Scott Hinson of Pecan Street Inc.

Welcome to the macro fab engineering podcast. I'm your guest, Scott Henson.

And we are your hosts Parker, Dolman.

And Steven Craig.

This is episode 292.

Scott is the Chief Technology Officer at Pecan Street, where he leads the Pecan Street lab and directs research efforts to study the grid, and climate impacts for integrating renewable technologies, electric vehicles and software embedded smart devices that will modernize and decarbonize the electric and transportation sectors.

So Scott, before we jump into what is Pecan Street, who are you?

Well, I am the CTO of Pecan Street. I got a degree in electrical engineering. A while ago. I double specialized in power, and signals and systems. I ended up having to go to the engineering department chair, and because I was signing up for too many engineering classes, and they were like, well, what are you doing for your free electives? I was like, no, no, I want to give the engineering department more of my money. And that's what convinced them.

That's pretty. That's pretty convinced engineer. I'd be like, I want more engineers. I

want more engineering classes. I like you didn't fit in their flow chart. Yeah. I'm taking extra math and engineering. Is that okay with you guys? Sure.

What's wrong with you, sir? Yeah, whatever

you want. And then after that, and this was all sort of, I don't know how else to say this. It was sort of an unplanned, like, I knew I wasn't going to be the fine arts because like, the idea of having to take foreign language in college was horrifying, terrifying and debilitating. I didn't want to do that. So that, that that left relatively few choices. I didn't actually even necessarily know I wanted it to be electrical engineering, that just sort of happened. The original plan was to be a pilot, and I'm not wearing them now. But if I had my glasses on, you would know that that was never going to be the case. Or at least it shouldn't be. So so yeah. So I sort of toyed with aerospace. I didn't like the longer term career aspects of that. Chemical Engineering seemed weird. And so I was like, mechanical, electrical, mechanical, electrical, mechanical, electrical. And I basically chose electrical. So that's, that's who I am sort of stumbled

on usual way to go about it. Because usually, when at least previous electrical engineers we have in the podcast, they are interested in electronics, and that's what drove them. I was you were you interested at all in electronics beforehand? It

was like, but the thing was, is that I didn't understand. Like, when I started engineering school, I didn't understand what, what even like how to go about the fundamentals, like I was good in the physics classes in high school is good in the math classes, right? But I was like, Why isn't their amplifier design one to three or one? Why isn't their computer design? Through I like, I didn't understand how the various classes fit into giving you the fundamentals until it was basically too late. And I was trapped.

Which is too far along. It was like,

Oh, God, how long am I gonna be in school? If I change now? And so, so So yeah, so I mean, like, like, I would tell people, I want him to be an electrical engineer. But, but until I actually became one, I don't know if I understood what that meant. Like hindsight. Older Scott needs to go back to to 18 year old Scott and say, Okay, this is what it is. And an 18 year old Scott, I think would still do it, because I've had a grand old time playing with a whole bunch of really cool stuff. Right? Like, like, I possibly have things in satellites, either that or they're at the bottom of the Indian Ocean. I don't know. Because you know, the rocket sometimes go, whoosh. I've got stuff. I've had stuff sort of buried 6000 feet below the surface of the earth and trying to survive, so I've gotten to do some really cool engineering challenges and designs since them. And so I don't know, you know, now I'm like, Yeah, this was this was a great choice, but sometimes it's better to be lucky than good. You know?

I like that. Yeah, that's good. And I honestly, I don't care who you are when you're 18. You have no clue what notes You're in for

having a 16 year old now. Yeah, yeah, I was like, oh, sort of seeing that math through through my, my eyes now it's like, Oh, okay. I'm gonna try and help you here. And I love you dearly. And then you're gonna look at me and turn around and walk off and think that guy has no idea what he's talking about. And that's, that's me, because I did that to exactly.

When I was 1618 years old. I didn't care who was giving me advice. Yes, I was never going to take it. Yeah.

So yeah, that was that was that was the deal.

So Scott, when I was in school, I actually did pull the plug on my, when I was going for it and switch majors, like, deep into it. So

my wife did too. So she she has enough if I remember correctly, to have like, a minor in a couple of different things at this point. She said that she was on the six year plan with good grades it was

that's what that's what ended up happening to me. I don't regret it, though. So

I changed my major one month in from aerospace to electrical because I was like, Aerospace is dumb. And electrical is way more fun. Yeah.

Yeah. Aerospace Engineering.

I know, right? The Aerospace Engineering hate, hate mail is common. Now, Aerospace is super cool. Well, they do some some amazing stuff. But too, it just tends to take 10 years to see the results of your work.

Yeah, it's also a lot easier as an electrical engineer to do work in your basement than it is as an aerospace. Unless you're like, I'm an RC plane guy, you

know? Yeah. Yeah. Or you're Elon Musk. Or have Elon Musk lovers of money. I should say, you don't have to be him.

I think this should work. You go make that work.

I want to make a rocket. You You 1000 engineers

go make this

Yeah. Okay, um, so Scott, what is actually actually started off because it's is it? Pecan or Pecan Street?

