georgetown alum that's been on the podcast. I don't know if you know Logan soya from uh Agricor.
Matt Golden: [00:08:29] but I can help, but I should, because, uh, there was like a little G town clean tech crew.
James Dice: [00:08:33] Yeah. Yeah, totally. I can send you an intro. Well, so that was a great, intro into recurve. Um, so let's dive into some of that stuff you just, introduced us.
So, I want to give you my background a little bit, cause I think it'll help you kind of. Take us off into this next phase of the conversation. So I've done a lot in like the, what you just described as kind of like the old way to do energy efficiency. So, applying for incentives, submitting calculations to incentive programs, helping my clients, which are building owners.
Awesome. Uh, it was not awesome. No, it was actually not fun at all. I learned how to get kind of game the system and figure out how to build energy models really quickly to kind of like prove something that was happening. Right. so I think a lot of people are kind of familiar with that old world, especially in mechanical engineers that have been doing energy management sort of projects for awhile, retro commissioning, commissioning that, that type of thing.
Um, Can you kind of talk about like the old world and then the new world that we're coming into.
Matt Golden: [00:09:35] So the most important thing is it's not like one or the other it's about, you still have to like engineer a good solution. That works. Right. But the way we think about it is we also think about behind the meter.
Right. And we want to, we want to be open The diversity of solutions and engineering and stuff that goes on behind the meter, do its thing and hold it accountable to those outcomes, but not micromanage it. And that's really the difference. I mean, you know, energy models make a lot of sense for certain types of projects.
You should do them if it helps, right? Like whatever, engineering that you do, product selection, implementation, training, like instead of prescribing all of that. And micromanaging and double-checking it because there's no accountability to the results. Right. And so you put yourself in like the old world and the old world.
I put air, air quotes for the listeners. Um, it's not old at all. Like mostly still what we do almost everywhere. Most utilities are still, if you're going to submit a bunch of paperwork in a super complicated energy model that like, I can't even begin to understand. And then I'm going to pay a bunch of money based on that.
And then like, if I'm a utility, like that's what if that didn't work? And so they don't really have a choice. Right? How else, how else do I make sure you're not trying to screw me and you call it gaming. I don't even think he was gaming. Like, he'd give me crazy rules. He paid me to the wrong stuff.
Like I'm going to do it, but you know, that's like a job. And so there's a fundamental mistrust because everyone does overestimate. Cause like you're paid to do that at the end of the day and their shoes. What else are they going to do? Like give me everything. And I'm going to try to make sense of this bespoke nightmare you've given me and yeah.
And if I just micromanage every single thing you do, maybe it'll work. Which of course it doesn't because you either go out of business or you game the system and get around them. Cause your information asymmetry here. Right. So. engineering a good quality work. Doesn't go away at all. In fact, good quality, energy models, engineering, and high quality work now becomes a source of profit in this model because you're not crying, but the trade is you become accountable that it actually has to work to get paid.
Hmm, right. That's the trade-off, but you're training that for all the bullshit. Okay. So the basis of the model is like we have standardized M and V, especially the smart meter data. We have agreed to how it's tracked. We can measure how these things are doing transparently lightly. Um, and then you'll get agreed to pay for your, what we call pay for performance, which is we sent flexibly purchase agreements, which is.
you know, you're an aggregator, what do we call an aggregator company? Let's do. What do you mean by aggregator company? That doing stuff with customers, like get customers to agree to do it, what you're doing and assign this value to you. You can be a finance company, a large contractor, you know, lighting as a service company has got a phone with one of them, uh, provider, uh, it can be unconnected.
Can we Google? Like,
James Dice: [00:12:11] yeah. So, but aggregator is going to charge the customer to do something and then they're going to. Apply for these incentives or rebates on behalf of their customer,
Matt Golden: [00:12:21] which is the building performance payments. Cause it's only about incentives and rebates. Sounds like they're giving you something for free.
You're actually getting paid for something you're delivering. That's valuable. Um, and sort of thinking, this is like two things how you deliver your services to your customers is your business. And they're going to buy it based on benefits they receive, right? We're bills, often comfort, better lights that make their products look better, whatever it is.
And we want to just leave that. To be your business between you and your customer and how you get paid for that. Do they give you cash money? Do they do at least an energy service agreement of your business? That's the customer's cashflow. Got it. We're talking about a tertiary cashflow that says, you know, You've actually done lighting in 350 homes on a part of the grid. That has a peak problem, right? Or more accurately. How about this? I mean, he's a real pickup actually. You know, we have a peak problem in our blackouts in August happened, you know, at 7:00 PM or you know, actually between five and eight.
Right. And we have this coincidental HVAC peak with like a commercial peak. And if you, so you go in and put an air conditioners in and you insulate addicts. You're producing benefits that accrue not to your customer, but to the utility because they don't have to buy $1,400 megawatt hours, right. Or as we install electric vehicles and all this stuff, all of a sudden we're really stressing our distribution network.
They can spend millions of dollars on a new distribution system or potentially they can reduce load and not have to. That's a mutual benefit. So in addition to that customer benefit, right, we're creating a tertiary cashflow. That's the virtual power plant that says you as an aggregator now can get paid for the virtual power plant.
You're creating the transmission and distribution value, the capacity, the energy, the GHGs, the stuff that doesn't accrue to your customer. We don't want them paying with their credit card for the full freight. And then you shouldn't be giving that to PGD or a con ed or combat or whoever she could pay for that.
and so that's what this model is. And it's setting up that grid value. So that as an aggregator, you go out, do your work, and you're also building power plant getting paid for. And you can take that cashflow we're about all about aligning incentives, right? And you can figure what you're gonna do with it.
Are you going to buy down your customer costs like a rebate? Are you going to reduce their interest rate or you can do better marketing? How are you going to do in a competitive market? Cause we don't pick winners. Right. And that's the thing that's actually what. Keeps everybody honest, right? Is that we're not going to run an RFP and be like you win you're it you're the monopoly, which is also the fundamental flaw in the traditional system.
Right. Um, and so go forth. And so what that produces is a model that says as an aggregator, if you can figure out how to sell your product to a customer in a way that they value. That simultaneously delivers the, and you've kind of value engineer, right? It's not, how do I deliver the best benefit of the customer and maximize the grid benefits and the GHG reductions.
And if you do that right, you make more money. Your customer gets a better deal. And we get a stable, clean grip. That's the plan. Got it.
James Dice: [00:15:04] So just thinking about the, kind of the old way to do it, and I'm still kind of like all the way new way. Maybe that's not the right way to think about it because we're in a transition, right?
So
Matt Golden: [00:15:17] we're stuck in the middle or in the
James Dice: [00:15:19] middle of purgatory. The old way was I'm going to do energy efficiency projects. I'm going to upgrade something, right. And part of that is going to be this incentive, this free incentive or rebate check. So what's the new model. And I think I know it. I'll just try it.
You tell me if I'm wrong. So now I'm going to do that same project and I'm going to get payments on the backend for the actual calculated energy savings at the meter or demand. The change in demand profile at the meter. And so your software kind of sits there and says, this is that number that's Rob.
Matt Golden: [00:15:55] Okay. And what you do that money. So you create this, created a cashflow. So finding anything cash flows is called infrastructure investing. Yep. That's project finance, right? Not financing projects with a credit card. So you're actually, so you have this cashflow you're creating that in a portfolio is incredibly stay one consistent that you can finance and bring forward.
And then again, your customer doesn't even really necessarily have to know it's there ultimately, but you figure out how to use that cash flow to grow your business and get more customers.
James Dice: [00:16:24] Okay. So if I'm an aggregator, I'm just thinking about this totally different now, instead of being like, uh, In the past, I was like, you could call what I've done an aggravator. And I was like a trade ally and the local utility program. So what would be the new model for that, with the setup.
Matt Golden: [00:16:40] So again, we're, you would get a flexibility purchase agreement, which gives you access to these markets. you go about your business, you figure out how to sell to your customers.
You enroll those projects, you get paid for their performance over time. Basically it, And so what our role on that is we are not an aggregator ever, that would be a conflict of interest. So, so we spent the last decade coming out of sustainable spaces, trying to figure out how to solve this problem and starting with the fact that you can't, this shit is not real and you can't pay for performance.
For sure. If you don't have an agreement on what it is in the first place. And the problem is a bit of a joke, but it's true. You take IP VIP option C or evaluation methods, anybody, and you. There's there's flaws in it to begin with. But the real problem is if you ask five engineers to give you the savings on the same 50 buildings, you're going to get 17 answers.
And the punchline is there. All right, because we haven't agreed to anything. Okay. And it's really profound. There's hundreds and hundreds of choices that would blow your mind. And I'd have to explain on Benning methods and, you know, balance point temperature, but a big one. So I didn't put a heat pump my own house.
Right. And if you use the nearest weather station, you end up with Napa I'm in Morin. Okay. Close to me, but it's hot. My savings 15%. If you pick the closest in weather in climate zone, which is what the methods we deploy, use B you get SFO, which is 1.2 miles away, San Francisco airport, further away than Napa.
And I say 23%. Okay. Right. I says, who's right. So. You know, we spent the last decade building open source methods through like excruciating public processes, mostly funded by folks like the PUC and the CDC and DOE and those utility. And then on-prem, but these are open. They're all mine still ongoing actually to apply a new idea, which is, this is math.
We have lots of data. Let's get everyone together and go through all of these little decisions and test all of the options. Anybody can come up with publicly against real data and agree how we're going to do it and not perpetuity. There's a process. We can get better, but we need a consistent standard, right?
There was a time in the U S when every state had a different definition for a bushel of corn. Which is one of the reasons why weights and measures is in the us constitution. You can't trade interstate. If you don't have, now we have one definition. You can't trade this shit and it's different. Everybody you ask.
Um, and so we built what are called the CalTRACK methods. Okay. Which is a set of methods. Actually, the hourly methods come from. Cause we looked at all the existing approaches. We could find a, something called a time of week temperature model. This is how we create a baseline, which came from LVL in the first place.
But we improved a considerably in the process because we opened it up and use real data to test it. And which generates an hourly baseline condition for every building. the looks at every month of the year, generates temperature bins for that month for that building, and then generates a regression model that correlates how that building opera in, closing open States uses energy relative to weather, highly predictive.
It turns out surprisingly predictive. Okay. A very standard way that you can verify. And we call those being able to verify and standardize. We call a revenue grade calculation. You can put it in a contract. We can approve, we followed it. Right. So that those methods and that code are open source, the open E meter code, which is what runs a CalTRACK methods as part of that is now in the Linux foundation.
So we're the primary operators, but we don't own it. Lots of people use it. It's well documented. Uh, we implemented, we implemented at scale and that's what we do particularly well, how do you take this code and implement it in a way that you can audit and how do you do it so that you can measure every meter on the grade every single night, you know, on a thousand servers.
That's what we do.
James Dice: [00:20:12] Okay. So what does this mean for all of us? Uh, certified measurement and verification professionals out there that have spent years in our spreadsheets. Um,
Matt Golden: [00:20:24] it's, we're in a transition. That's math. Okay. Yep. Paralyzed computing in a spreadsheet. Yeah, but there's still a lot of stuff.
That's not exactly math. Especially in individual assets. So we at the portfolio level utilize something called the law of large numbers to wash out most NRAS non-routine events, things like that. We want to do math on individual buildings, and you want to be like an energy services being, you have to be right on that building.
And something changes fundamentally in that building. Then you have to do stuff that's not actually that much math, which is make an adjustment and use an energy model and figure out what do we think happened and give everyone it's a con, I think of that as a changeable contract, actually. And acknowledging what it is.