So all the employees, say Pecan Street, because we're from around here. I'm based in Austin, Texas. And that's, that's what we say here. We always know if you're from, you know, Georgia or somewhere else, because then the other pronunciations start to come out. But no, we all say Pecan Street. Okay.

I'm glad that you're on our podcast now.

You're allowed to.

Wow, that was the shortest podcast ever. He said he can. And we were done. 15 minutes.

So what is Pecan Street.

Um, so it is a 501 C three nonprofit research organization. And we have a lot of things that we do, but we're probably in the energy world, we are definitely most famous for the data and that we collect and the data set that we have curated and in our in our sitting on and in license out to commercial entities to academic partners around the world. That data is how people use and produce energy, mostly at a residential level. We don't collect what most people think of as, as the normal energy data like, like a utility, smart meter system, right? Might our most often gets 15 minute reads on a residential structure. So you know, you can multiply that out. And you know how many data points they get. And that is big data, right, especially for some of these larger utilities that might have a couple million residential meters. But that's not how we get to our number of big data. We don't have a million homes that we have instrumentation and we go in and put equipment inside the circuit panel on every single circuit in the house. And instead of collecting data every 15 minutes, we collect five data points every second. So we collect real power, apparent power, current RMS phase angle between voltage and current and current THD on every single circuit in the house every second, which means we have single family houses that generate 10 and a half million data points a day. And we collect about 4 billion with a B data points a day. So that's a lot. We have we have a number of folks were I've had to sort of remember I mentioned that signals and systems background that I have, it comes in very handy when they're talking about well, we have this one house that has, you know, this, this 18 second gap. And I'm like, Well, you've got 300 houses that don't, okay? Like this is how you deal with this on the data side, right? We have those systems collect and store locally anywhere from three to seven days worth of data on them. And so if there's an internet outage or we lose contact with them, as long as we get that connectivity reestablished, we can actually backfill that data. So we have quite a few homes that have very high data completeness rates 99.9%. So that's what Pecan Street is. Now we do, we do that to a lesser extent, because it's, it's a lot harder to do with natural gas and water. But we do have high resolution devices, for natural gas and water as well. Natural gas and water, you're less likely to need to sort of have that ground truth, detailed measurement on individual devices, because there's fewer simultaneous uses of those of those energy streams, right? If you see an 18 Second water event, odds are it's handwashing. If you see 1.3 1.5 1.7 gallons, odds are that was a toilet flush, right. So it's a lot easier to sort of, if you have high resolution water data, it's sort of a lot easier to pick out individual events and know what they are, if it's 1700 gallons, it was irrigation, right like these are, it's pretty easy to spot these things versus electricity. Even if you have very high resolution data for the home. Unless it's a big device that sort of pops out of the the noise. It can be really hard, it can be really, really challenging to go figure out what that that thing was that just turned on.

Yeah, that was that was actually one of the first questions that came to mind when you're talking about that 15 minute interval versus five times a second.

For every single circuit that can be 24 circuits in a house.

Right, right. So what kind of data what kind of, I guess, ghost data is lurking in between those two? Like what like, what is the benefit of having that much resolution?

That's a really good question. That's and it's a it's a, it's a better way of asking it than the most people do. Most people just say, Why do you need that much data. So we used to collect one minute data. And we we, that was very useful. In fact, if all you want to know is sort of really detailed information on where energy is going into a house. During the day and day out operation of that structure, one minute data is good. But if you want to start really understanding the interaction between solar and batteries, or if your super fancy algorithmic control systems for thermostatic loads are responding in time, a minute may not be enough, for instance, in Texas, right? And you guys are sitting in Texas, right? So we're all we're all on ERCOT I feel bad for them. I also, you know, I am. I'm in Colorado, okay. So so in ERCOT. And I have friends that work there, I feel bad for them. Because, you know, we went through what we went through this winter, and and yeah, that was bad. And ERCOT has a five minute nodal market. So they're making wholesale purchase sell decisions on electricity on a five minute settlement basis. And if you're studying something for one minute, you've lost 20% of your time, potentially, for that, for that marketplace. So as the marketplace gets faster and faster and as the interaction between devices, right, sola can go from full production to no production in 10 seconds. Or, and vice versa, right. Now, you need to start collecting faster and faster data to understand the interaction between those devices, because one of my long term concerns is grid stability with intermittent resources. And so to truly understand the the updown of all these things, yet, you can't have an aliasing problem and and just lose all that information by taking 15 minute averages. It's fine for billing. It's not fine for operations.

Yeah, I'm imagining like a future where like a one's house has solar panels on Top Right, and then just a big cloud just just one cloud, though, it's cruising across the city blanketing a couple a couple of the roofs at time, local outages.

We, I mean, like, as part of our privacy agreement with our volunteer participants who allow us to monitor their homes, we don't give out locational information, but we have it. Right. And, and very early on, we sort of did, we did some geospatial views. And we, you just watched the cloud cover, roll through a neighborhood, you're like, oh, there was one, there it goes another one. They're, like, oh, that's where they were. Okay.