Um, and so it's, so the core, like routine calculations, if it's routine, we're going to beat you every day grind definition. Right. Um, and we're gonna do a better job of it too, but there's all the non routine stuff. Which is a different story though, as you get it. But again, as you get into portfolios, we can wash most of that non-routine stuff out because some people buy hot tubs and some people, you know, have their kids go to school and some buildings Google moves into and some buildings go secant and like it washes out in a very predictable way.
Got it. Okay. But yeah, don't compete with real software in the cloud to do math. If you're doing it on a spreadsheet. A local server. Um, and that's, you know, some of the calculations where you doing would take 14 months on normal servers, run them on 10,000 at a time. Got it.
James Dice: [00:21:48] 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 want to understand how technology is changing things.
This course is also for you. The alumni are raving about the content, which they say pulls it all together, and they also love getting to meet the other students on the weekly zoom calls and in the private chat room, you can find out more about the course@courses.nexus lab. Start online. All right, back to the interview. All right.
So well, real quick. I wanted to ask you about like, there's a lot of companies out there, especially on the building software analytics software side that have their own ways of doing these calculations. So what would be the benefit of kind of standardizing on these smarter, more open methods that you guys are sort of promoting out there
Matt Golden: [00:22:43] because you're not allowed to measure yourself and get paid on your own measurement.
And it's like, there's always like, so back away from our shit for a minute, like I learned this stuff. Because after doing recurve, I did a bunch of other things, including spent a bunch of time during really sobered securitizations in that process. And what we're bringing to the table is we were like, Oh, you're so innovative.
And I'm like, not innovative, but we're trying to copy how this should actually gets done totally in the real world and the standardizing amount and be like, I like that kind of stuff. I'm a bit of a nerd, but I don't actually care. We just need a consistent weights and measures. Like it has to be good too, because we have to use the grid.
People have to believe it's real. I'm going to know is real, but like. In terms of like making this all happen. The important thing is it's consistent and replicable and definable, you put it in a contract, so you just can't do it, especially if like you were honest about how sensitive these calculations are.
And I just mean that in a general sense, like there's always a third party, like an asset classes, underwriting criteria with documentation and third-party verification all the time. Right, right. Whether it's your appraiser for behind your mortgage or your FICO score behind your credit score, you don't get to be like, no, trust me, I am credit worthy.
It doesn't carry weight. So I would just say like, all these companies who say like, we're going to go implement your work, measure it. You're going to pay us based on what we said happen. That's part of why we can't scale. And like the building owners are like, well, what? and so. And it's a terrible business anyways.
I don't really like, we can do it at scale, but like, why do you want to be an MNB? It just makes you less credible. And again, the more you know, about M and V and I think your audience does, and these hundreds and hundreds of little decisions. And I would encourage people to go to the CalTRACK website and look at the look at the actual technical requirements and ask how many of them you even heard of, how many of these decisions do you even know exist?
Most people that run the code don't even know what's going on behind the code. Right. Black box. So where are the anti-black box? Everything we, every method we use and all the coding, Ron is open to all parties. Anybody can run it these engineers can absolutely run these companies who are doing this can just literally pick it up and use it.
and then we can verify it. Cause he's still actually in implementation. It's so sensitive. you just, shouldn't, it's a conflict of interest flat out, and it's a big barrier in an industry that we just need to leap over. Totally.
James Dice: [00:24:57] Yeah. Yeah, absolutely. As someone who's done those calculations on the side of the ESCO, uh, it's just, it's, it's very different.
Matt Golden: [00:25:07] That's trust, trust. I can give you any number you want and I'll never know exactly.
James Dice: [00:25:12] Yeah, exactly. I, yeah. And I've also, so I've been in a situation where I've been the MNV person, right. Doing the calculations to show the savings. Uh, I've also been in a situation where I've had a black box provider. Try to get me to, uh, give my rubber stamp on their savings calculations.
And I've tried to reproduce them. And I've always been in this, like, you can't send the
Matt Golden: [00:25:35] box, it was worthless. Like we've looked at like managing models, these boxes, you can test them in a lab all day long, but how do you know how they were actually used as like, it doesn't even, it doesn't matter what it does in a lab when they're highly motivated, you can be super accurate and alive and we've seen it.
So like, we looked at like Ani building modeling side, which is a similar problem. That's where a lot of this came from, it was like, and I might recur, we built energy modeling software. And so we took all these molecules. He said, well, how do we let them in the market? we don't let people pick their tool.
So we created this like empirical test let's test. All these we'll have the providers, the software prove it works well. Here's a bunch of buildings, model it and look at actuals. Hey, here's a whole bunch of software that didn't iLab or great. They were very motivated to use it. Well, right in practice, the, we only delivered 30% of predicted results using the same software that can totally perform in a lab.
Wow. Why? I don't know, lots of reasons actually sent it to me. Like it's super freaking hard to use the software. People didn't give a shit. The people who were using it were just like, how quickly can I get a rebate, right? Or more than that. And the more savings their model showed the bigger the rebate. So like, what are you gonna get?
Crappy models with high savings.
James Dice: [00:26:38] So this with one another, one of the patterns that shows up on this podcast over and over again, which is there are so many people in the buildings industry that are doing the same thing in different ways, basically solving the problem. Same problem in different ways in different silos.
And building owners are paying for each. Each one to do it all differently across the whole entire industry. This is just one example.
Matt Golden: [00:27:00] Yeah. We're heavily there's way too much overhead, which is a massive drag on our scalability. And so like one challenge is there's a lot of people that make money in what we consider fat.
Totally. However, that's holding everybody back. So everyone's like, no, don't take my fat away. I need this fat to live. We would all go home and look the other way and say, let's go build muscle. And if we build muscle, everybody makes way more money and we're going to scale. And there's still like, when I talk about like, you know, are you an IPM, BP certified, you know, there's shit, tons of work out there, like.
But kind of like being 6% overhead on a small project in the stack, like let's make it really efficient and let's go get 60 more projects instead of that one. Right. And cause like the drag is insane. The complexity it's crazy.
James Dice: [00:27:43] This gives me a justification for what I did last month, which is let my a C a BP labs.
Matt Golden: [00:27:49] Uh, so we are completely IP MBP company. Well, yeah, but I'm going to say that's a problem. We're like, yeah, exactly. It's nothing. Right. Like you guys handle it. Principal. People are always like, Oh, we use IPM BP. And like that w you know, it doesn't mean a whole lot. It's like four general principles.
James Dice: [00:28:07] totally. Uh, all right, so let's talk about a couple of these, concepts that are enabled by. Hourly data, like you said, I just want to make sure I understand some of these terms. So you mentioned CalTRACK um, is that the same thing as open E meter? Is that,
Matt Golden: [00:28:25] well, there's a weird history there about how it came about, but Cal tracker methods that count triangular Caltrain, or it says like, here's how we're going to do it.
You're going to get hub. Here's all the research, blah, blah, blah. But here's, it's a finds, a set of methods and a technical reason why. Okay. And then open IE meter. Which, uh, got actually got split out because people who had black boxes were super pissed that we were building open method code. And so like politically we had to separate the two, never lived it, but it was because we got attacked by all these people being like you can't, you know, open source is going to kill innovation, which is total baloney.
So opening a meter in CalTRACK CalTRACK and the methods, but you can have methods up the wazoo. How do you know if they were followed in like we're rounding matters, you know, order of operations matter? So opening meter is the open source and what that means is anybody can use it for any purpose without restriction in the Linux foundation implementation.
That was Catherine. I see. Okay. And that's actually one of, really three major tools that we use. And it's actually, by the way, this is really important. The real problem with M and V is nobody can do it anymore, especially in commercial period. Okay. Why not? COVID okay. Yeah, the methods except for what I'm about to describe no longer work period.
And so the problem being is that I ended up, by the way, it doesn't matter a deemed savings from like utility sense that based on our work paper from two years ago, useless Uh, option C based on an energy model of last year,
James Dice: [00:29:50] doesn't make sense.
Matt Golden: [00:29:51] Yeah. And energy model in general, for any purpose, what assumptions are you going to use?
Right. How would I verify those assumptions? You're just guessing that's, that's a major issue. We've got to confront that these things are completely screwed and useless right now. All you measure is COVID and the problem is, is that there's this, especially in commercial, when we look across NACE codes, categories of buildings, like.
You know, a grocery is down by 4%, but 30% are up. And some of them up a lot, because like, you know, maybe they're open at 6:00 AM now to let you know people that have community issues in, um, some are closed. Um, you just, the ones that are like 75%. So. Very complicated. And they're all recovering at different rates, right?
Like everyone in Moran, I Aaron's recovering and some buildings are opening some aren't depends. What's in them very hard to tell, Oh shit, we have a stay at home order gang. One's going down again. Right. The beacon he's like, Oh, well, you know, we have our NRA handbook, which was another 150 pages of stuff you might want to do.
and they're like, well, just use that. you know, we just apply that and like, honestly, if you had an army, if you could camp out an engineer in every lobby, I don't think you can do it.
James Dice: [00:30:55] Yeah. If an engineer was just adjusted and they're making adjustments every time something changed it
Matt Golden: [00:31:00] too crazy.
Right? So when you say, well, what are you talking about? Cause you just described CalTRACK is option CIPM, BP, which it is so we don't have to, we always needed to, but now we have to have a two-step process. The second step is to And this is us. more concerning for everybody?
Accuracy and M and V on an individual building is no longer possible flat out. However, what we are able to do is provide revenue grade what we call settlement quality numbers on a portfolio or population. And we do that by using something called the grid meter. And, uh, this is we've been working on automating population, comparison groups, and the tools to get access to that data, which I'll describe next for the last few years.
So beginning of the summer, as some friends at DOE they've been funding a lot of our work and I was like, Holy crap, this is an emergency. Nobody can do MNV anymore. we have some ideas on how to do it. So they, they were good enough to fund us. We worked with a research partner, a CCA in California called MCs, made use of all their data smart meter data.
And that we generated a big working group of like top evaluation, thinkers and whatnot. And we said, all right, we know how to do this. We're going to use these methods. We developed two comparison groups and we'll be able to normalize for, uh, for COVID. So we got going and nothing worked, nothing even came close to working.
I couldn't come up with any way to make it work. We tried this, we tried that. We tried simple. We said complicated let's match. It. Let's match each individual customer to a portfolio of their bad doesn't work. Didn't work. Um, that was a worried, it was not ever going to work, but luckily in the middle, not really luck.
I got a really smart group of people. Um, we came up with a different approach, a really fundamentally different approach. Well, a lot of the words are not fundamentally different, but the approach is quite different, which is so we've created a, in the grid model, a set of methods and code all open source, same thing that allows us to look at a treated population and create something called a stratified sample, which is not a new idea in and of itself, except for how we're doing it.
So stratified samples like a political poll, right. You don't just pull it. You gotta, you gotta have a sample that represents your voters, you know, 20 year olds don't vote this, you know, maybe at the same rate as, as six year olds. Yeah. and so what we do is we run the opening meter on every single meter on the grid treated and untreated customers.
And then the difference we have is we know our voters are. That's the treating customers. Okay. And then we run because we have large-scale computing and you mean treated customers in terms of the company where we have projects, right. Projects, there's a group that has liked those folks so that we can deal with things like COVID or, you know, it's a peak event and they send out a, you know, there's radio ads or electric cars are happening, or, you know, the economy changed.