Shadow tracker,

pretty much I mean, and then, and then, of course, if you look at the like, the daily production, you know, kilowatt hours per kilowatt peak installed, for equal Azmuth, and tilt, right? If they're all, they all work out to be roughly the same, the longer you average, right, over a couple of days there, they tend to be very close. But on any given minute, on any given hour, your production values can be very different, and the decisions on what you do, especially if you've got energy storage involved to try and balance this can be very different. Because you, you don't want to position that battery poorly and have it full, when you desperately need to put more energy into it. Or the more common problem of having an empty when you desperately need to get more energy out of it. Right? Either of them are bad one is probably a hair bit worse.

So what do you do with all this data?

Yeah, actually, that's, that's the you're collecting or Prakash streets there is you're on each circuit in a house, right? What does that enable the users to do with that data, I guess, is a good way to put it.

So we have a few dedicated participants. And in case any of them ever see this, thank you for volunteering, like, seriously, we couldn't do this without our volunteer participants. And we have a few dedicated participants that actively watch their data, we have a larger subset of participants that know that they have access to it, and you know, it's too much information. And, and, and, or they just don't understand it, they know it's important, and that we have, you know, like 2000, or maybe 2500. At this point, academic researchers worldwide that have accessed it to try and hundreds of peer reviewed papers have come out of this data, right. So that the users there are some dedicated users, and we'll get calls of like, I think my solar system is not working as well, can you help or I got rid of my first all electric plug in vehicle and I got this new one, just so you know, I've got a different one, now you're going to see the charging patterns change, it's going to be more or less Bower or whatever, right. So so we do have people that use it and track it, and some of those folks, we've noticed that they can get very low levels of sort of background, total energy and power usage, right. So you know, they're they're the ones sort of going around making sure that anything that that has a significant vampire power footprint and they're diligently turning all that stuff off.

My dad would love this

like the the like super advanced version of Don't touch my thermostat. Yeah,

pretty much. And then there's then there's houses like mine that have children whose fingers little known fact can turn switches on, but not off. And so you can see when when I end my workday and go around and shut a bunch of stuff off in the house, because the whole stereo setup function.

Yeah.

So yeah, so So that's, I mean, that's like the the user or the volunteer participant, that's what they're looking at, from an academic perspective, or a commercial research perspective, these homes now form testbeds, where they can go in install stuff, do demand response, do battery, integrations, all sorts of stuff, and see what the difference is to the grid for those homes. If you had just one home What if you what if you expanded that to 100 like 1000 10,000 What does this do to the electrical system in terms of of peak requirements or omissions or something like that? So there's a bunch of different like we have over the years we've had a bunch of different programs so I'm I can talk about because They're sort of public knowledge. Others are covered under NDA. And I unfortunately can't. Because, you know, and, and, unfortunately, some of those were the coolest, of course, because they're covered under NDA, right. But But there's been a ton of, of of trials of various demand response and battery, like we did one with Lawson energy, where we compared residential energy storage to commercial scale energy storage to utility scale energy storage. And if it works, right, the price, even at the prices of of like a year and a half ago for for energy storage systems. If, if the, if the ERCOT pricing gets flowed down to the owner of that battery, the batteries can pay for themselves very quickly, very quickly, a couple years. Right. And so that there is an economic reason to do this. There's also an emissions reason to do it.

Basically, storing power when you can, on wind and solar,

right. Alright, so for these homes, you know, you could if you just wanted to do it sort of your most basic simplest way, you charge the batteries over a four to six hour period at night when when energy is most plentiful on the the Texas grid and the prices are the lowest. And then you discharge them in a two hour window in the afternoons in the summer. Right. And, and that alone, right? You don't need like fancy, you don't need fancy AI or ml to predict that it's going to be hot, and there's gonna be a lot of air conditioning usage between four and 6pm.

I was gonna say I was gonna say five to seven. But yeah, for six, probably. Yeah. Normal people.

Yeah. So So what they're worried about in Texas is that, that what's known as the four coincident peaks, so the 15 worst minutes in June, July, August, and September. And if you look at it, like, for the last 10 years, 98% of them have happened between I think 345 and 545. Or maybe it's 415 to five, or 615. I forget, forget the exact timeframe. But like there's a there's a two hour window where if you've got a two hour resource, you don't need to do AI machine learning. Now if you have a 30 minute resource, right? Now, it's a lot harder. Now you have to pick the right 30 minutes to deploy that resource. But if you've got a two hour resource, just run it.

I worked at the power company back in college, one of the ones up in the Dallas Fort Worth area. And it was impressive to see the Oh yeah, it was it was it was it was impressive to see the load chart during the day. You know, like Yeah, updating, you know, around noon, it's you know, it's at some level, and it is a step function. When people just from work, it just skyrockets because every AC comes on. Every TV comes on every computer turns on. Yeah. All within an hour.

Yep. We actually saw so for like, one of the things that, you know, the other like, some of the cooler stuff that I can talk about, that the date has been used for is there was a I think it was an economist at UT that did this. Maybe it was sociology department, which kind of blew my mind because it's not engineering, right? looked at it and realize that they could predict if it was going to be bad traffic the next day, by if people were enmasse staying up later. And the way they looked at that was device usage in the homes. And so if they stayed up later than they realized everybody's going to sleep in and wait till the last possible minute to leave to go to work and traffic was worse than the next morning. So there was a very strong cost access

to that data.

There was there was a very strong cause and effect we actually looked at it at the start of COVID. Right so last March or two marches ago, I guess now it's too long. And unlike electric vehicle charging, plummeted, like 90% overnight, the day after the city of Austin Mayor canceled South by Southwest. That was the moment our participants were like, Whoa, we have to stay home and then we are

gone. Right

yeah. I'm not even gonna go I'm not even gonna go to the grocery store. I can't even get to them.

I've given up Yeah.

And, and like, you know, since we we go circuit by circuit, we can pull out car charging. From the mix. We could pull out air conditioning usage from mix. We can pull out what few homes have electric water heating and stuff like that. Basically, we got to what we call the everything else category. And that tells you sort of what people are doing. And you used to see this sort of ramp at 530 in the morning where people would start to get up, and it would sort of plateau at about 630. And then it would ramp up began about three o'clock when people got home, when kids got home from school, and then it would ramp up again, slowly till about 839 o'clock at night. And that profile when you know, because people wouldn't all pre COVID You know, it wasn't hanging out at home, in the evening, it was go to the movies, go to the grocery store, go to the shopping center, etc, etc, all of these things. Well, none of that was happening. And then we saw people staying up later. So we watched the whole pattern shift. Overnight, we saw refrigerator usage go up like 20%, because we were all being little piggies and sort of hanging out at the at the refrigerator and hitting it a little more often my kids took inventory regularly, right? Like, like, we haven't gotten to the store. Nothing has changed in the last hour. You didn't take anything out nothing else has gone in, it's still the same.

They're just curious that light stays on when the doors closed?

Well, I can tell you that it shuts off, I can tell you for sure. 20 million and foundational private grants, DOD grants and and commercial research grants. And I can tell you that light does go off. That's the answer.

You know, okay. So you just you just mentioned that you were able to identify, you know, this is this is this event is AC turning on this event is electric car charging things like that, when you install these trackers on each circuit? Are you identifying the circuits at that time? Or are you building that data out from the data?

A little bit of mostly, mostly we understand we are our master electrician, we actually have one on staff where we're a nonprofit, licensed electrical service contractor in the state of Texas. Which is an odd place

to be, they tag the circuits for them,

but they'll go through the then Richard knows to go through and check all the circuits and tag them. And so our participants also know that their circuits are more right. Because their neuro, right.

From the I don't know why that's so correct. Like every single house I've been to, or help friends do electrical work and stuff. Those Those fuse box or circuit breaker boxes

are never correct. Yeah, it's it's I think it's a big gag at this point, like, I don't know, either. But But yeah, so we'll go through and we'll check. And then after looking at these things, and here's the crazy part for all of this, after looking at these things for all these years, right, we have quite a few advanced sort of analytics that run on this stuff in the background, make sure that data is valid and good and things like that. But we every single house we add, we still put a set of eyes on it. And at the end of the day we go Yep, that looks like a dishwasher. Yep, that looks like a refrigerator. Yep, that looks like an air conditioner. Yep, that looks like a whatever it is. And we still end up having to put a set of eyes on it. Because like there's every once in a while something slips through. And you're like, What the heck is happening in this house? That can't be Yeah,

that's Parker welding for 12 hours straight?

Well, you can't you can't see it, because I've got the thing facing this way. But I have power tools to make all these speakers right. So there's a three horsepower Delta UNISAW sitting over there. There's a CNC machine sitting over that way. I know for a fact the folks that have looked at my house for disaggregation purposes are like what the heck is this? This isn't a normal. This, this needs to go into the outlier bucket. On the weekends. Yeah.

Yeah. Okay. So so I'm curious. All right, does it if you were to boil it all down? Are humans more predictable than we think?

Oh, yeah. More than we'd like to think we are.

Yeah. Oh, yeah. We have a we have a if if anybody listens goes to pecan street.org. And goes to our news blog series. If you go back about 18 months, and go to our COVID patterns, blog thing and I'll have to shoot you guys a link later to this thing. It shows you that everything else category and year on year in year out pre COVID does not change and we compared it like there's there's a weekday pattern and there's a weekend pattern. And they they are they are really really steady.

So can we talk about the hardware that y'all install? All? Oh, sure. So the hardware hardware device challenges for this because monitoring and an AR management. So monitoring energy also requires energy uses energy. So how do you all you have this installed on each circuit in the house? And someone's circuit breaker? So I'm imagine like, there's not a lot of room in a circuit breaker. So how do you make all that equipment fit?