This is all stuff that doesn't get picked up in M and V and it can be profound in it's increasingly profound. With the grid transition going on and electrification, and like, can't just be adjusted away. Totally. So we look at those customers that actually got the retrofit done. We look across these 150 key metrics, like percent cooling, all this, these derivatives that CalTRACK spits out about these customers.
And then we look at the population and we run a process. You know, if you've heard, you've heard of like 40 chest. Â That's a joke actually, but it's a thing 40 10 days. Like something's really complicated 4d chess. Anyway, this is five D stratification. I, like I
James Dice: [00:34:06] said, 40 chest for DHS. Got it.
Matt Golden: [00:34:08] Okay. Cool. Look across in like in an automated way, look at every binning combination and also every combination of these 150 potential metrics in the population to generate a comparison group that matches that, that control group or the treated group. And it's crazy predictive. Um, okay. You know, we actually thought, we thought we had screwed up at the beginning.
Cause we, when we first got the first results out, cause it was a lot of work to be able to do it in the first place. A lot of cutting kind of coming in. Um, the comparison group was so close to the tree degree that we thought we had screwed up. Cause he couldn't see the difference until we zoomed in. And so what we do is we run that comparison group.
Uh, and then we difference the differences. So we. Say all right, you changed 17%, but the general population increased by 2%. And the difference though is when you get the net impact, net of the population changes that are current got out of COVID it works perfectly. It works amazingly well through COVID in commercial.
You do have to know NACE code because you can't be comparing beauty salons and grocery stores. But if you do with that one key thing, which, um, we always know, cause you can buy that in pro if you need to. Um, now we can do M and B. That's a nice
James Dice: [00:35:13] code. It's like what type of building it is this basically what type of space.
Matt Golden: [00:35:16] Exactly. Um, and then we, you suddenly called also funded by DOE something called energy differential, privacy, which is a privacy technique that Google uses on location data. It's actually being used in the us census Bureau, but it's never been used in energy, which is a method to inject random noise into datasets that allows us to use population data.
And obscured in such a way that it's not a privacy violation.
James Dice: [00:35:37] Got it. So if I'm a nail salon and I was supposed to shut down and I didn't, um, you can't, you know, out me basically,
Matt Golden: [00:35:46] right? So we're using samples. So like these are real customers, but there's no way to know who they are. And beyond that, there's no way to know what is true and what is actually just noise.
We're injecting. Okay. Um, very cool. It's how to break that stuff free. This is the excuse they add for not letting us use it right. Privacy. You can solve. So anyways, that is a freaking complicated way to say that we, well, one is question M and V right now people are not talking about this because it's an existential problem and no one wants to talk about it.
James Dice: [00:36:14] I've put it in the newsletter a few times. We'll put it. I I've been asking this question since about April, because when I was at Enrail, a couple of our projects got really derailed by the fact that we couldn't, we couldn't measure before and after effects of the software, we were testing and piloting.
So yeah,
Matt Golden: [00:36:29] I'll, I'll, there are P for P programs running in this traditional market. Like they like site based and like it's fricking nuts. So talking about that original point of like people measuring themselves right through, COVID like, We have companies who are retrofitting buildings, measuring your own shit, trying to make all these adjustments, and then someone's going to pay them directly for that,
James Dice: [00:36:45] especially when it's in their benefit that
Matt Golden: [00:36:48] people close my mind.
I I find it just so strange that nobody else that so many people don't seem to find that this is a problem. Oh, I,
James Dice: [00:36:57] yeah, I I'm a hundred percent with you. And a lot of people have responded. Like, I, I don't, I don't know what we're going to do. So what do you think we are going to do from like a single building?
And if I have a customer and they're an office building and we did say a performance contract two years ago, what am I doing right now? Like, what are we doing to say what the savings were?
Matt Golden: [00:37:18] So in that case, I think you have to stipulate to some degree. You're kind of just have to, I mean, again, or you. Again, I'm highly skeptical. If you take egos, NRI recipe, book of things, you can do that. Like, you, so you can come up with something, but really it's just a contract, not math. So, when you really need to do is go to the customer and agree to a contract team that says like, shit COVID, maybe we'll use last year's in stipulate, or here are the 16 adjustments we're going to make, but there's no, I mean, there's no way to verify it.
Yeah, no, it's just, and so, and it's log diminishing returns and it's another onion in a rabbit hole. It gets worse and worse and worse as you dig into it. Um, but at a different level the way, and this is, this is what we should be doing anyways. Is customers one of the reasons they don't tend to buy ESCO agreements except for like mush, municipal utilities, schools, and hospitals and fed federal, um, it's freaking complicated.
No one actually believes it. So, you know, w I see a big trend and I think we need to be looking at this as like cold beer and warm showers and looking at how risk is managed and like every other industry. And so again, there, and there are these energy services models, like the Mesa model managed energy service agreement, where instead of like trying to be perfect on each building and treating on each and every asset, you get a portfolio and you can buy insurance for that portfolio.
And you say, yeah, you know what? We're going to, you know, your bill was 1200 last year. It's going to be 800 this year. You're just going to pay me and I'm going to win and I'm going to win some, lose some across my portfolio. Yep. Sometimes that 1200 old bill ended up being $1,300. Sometimes it'll be $600, but in a very consistent way and give the customer something very simple and manage the risk.
Like an adult, let's take it to market. Risk is good. Risk is good. If it's manageable, individual buildings are not risk it's uncertainty. Hmm. But you package it all up into a building. Right. So if I'm getting a car loan, right. I would say I go scores of $700, have a 6% default rate. If I was doing that on one customer and they lost their job in default, I am screwed.
Right. You do that across a thousand customers. You're gonna get 6%. So. That's how risk is managed everywhere else. And contrary to popular belief, energy efficiency works the same way. And with the exception of like the most bespoke applications, the industrial buildings, the large-scale commercial buildings where you got to get a bit fancier because they're one-offs, um, it works really well in Rezi for sure.
Small business, no problem. Office buildings, retail. Groceries food services much more predictable. We wait, we wave our hands at this, that everything's a bespoke nightmare and it's not in our opinion. Um, and often we do, we generally know in advance by the way, who is a bespoke nightmare. And so the other thing is like, instead of building our whole industry around the 6% outliers that are really, really hard, let's build everything around the 94% that are down the middle and then decide what we do with the other 6%.
That's our approach on it. There are companies like we will look at buildings and like, If we can't model the baseline, they have, I don't know. I just, this is an actual example. I was just looking through it and I'm like, why is this one so wacky? And it was a, it was in the bottom floor was like one of those art studio things where you can like paint dishes.
And so it looks like, and we can't predict counts. Right. So if it's worth it. So the question then is what do you do? So this is a small enough asset stipulate. It who cares? It's like 1% of the portfolio. Or you could go in and hire an engineer to like figure it out when they run their killing or make an adjustment.
If it's big enough, just not big enough to bother, like we'll wash it out. It doesn't matter, but that's a, that's a business decision, not an SUV. Got it. Okay.
James Dice: [00:40:45] So I think a lot of what you described so far is sort of pinned on our. Sort of newfound hourly data. Right. Um, and this hasn't gone a whole all the way across the world yet.
Like not every building has hourly data yet, but a lot of this sort of depends
Matt Golden: [00:41:01] on that. So Caltrate has two sets of math, three sets of methods. Okay. Uh, monthly, daily and hourly.
James Dice: [00:41:08] Okay. So you can do it. If you just have your tilt,
Matt Golden: [00:41:11] we rarely ever touched daily because if you have daily, you generally have hourly.
Yeah, exactly. I went that way. We started with monthly because we didn't have hourly in them anyway. Okay. So, uh, we run monthly models are standardized, totally consistent. I mean, essentially prison months, you know, if you know the prison model like, and for just base-load heating, it's not rocket science, but doing it consistently did take three years because even though like the basic heating, cooling baseload model is not rocket science and construct with monthly data.
Squeezing out all the details and all the data cleaning rules and everything is hard and it sits on top. That's the same set of rules that both sit on, so you can get a consistent answer, but you can't fix the grid with that. And there's always more uncertainty because you're fitting to 12 data points, right.
It's tough. And there's also an inherent biases. Uh, it tends to underestimate certain shoulder months and overestimate other periods. And like those are inherent biases. Every time you do a monthly model that is baked in. Yep.
James Dice: [00:42:05] Yep. And then on the, on the other side of things doing the traditional way with hourly data is also really difficult.
It's just like too much. It doesn't work.
Matt Golden: [00:42:12] Yeah. It's just too much what everyone's doing, everyone that says that he was doing interval with traditional data. What they're actually doing is adding it up to month traditional models. Yeah, exactly. So yeah, the time of week temperature model is really a Dr.
Model. We're using it to unify EMDR. Like we don't care. We can actually tell the difference between long-term changes in short-term responses within the same signal. Um, we think of what we're doing as a unified field theory. We don't care what it is. We care, what did it do? And what's it worth? What's it worth as a function of what you're responding to?
Is it a market signal from the CAISO cause we're having a blackout or is it fighting the duck curve every single day, blackouts worth a lot more, but there's not much of that. Riding the duck curve every day is worth less but worth a lot. But a lot of it
James Dice: [00:42:56] let's talk about that. So. Well, let's kind of start high level for people like, like we talked about before we hit record, if I'm a building owner or I serve building owners, why should I care about demand?
Flexibility? Why should I care about everything you just said about the duck curve and the time of day and things like that? Can you, can you just like maybe
Matt Golden: [00:43:17] trying to fight climate change and carbonize put that aside? Cause nobody does this shit because of polar bears. In my experience, you had to write a big check.
Yeah. So I've had crazy environmentalist scoff at the big check when it comes down to it, right? So money you're leaving money on the table. That's why you care. So at a fundamental level, your customers investing in all this stuff in their building, that could be potentially doing harm or good actually to the grid and GHD is.
And you know, the thing we're fighting is that the, and the, really the reason to do this at a macro level is that as we decarbonize the grid, as we bring on renewables, Um, you might've noticed the sun rising and setting every day. Right? And so you ended up with like the supply of generation, not being coincidental with our peak, which is the most, it varies a lot, but in California, it's that seven to 9:00 PM window.
It's pretty common that you get like a late afternoon, coincidentally peak resi and commercial the same time. So the big idea, and what makes us valuable is that shifting load around is the new game in town. Right? We have to figure out how to use the clean energy we're generating at the times when it's most, when otherwise we'd be buying really expensive, dirty stuff.
So, you know, all the, obviously we think about storage and EVs and all that we have to actually, we think what's behind the meter. It's the same thing. Um, But there's also really simple other valuable stuff, right? Like if you've got a air conditioner and no attic insulation, there's no such thing as a flat reduction that will produce really valuable load shape impacts during the peak window.
Very reliable. It's not, it's not dispatchable, but it's valuable right there really isn't such a thing as a flat nothing, right. Refrigerators can be turned off, open connect does this, right? Like you can return, you can turn off frigerator for two hours. No problem. Right. It's not flat. So like, you know, a new refrigerator will be kind of a flat reduction, but you can also control the damn thing.
Okay. Okay. So, so the opportunity is to help solve that problem, which is a very expensive problem, which may, and there's not enough of any of the storage and EVs and all this crap. That's mostly aspirational anyways, not even close to enough of it. And the demand is going up up up, which means value goes up with it because there's not a supply.
Okay. No. Why. Because if you're not doing it, you're leaving money on the table, potentially really big money. Why should your customer use their creditor asset value to buy a set of benefits that goes to a utility for-profit utility in most cases? So the opportunity is to value that correctly so that you can reduce the cost to the customer, make more money scale your business.