So it has changed over the years. And this actually is, is when we open new test beds, because we're, you know, like, like, I've said, for years, when we first got started, we had a known geographical bias, we had most of our most of our volunteer participants were in Texas. Okay. Well, weather in Texas is different than other places, right? And, and so eventually, we got testbed started in upstate New York, and Northern California. And so we started to remove some of that geographic bias, the Texas bias, the we also have socio economic bias, right? Because especially at the beginning, we purposely went for homes, that, that were getting solar rebates, getting electric vehicle rebates, and things like that. So what I what, you know, I will often say at presentations is we understand how doctors, lawyers, and engineers use data or use energy. To take this back to the installation and the equipment. When we recruit these test beds, one of the biggest challenges we have is, are we going to be compatible with what's already there? And are we going to have networking sufficient enough to get our data out? Right? So it's, it's like 100 megabytes a day? So it's not gigantic? Right? But if this is somebody depending on cellular data for their home, we don't, we don't want to impose that on them. Right? It has to be a broadband connection without data limits, right? So that that there's no, there's no imposition on the on the participant. And the way the rules and this is, this is a broad generalizations of there's a master electrician, listening, understand that I'm trying to keep the rules short. When you go in and you do work on an electrical panel, the electrician is, is responsible to leave it to me, you know, a certain level of modern code if they go in and they take that panel cover off. Alright, so there have been some times where we've had older properties where our electrician walks up to it and realizes it's like a 1940s Vintage circuit distribution panel with like four circuits in their fuses. And he's like, I can't, I don't want to want to take that cover off. I can't touch. Right, like I, if I can't take this cover off, I have to put a new panel for you. Right, so. So there's some difficulties there. And up until about two years ago, we there, the Phil rules how much space you could allow us to go inside the CTS themselves are tiny, and they're split core. So we don't have to take wires off. The measurement box itself only consumes about six watts, and it's about this big. And so it's it's relatively easy to go in there. But now we usually put a NEMA rated enclosure next to it. There's two sets of conduit one for mains one for the CTS depends on the jurisdiction, some allow you to to run simultaneously because it's it doesn't qualify as communications cables. It's It's It's monitoring, our measurement, wiring. So even though it's low voltage and high voltage in the same conduit, you can still do it. So it just depends on on the rules of of the jurisdiction that you're in. But that's that's how that all works. And it is a every few months, we're like, Oh, what is what city doing? Oh, okay, that changes for us now there for the future, we have to do something different.

So is the actual data acquisition box something of your your design or

no, it's commercially available? And we've talked about all times it's called eGauge. And if any of the eGauge folks are actually out in Colorado with you, Steve, you're in Boulder. If any of the eGauge folks are watching, hi. We've got you know, we've that's the best one that we've used. It's the one that's got the most storage and they've got one of the more advanced API's to access the thing.

Very cool. Yeah, I'm checking out the website right now.

So now our water device, that's something that we we developed. And there's some commercial ones that are used very similar technologies. But it's, it's basically something that uses and I don't have my cell phone it within reach, but it's the same sort of type of chipset, that's the compass in your cell phone. They're very, very sensitive magnetic field transducers are very low power usage, because they have to work on cell phones. And the way a water meter works is, as the water flows through it spins a an impeller Deeley with a disc magnet on it. That's north, south, north south, right. And there's a register set that goes on top of that, and it's got another magnet and they north south link up, and then they can spin each other. So if the register gets broken, you don't have to cut pipe and put a new meter. And those meters are expensive and big and bulky and brass and heavy duty and last 50 years, right. But the register set can can be much more easily removed. And even though those magnets are linked up with each other, there's enough residual flux escaping that's got a polarity flip that as it spins, we can watch every single rotation. So that's about four ounces for most residential water meters. So that was that was that was a cool one that we did. In fact, I don't even think you guys know this. So this isn't the the advert macro fab advertising hour. But macro fab built all those boards for us. So, but yeah, but yeah, that was that was a program that we did a few years back for, for the state of Texas for a water conservation research effort.

Very cool. Is it a similar setup for the gas meters? Are you reading meters

vary wildly? So there are there unencrypted chirp technologies on gas meters, there are encrypted ones that we can get access to there's a whole the gas meters are a different animal altogether. And gas meters are Totalizer and sewer water meters, typically their Totalizer. So every time the flow goes up by a certain amount, it sends out the new total that way, if you miss literally hundreds or 1000s of reads, right, you still know what you should have total mountain for right? Versus the thing that actually matters to the those companies. So yeah, to the utilities, right, um, the catch with and I feel bad for them. The catch is, is that the water utilities are typically the lowest funded utilities for any city. And so they have the smallest research budget. So they their metering technology is typically lagging the other two major utilities. And I really do feel bad for him, because it's not like those water, like, like, I've talked to a number of different municipal water departments. And they're all like, Man, I wish I had this kind of data. And then they sort of sit there and think, Well, I'd also need the data scientist to do stuff with that data. But if we had both, if we had the data and the data scientists, we could do a lot.

That string of ifs is actually probably quite a bit longer than just two if this and if

Yeah, well, I mean, big data, you know, go find go find big data people like they're, they're in super high demand, right? They're there.