And then the policy objective is that we want to give you a reason to do that. one of our aggregators does. refrigeration controls and they do utility programs, right. Left and center, but they're all based on averages. And so showing them the avoided cost in California, which is what drives our, when savings are valuable, you know, even though they're in all of these utility programs, no one ever asked them to reduce peak.
It didn't matter. Everyone was paid on averages. Right. So they're like, well, wait a minute. You're telling me if we just move our compressors as much out of those three hours in the summer, that's worth a lot or the whole lot. And so. You know what I, sometimes I don't mean this in a net negative, it comes up, this is like the moral compass to our industry, right?
Like we're totally fixated on customer benefits and in savings and in order to pivot. So we are also considering grid benefits in GHGs. We need to make them valuable and that's just how we do it. And like what we end up with and why this is great policy, is that now the market, you know, everybody that's touching buildings.
And, you know, there's all the cool people doing work out there today, but I also want to engage, you know, United technologies and all the big folks that control huge loads that like will never screw around with the utility program. I mean, like you're in the virtual power pamphlets and it's now, and you're going to make more money and get more customers, if you can figure out how to also deliver on grid benefits and GHG reductions.
Right.
James Dice: [00:46:48] Got it. And so what about the, buildings out there that don't have the incentives to. Take advantage of those so that they have, they have rates that are either flat or the rates are
Matt Golden: [00:46:59] today. Yeah. Rates are always a laggard. They never expressed the two grid value. You've all sorts of like edge case equity issues that are real.
And if a customer is getting savings on their bills, they end up with a savings cash flow, which largely they have to pay with their credit card. Um, So I think there's moral hazard and focusing entirely on bills now, you know, reasonable time of use rates is a good thing, but, and also just the complexity, like even large buildings, don't have people like you push this on the bills, you're making everybody an energy trader.
That's what you're doing. And people like the retailers, right. Like, you know, and it was like, Oh, they're on the market. They're like, they hedged their heads up to their eyeballs. And customers can't hedge. Right? So,
James Dice: [00:47:39] so if I'm doing a project,
Matt Golden: [00:47:42] so this is a wholesale signal, right? This is a signal between utility and the aggregator.
Okay. Well, you can manage that risk and, and not retail rates.
James Dice: [00:47:53] I see. Okay. So, so right now today, if I go do a demand, flexibility project, the utility for the most part is seeing the benefit of that. Unless there's some way for me to capture that value. Right? And so what you're saying is, as an aggregator, I can capture that value.
And then I could figure out how to provide that in the right way to my customers, which are the building owner.
Matt Golden: [00:48:15] Right. And it aligns the incentives to the whole system. Now you've got a reason to invest in this stuff. It allows you to finance it properly, like an integrated asset, manage the risk. Um, and to be honest, for all the MNV reasons we just described, we're never sure what the hell is happening on vintage real assets.
Right. Right, right. Right. And so the signal ends up being really messy to the customer anyways, like you saved energy and like, no, my kid went to college. You didn't save energy. I had a baby. Right. Like. This does not shift the customer should be dealing with. Right. Right.
James Dice: [00:48:43] It's also too complicated. They don't
Matt Golden: [00:48:44] care drastically too complicated.
James Dice: [00:48:46] So, okay. So you guys are basically saying here's
Matt Golden: [00:48:49] the thing. Yeah. Oh yeah. You're right. By the way, in complicated, it's worth like cappuccinos to the individual. Right. So you gotta roll it up to make it
James Dice: [00:48:55] useful, something like that, some terms that they actually care about. So, so you guys are coming through with software and saying, we're going to align the incentives in this system.
I think I'm starting to picture it now that for this whole conversation, I'm starting to get it, uh, get it fully, which is the point of this podcast. Can you talk about a couple of different terms? So what is a virtual power plant? And you've talked about it a bunch. I know what you're talking about,
Matt Golden: [00:49:20] and then it's a big, big idea.
So if you install installation, you're building a virtual power plant. If you put the controls on a building, you're proposing a virtual power plant. If you replace HVAC systems or installed storage or solar behind meters, you're building virtual power plant. If you send somebody an email they change their behavior for some event, you're building a virtual power plant.
If you're doing EMDR, it's all virtual power plant, we don't care. So it's really just a way to talk an integrated way to talk about all this stuff. So we stopped putting it in silos. first? It was a portfolio of buildings in a place affecting the grid in some way.
Right. And, uh, how you get there as beside the point it's that you've aggregated this, this resource it's reliable. We can measure its impact. It's a virtual power
James Dice: [00:50:03] plant. I can plug a bunch of interval meters in, you can do your calculations in your software and there's some sort of power being.
Matt Golden: [00:50:10] Well, what we're doing is we're measuring the change, right?
Like, so change virtual power plant. Like This, this aggregation of 500 buildings that have my controls and whatever our responding either to a long-term system. Like Hey, we want you to reduce, so we don't have to build that's distribution system, or there's no grid event.
That's responding like a power plant, but it's virtual. Yeah. And it's flexibility. So it doesn't have, you know, it's not exporting necessarily. It could. Um, but you're responding to the signal and it's equivalent to, right, like instead of building a power plant where deploying virtual power plants that do the same thing, because.
Producing electrons and using less of them has the same impact just happens to be producing less than, than tends to be cheaper, has no GHG impact. And also as a co-benefit, which is that it actually helps customers because you get better buildings too. Not just gridscale investments.
James Dice: [00:51:00] Totally. Well, okay.
So that's, I think that's a good intro to VPPs for everyone that does, hasn't heard. What about grid? Interactive buildings? So what about that concept?
Matt Golden: [00:51:10] You know, if you ask our buddies, we love cause they've funded a lot of our work. We have a different opinion. Like, you know, there's one aspect that there's one school of thought that says, this is kind of a, we have a very specific opinion about this, that, um, we need every building and every device in the building to be automatically controlled and some utility or somebody in the middle is gonna.