Yeah, absolutely. Yeah. Yeah, imagine

if you could, if you had that, I'm just trying to think of what they could do, you would basically you could figure out when your high demand of water is and make sure your your towers are filled for those points, but then fill up our

it's more it's, it's, it's, it's even more basic needs than that, actually, this is a semi horrifying statistic. There are there are municipal water, places that don't know where 15 to 20% of their water goes. Like they know they shove it into the system. And then they can sum up all their

customers and when I was saying to Yeah, like they're like

you can I don't know where it went. I mean, like, like the water main for my house hasn't been touched in probably 60 years. And you know, it's got micro fissures and cracks and stuff like that. So one of the reasons that we got all those boil notices for for the winter storm is because if the pressure drops low enough, they'll actually have backflow into the pipes and now you can't guarantee water cleanliness. So there's there's a whole like as soon as we lost power my I was like, alright, fill up every bucket in the house, every pot every pant, like we're gonna need drinking water, like like knowing what I know. Like, okay, there's a triage of things that we need to do. Food is actually not at the top of

so Oh, yeah, that's kind of gross. If you think about it.

Oh, it's and yeah, and that's and you're like, Oh, should I really be boiling the walk? Yes, yes, you really should.

To engineer Bob in our Twitch chat says, I was a little confused. Are these meters connected to an internet connection? Or does a person have to go out and download the data for reporting? Now they're connected, they're not correct. They're connected

to an internet connection. And in fact, we use powerline carrier to so we've got the the gauges, the newest ones will have an Ethernet connector on the side of them and you can you can direct connect that way. But a lot of them the older style have powerline carrier connectivity to them. And so then we just have a powerline carrier modem that that plugs in next to the router. And off we go. And so yeah, we, we couldn't we couldn't get this kind of data. If we had to truck roll every, every time we wanted to download data, there'd be no way. I mean, when we upgraded to one second data, we bought a petabyte of hard drives. I mean, that's that's that we just can't

I guess they expand on that. So let's say the water meter? Because that's usually out in your yard. Right? Are those battery powered? Or are you running power out there?

Yep. battery powered. And that's why we ended up going with a man we the wheat. By pure calculation, we should we should have 10 year battery life on those devices, I'd say if we really in real life with temperature fluctuations over the course of the year and stuff like that. And frankly, even like, you know, the the the molded enclosures with seals and these sorts of things. The moisture vapor transmission rates into these enclosures will mean that there's some leakage current stuff like that, I if we get five or six, I'm, I'd be ecstatic.

Right, Texas has a rough environment.

And I mean, like, like, where are you? And not only that, but it's it's an RF signal. And if that pit floods, you're not getting that RF signal out, it's got a metal lid 99% of the time. So that makes it fun, right? Low E glass windows also are, you know, don't don't let that frequency range through that we can transmit in. So if it's a really efficient house, we have the issue. And then if if it God forbid, it's a stucco house, because that's that's, you know, a wire mesh that forms a really good Faraday cage to these sorts of things. So I mean, that those are the water measurements are really, really challenging, which is why, you know, I again, I feel bad for the water meter, folks, because there's a number of commercial companies that are working on this, but it is not going to be an inexpensive solution. And I doubt it will ever be as easy and as complete as the electricity data.

Yeah, it's most homeowners don't spend as much on their water bill as their electricity bill.

That's true. That's not where the money goes, right? The money is not going to natural gas, the money is not go into the water. The big dollar bill of the three is the electricity.

We're not sending signals over water also. No, no, no, it's a lot easier on the electric.

Is that Morse code? What's coming in? Why is it coming out of the sink like that? I'm

sure the baud rate of water is real.

I'm just imagining trying to send a signal through a water hammer style system. Just pulsing the water.

It's just like a diaphragm that hammers the water.

I now want to do this just do it. But anyway, to prove

it sincere, Bob's

got another question is sure How do y'all deal with security updates your boxes? If you'll do updates? I imagine that's on on the the OEM for the those boxes.

It is but this is one of the reasons like like, you know, they'll push updates to just privately owned EEG gauges, we actually we actually push the updates to ours. And we don't we don't update every time. Like we don't we don't send every update because if there's a change to the API, it's like, ah, we just we just updated and we just redid everything. Why don't want to redo it again. Yeah, security, security is one of those things where and, and you know, I am not a cybersecurity expert. But I stayed at a Holiday Inn Express last night. No, I took a couple classes in it in in college. And it's one of those things where our data boils down to the value of an individual data stream Right, then, you know, like, like, if you did get access to it, what could that tell you? And how important is that? And in reality, we're not sure it tells you all that much. Because homes, electricity patterns are so complex that you have to know what you're looking for to determine the occupancy. Right. So just just having access to oh, well, it's four kilowatts right now, that doesn't tell you occupancy,

but you can, on that, just on that same line of thought, you can just like walk in someone's backyard and look at their meter.

Or you could stand in the street and see if their lights are on, right. Like, there's way easier ways to tell, and, and

their toilet hasn't flushed in four hours, there must not be home.

Right? You know? Conversely, conversely, we actually see, you know, to sort of flip this around, right? We actually see, there are implications for health and wellness, right? Like, oh, you know, grandma's energy use pattern has changed over the last couple of days. And she says, she's fine. We might really want to go check on her. Right, those kinds of things. So there's, you know, like most things, you know, with great power comes great responsibility, what are you going to use them for, and there's some there's some true value, and wellness type things that you could do with it. Conversely, the other the other example that we've given years ago, was if you did have high resolution, water usage, and you knew about those toilet flushes and both parents are, are out of town, and they've got a high school aged kid, and all of a sudden that that side bathrooms getting flushed 50 times an hour, somebody's having a party, right? Like they're probably not doing what they're supposed to be doing right now.

The kids get smart, and they're just like, go in the backyard. My parents are monitoring the toilets right now. Like,

Well, okay, so we also have transportation research that we do. And we did a pricing trial for for electrification of that last mile link between, like where a bus stop is and where the front door is, right. And the pricing trial got completely blown up by a group of high schoolers, we had to remove like 40% of the rides to find out what the, the actual value of this was. So the app for about a six week period that we had, we did a phone app, and the app would randomly assign you a price and say, Well, we're in the truck palletizing Are you willing to pay 50 cents or $1, for this ride? We our office was within sight of the school bus stop. And we'd watch like 15 high schoolers all stand in a circle with their phones, and keep hitting refresh until somebody got the free ride. And then they all piled into the Watch

Game system. They totally game the

system. And it took them like two days. Like it, it happened so fast. And you had a table full of software developers and engineers that were watching it happen. And we because we could see that we can see the the dollar values coming in to the database, right? And we're like, Oh, my God, they just broke it. That's an and, and like, the software folks were mad. And I was like that. Awesome. That is so cool. Good times. And then, like one day I actually and the former head of software, like we went out there and we talked to him. They're like, is this what you're doing? And I'm like, oh, yeah, that's what we're doing. We thought so we just wanted to double check. And they're like, are you mad at us? And we're like, like, we're not telling you if we're mad or not, right? Because we don't want to we don't want to we don't want to bias the behavior. That's awesome. I love that story. It was so much fun to watch while I was having because it was it also sort of coincided with the Pokemon craze. So at first we were like, are they all playing Pokemon really intently? No, because this mattered this was going to save them 25 cents

you got a lot of time on your hands as a as a high school student I guess. So I'm curious, how much data do you have like what is what like going back how far

from the one minute data some of it goes back almost nine years. So we can actually watch home envelopes age.

Oh wow. You can see appliances get less efficient,

and insulation and air conditioned. units and all sorts of things. And we can watch solar panels degrade, we can we have, we have really cool data on some of that stuff.

Okay, so that sort of leads into the next next thing. The analytic side of my mind is like, I would love to see this data, is that something that someone can go look at your data or

so we have commercial licenses, which which I won't talk about pricing, but they're not, they're not cheap, right? I mean, this is not an inexpensive data collection operation. We have academic licenses that are very, very low cost. So if you're part of an unfunded research, so if you're like doing your masters or your doctoral thesis, and you're just trying to do a bit of research, based on on this theory you've had, and you're trying to write this thing up, and you're not part of some sort of DOE grant for the department, or, you know, funded bid from Duke Energy or whatever, right? Then Then those folks have datasets for like, 75 homes for a year for free at one second. And they're massive files, like, like they, and we also, we make it easy on him, like we give them the one second, which is massive set of files, and compresses down to something very reasonable. And then they uncompressed and they go oh. And then we also give them sort of one minute and 15 minute, you know, averaged snapshots, chunk snapshots for because because, you know, eventually you figure out how to work with one second data. But I can't tell you how many times I've gotten the call will excel is giving me this error. And I'm seeing the bottom right hand corner of a spreadsheet, I didn't know that existed. Like you can't, you can't use Excel for this, right? Like even MATLAB and Scilab start to start to cough. We set we actually set up a Jupiter hub environment for researchers to go manipulate the data in. And we spent a fortune on that server. And so if there's anybody that ever listens to this, that that, that doesn't realize we have that resource for our academic partners, please go log into it, please go spend our CPU cycles because we have it for you. And things like that. So yeah, that's it for the academic folks. One of these days, I need to sort of talk talk with the leadership team and sort of say, All right, I think it would be handy for everybody involved to sort of have like a, a one home one week, one minute dataset to just go look at so they knew what this looked like for curiosity say, but we have a ton of we have a ton of blog posts and things like that on our website that have examples of this data so you can go see what it looks like it's fascinating

I think I think that would be really really interesting if if on the website there was something like that where you just like even tables or charts or something

Yeah, we got a ton we got it like like we just released a an analysis that we did on if if you are going to fully electrify home our people circuit panels large enough to do it. We did one a couple of weeks ago on power factor, because we've seen that like energy efficiency of devices is getting better and better all time and they should right but the the power factor you know the distribution utility folks want a house to be sitting there at point nine five you know, one's perfect point nine five would be great. And we see houses sit in there at point seven all the time. Well, why? Well, all these really efficient CFL and LED light bulbs with their switch mode power supplies. A lot of them aren't Power Factor corrected. They have tremendously high harmonic distortion, I have a I have a the name brand, I'll protect the name the brand because it protects the guilty by anonymity. But I have a direct drive washing machine that when you know because I'm me and I'm a nerd. When I plugged it in, I put a power quality unit on it because it was like direct drives can be really bad. It is a power factor. point four seven.