Control it all remotely. Okay. we think that's all true. Like, you know, but we just are not as diabolical about it in that, like we think control is going to come from the aggregator, like, okay, the derms system, the control system, isn't going to be some centralized. We're not going to replace like utilities.
We think are distributing, not, you know, distributed resources. They're not then going to be centralized to control, but you know, I'm not going to let the utility control on my smart toaster oven. Right, right. Yeah. I want that control or my contract with somebody to control it, but it's not going to be a one size fits all.
Um, and so we think we are absolutely doing great interactive buildings. We think we send a price signal to an aggregator that enables those buildings to react to the grid in whatever way makes the most sense for customers that they'll actually buy. And we think there's going to be lots of different ways.
That's going to look. That's the alternative view to like, everyone's going to use this DOE standard and, you know, PGD is going to control all my stuff. Right, right. Totally unreasonable. I mean, many of these utilities don't even know where their meters actually are. Like, I mean, I dunno, I'm going, I'm putting a lot of work on my own house and it's like bespoke nightmare for me to do it.
In my own house, right? The five contractors licenses, like I,
James Dice: [00:52:39] okay. So there's gonna be aggregators that are gonna basically design the grid interaction for their customers. And that they're going to have an agreement with our customers that there's trust involved in what's happening.
Matt Golden: [00:52:52] And I'm going to pick them.
They're not gonna afford it. Like, you know, I use OhmConnect for example. Fair warning of an advisor too, but like I connect, you know, sleep with truly, I've been connecting shit to controllers and they'll turn off for me during great events. But then I was like, I don't want you to, you know, I don't know.
But then I decided I don't want you to turn that thing off. So I have control over it. Like, I don't know. It's mine. Yeah. Yeah. So I believe, we believe fundamentally that the meter is the customer right on one side of the meter is the grid meter is the grid asset. That's where all the telemetry comes from and then everything behind the building.
Like, I'm pretty sure I own all the shit in my house. Yeah. Okay. You know, we don't think the grid extends into the house or into the building. And we think the utility monopoly has to have an edge also. Like, are we going to let utilities control transportation heating and cooling of all buildings, lighting refrigeration?
Where does that, like, where does that monopoly? And given everything runs on energy, are they just allowed to control the economy? Yeah. And that sounds hyperbolic, but like where's
James Dice: [00:53:50] the edge. So with this gap concept, do you picture there being multiple aggregators that serve different buildings?
So each building having multiple aggregators, like, do I need an aggregator for my electric vehicle charging systems? And then my  for
Matt Golden: [00:54:04] my age, it depends what the measurement barrier is. Some things we can isolate, but in general, we think like you will. At your master meter, have an aggregator that you'll choose to work with.
They may subcontract with others because how you break the savings out between devices is kind of a contractual agreement. Um, things that have meters on them, you know, car charging or solar can be isolated. We can take that out of the equation. That's a little bit of a sloppy answer. There's going to be different iterations of it.
Okay. Got
James Dice: [00:54:32] it. Cool. All right. So as we kinda wrap this up, this has been super helpful for me. Um, I want to ask you about. Your your answer to my favorite question. Uh, so I always do one question, ask everyone the same question So my question for this year is what's the number one thing you think needs to change, to unlock smart buildings, and you can define smart buildings, however you want.
Uh, you have a different perspective than most people on the podcast, but what's the number one thing you think needs to change to just sort of blow things up.
Matt Golden: [00:55:01] Boy, there are so many fun barriers to talk about here between, uh, access to large scale capital and competitive markets. And, um, I guess the, the fundamental thing that I believe we need to put in place is market access and competitive market access, right?
that, um, I believe businesses, whether it's the customer and the building or the aggregator, figuring out how to invest millions of dollars to build a business model and deploy it, um, respond to something called money and other things too. But we have to align incentives around what makes money, what is valuable.
And so, you know, it's pretty consistent what we've been talking about here, but I think. Having a price signal that makes doing good for the grid and the climate, outside of the four walls of the building is the critical thing that aligns interests. So that again, producing stuff that actually works becomes a source of profit to the market and a better deal to the customer.
And then everything flows from there. Right.
James Dice: [00:56:01] Yeah. So basically a cashflow stream that everyone agrees upon the calculations like we've been talking about that then creates the marketplace around.
Matt Golden: [00:56:09] And under that there's a, in a competitive market, we're not going to pick the winners and make more monopolies.
And then everyone's competing on the right grounds to go out and figure out how to build business models and deliver valuable solutions that actually work. And if they do that, they're gonna make more money and grow. Customers are gonna be happy. We're going to scale. Love
James Dice: [00:56:27] it. Love it. Cool. So last question.
What are you excited about for 2021?
Matt Golden: [00:56:32] Well, I'm no longer running around trying to convince utilities to give us a hundred grand so we can prove they have a problem. Um, we have a new administration coming in, which isn't gonna hurt either by the way. But, um, this is the year of the virtual power plant. We are decarbonizing rapidly in many places now.
Um, even prior to our new administration that just a hour or so ago happened. so I think we're in a quickening. and when I say like, we don't have to convince utilities to have a problem anymore. I think there's, you know, things move very slow into it. No, they don't. And I think we're approaching a inflection point where, you know, this is, we're not just going to write reports about barriers and, you know, run $6 million, pilot programs, but.
Things are going to start going faster and get bigger quickly, hopefully.
James Dice: [00:57:16] All right. That's a great place to kind of sign off. Thanks, Matt. I want to get an update from you at some point on this inflection point. Uh, but thanks for coming on the show. Thanks for educating us.
Matt Golden: [00:57:26] That was good. Thank you.
James Dice: [00:57:31] 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@nexuslabs.online. You can find the show notes for this conversation there as well. Have a great day.
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