Actually, I know what Brian you're talking about because I had one of those washers

it is like it and it's like when that drum is really spinning hard. It's like a one and a half KV a load. Not Ottawa, it's and and we used to have a toaster oven on that circuit and it kept popping, like kept popping the breaker because the amperage was so high, like like okay, well now I understand why. Okay, so

you were gonna say there was a bunch of weirdos was like inductors just plugged into the line in their basement or like just motors all over the place.

No, but what we've seen is like, like a lot of like we've had we've had academic researchers come back to us and say your face angle is wrong. Well, why do you say that? Well, uh, I was looking at this refrigerator. And since that's a motor, it needs to be inductive. And you're showing it is capacitive, or I'm looking at this lighting circuit and that should be resistive. And you're showing it to be capacitive was like, that's because they are, well, they can't be I'm sorry, they are when you have those those variable speed drives, and those those electronic frequency control drives and those switching power supplies. Very often those devices that used to be inductive can can easily swing capacitive, and then you get into this wild spot where the house will switch capacitive to inductive 70 times a day as the air conditioner turns on. And so you're just You just watched the thing go lead lag, Li lag, lag. And if you're a utility distribution, person, in some respects, it almost doesn't matter to you. Because if you get a bunch of houses, they're sort of their their average out, right. But in some respects, you really have to start watching when you get solar into the mix, because solar injects a bunch of real power, it doesn't correct for the harmonic distortion issue. And now you're sitting there and you've got a 1k var load to this house with no real power. So you've got a resonant circuit with no damping. So so it's like, alright, long term, that's unsustainable, we have to do some total distribution engineer that his entire load is going to be non 60 hertz and reactive, and see if they like you for very long.

So Scott, what are you looking forward to most in the future of either what you're doing now or with the country in general?

Um, I am really looking forward to accelerating the adoption of electrification of transportation, I am looking forward to trying to do that as best I can, in an equitable manner. Like I'm trying to figure out financial systems that don't penalize folks because they can't just go buy a Tesla or BMW or a Maki, right. The concrete over the course of its lifetime has purchased several electric vehicles. They are so inexpensive to own. But the barrier to entry is quite high. You know, I mean, we've got we've got 10 year old vehicles that have had less than two kg of maintenance done to them. Right. So it's like, ah, but but

they I know all about car maintenance. So yeah,

right. So so so there's, we've we've got to figure out ways to work around that. I'm very excited to play with the controls around battery, energy storage, and controllable shiftable loads, what you can shift versus what needs to actually turn on when you ask it to, like, you can't shift cooking, right? If you want that stove to turn on, it's got to turn on. But there's a whole bunch of stuff that can shift. And I think that there's a lot of hay to be made in terms of sort of leveling that loads. So it's not nearly as dynamic, and then all of a sudden, your your emissions go down, because you don't have to be able to have peakers. You don't have to have peakers. You know, there's a whole bunch that we can do there. I'm hoping that there is with the most recent IPCC reports, being as dire as they are, I'm hoping that there's more emphasis on those sorts of things, because there's a lot of of benefit to be had there.

Well, thank you, Scott, for joining us on this on this podcast,

talking about No problem. Thank you for having me. It was fun.

Yeah, we're gonna have to get you on the future. Because I think talking about like electrification, transportation and energy storage would be really cool topics for the future. Yeah, yeah, absolutely.

I'd love to do that. We've done a lot of research around that. And we've got a few more programs coming up. We're hoping to cross our fingers. So

Scott, where can people find more about you and Pecan Street?

Go to the Pecan Street website at pecan street.org. You can connect with me on LinkedIn, or Twitter Scott Henson one apparently I was not the first Scott Ensign I was the second on Twitter. But but any of those places connect with me and I'd be if anybody has more questions, I'd be happy to answer them.

One more quick thing before we sign out if somebody wanted to participate if someone wanted to get probes all over their, their house, how could they get on in on that

call the aliens take off the tinfoil now. So we have on our website pecan street.org. And we are org where our nonprofit in the top right hand corner it's there's a part Despite link, and I think it's top right. And if we have an open program that is funny, we don't we don't have I wish we had sustaining funding to just sort of continually go install, but we don't have that. But the moment that we keep lists of what you're interested in and stuff like that, in the moment, we do get a program to go do something. We go through the list and say, who needs to call these people?

Very cool. And with that, Scott, you want to sign us out?

Oh, sure. I don't, don't remember. Oh, there it is. I got it. That was the macro fab engineering podcast, and I was your guest, Scott Hinson.

And we're your hosts, Parker, Dolman and Steven Craig. Later, everyone. Take it easy. Thank you.