Advanced Battery Analytics with Shyam Srinivasan (Zitara Technologies)

Advanced Battery Analytics with Shyam Srinivasan (Zitara Technologies)

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hello everybody and welcome to the transmission podcast it's me Quentin and this week we've got sham CEO and co-founder of zitara Technologies in now Sharm comes from a company before this that I really admire it's Nest who make the thermostats that we all know and love and um got bought by Google and now they're doing battery analytics software to figure out how to get the most out of assets and make more money with them so really enjoyed this conversation we talk a lot about hardware and software at the edge and what that really means and the impact that this kind of software can have on asset owners and ultimately the returns for battery assets so if you like this one please do hit subscribe and like and put a comment in the comments it really does help us increase the reach and get to more listeners let's jump [Music] in sham thank you for joining us on the podcast Quinton good to see you so zatara should we talk about that to start with what is zatara yeah absolutely uh zatara we've been around for about six years uh we're a 35 person company based here in San Francisco and we're focused on uh real time Edge monitoring and controls for best so we try to make your best more profitable safer uh and last a lot longer and and how do you do do that then so what what do the 35 people do are they software Engineers or are they um you know other types of engineers yeah uh primarily we have uh two two categories of engineer at Zara um software Engineers that build controls so controls experts uh a lot of our team comes out of kind of the autonomous driving world uh so we are really experts at Edge controls and Cloud Edge controls um but you know really the other half of our R&D team is battery modelers and algorithms experts so we get really deep into the chemistry of batteries and that's what allows us to control them better at the edge and what's the what's the reason that I mean we've had a couple of um battery system analyst companies if you like or analyst software companies on and um they've done a really good job of answering this question so I want to ask you it to you as well what's the reason that a customer say you a grid scale actually do this differently hold on going edit this B down and so we spend our our whole life on this podcast talking about grid scale batteries um which is of course a massively growing market and lots of different types and chemistries and and um uh blends of um batteries and Battery Systems out there so for for a owner of energy storage assets what's the advantage for of of coming to zatara versus going to the the original equipment manufacturer say Samsung or Panasonic or catl yeah absolutely well you know uh across the board today we've seen kind of the dominance of one chemistry uh and that's been the last few years of uh lfp batteries being by Far and Away the cheapest option uh for grid scale they are notoriously difficult to manage um you know especially as the formats of these sort of uh these cells and and the the choices start to get uh larger and more consequential you know we see different kinds of effects make it harder to tell how much power or energy you have at a given time uh even all the way down to the cell or rack level so you could look at one of these sort of uh uh uh battery voltage curves uh and kind of compare lfp to uh previous Technologies like nmc um or you know in the cell phone era lco and you'd see kind of nice linear curves uh for previous chemistries that told you you know for a particular state of charge how much voltage you should expect this because systems you they measure voltage as a proxy for state of charge so when you're when you're when your iPhone tells you it's got 90% or 85% the way it's doing that amongst other things is actually measuring voltage and then looking it up on a little chart exactly yeah uh if you want to get to looking it up on a little chart you often have to let that battery idle for a little while uh and so then even more complex is trying to sus out while you're using the battery while you're doing that discharge how much more voltage drop has happened because of the discharge and so if you can back all of that out while the battery is discharging uh then you can tell how much power and energy you have it turns out your OEM systems are often 20 to 30% off during a discharge wow 20 to 30% is that 20 30% uh error I guess yes that's right all the way down at the cell level and you'll see Corrections come out to the telematics that end up getting reported for your Market operation or for you know for your grid op uh for your ISO um so you know you'll see smoother signal at the site level but if you drill down and look at you know individual inverters or racks within a best you can often see these 20 30% jumps uh frequently and so measuring state of charge or the the percentage of energy in a battery to keep it simple why does this why does this even matter why is this so important well uh you know it depends what you're trying to do with your battery that day but almost no matter what more hours of power translates to more Revenue uh on the on the whole over a long period of time so you know uh our customers you know they may be trading uh energy wholesale so they'll have a a sort of day ahead activity uh and then a a you know a real-time activity on the next day uh and if you you know bid the most aggressively you possibly can day ahead you're not going to get necessarily awarded all of that energy that you've you've put up uh for um for sale during the day you really want to know especially kind of towards the end of the day when prices might be peing exactly how much you have left in the tank and the realtime signals that you have to do that today if they're inacurate you're either you know incurring sort of opportunity cost by not trading as aggressively as possible or you're ending up you know with a base Point deviation in a market like OT um or you know other penalties for not being able to serve what you've committed and we talked sorry and when you when you at the beginning of this conversation you talked about this problem getting worse so the the change in chemistry over time from let's just do it most recently from nmc to lfp which is now the the dominant uh battery cell that's being installed around the world for all the good reasons about supply chain you know um input materials cost um but if I read between the lines you're saying that actually measuring state of charge from voltage of lfp cells is more challenging than nmc is that correct yeah that's right well well with any battery I think once they're old cold or under load um you know you like we like to say that they're they're more difficult in those moments um but with lfp batteries we're seeing shocking problems just on day one where you know you might expect a few years before you have problems on previous chemistries and so how do you guys do this better than the original cell manufacturers what's the secret Source yeah well you know it's it's not really even cell manufacturers that have spell specialized in this to date um you know largely uh we think about cell manufacturing is this incredibly complex chemical manufacturing um kind of if you've ever been to a battery Factory it's a very you know clean room facility more complicated than manufacturing silicon uh what a what a thing um it turns out this is a wholly separate skill set than writing software uh today you may see a module maker in the middle of the value chain being tasked with you know provisioning a battery management system hardware and usually getting the software just kind of on on board that BMS by default uh these are often some of the most profit squeezed players in in the battery value chain day and you know um they may be focused on just razor thin margins for assembling those cells into a module but they're really not putting a lot of R&D into the into the equation additionally they don't really have any ltsa or you know contract or warranty associated with the performance performance of the algorithms on the BMS you know usually an availability contract says my inverters or some percentage of the inverters in my system need to be up and functional uh but nowhere does it need uh mean that um you know 50% SS means I have 50% of my energy usually not in the contract and when do you guys get involved so say um I'm an asset owner I'm going to build a new well I've got existing assets operational right now or I'm considering building a new one when do I say right I've got to call Shan and get his team involved absolutely well today we're focused on retrofits so uh we'd love to talk to you if your you know max power High sustainable limit readings from your uh lfp battery are noticeably wrong you're running into base Point deviations you've noticed that thec is not accurate uh and you care about your your trading clearing you know uh as expected did uh we think about it kind of as a market clearing problem because when you submit that day ahead offer you're including s so pairs with your with your power and and and price uh and so if your s so is 10% off that means that your bid isn't clearing correctly so if you run into those kinds of problems we'd like to talk to you we also love to engage more Greenfield projects uh so when you're at about your 30% uh completion Mark we do love to in and audit your networking diagram um you know this is just sort of a service that we like to provide we think that it's very important if you're constructing and planning to own and operate that you have access to the right data and then you have access to the right control and so 30% is right about the time when we can you know get ahead of any issues um but then then we got to wait uh until the until the assets operational uh to really help but you have um going back to the first thing you said there which is that if you if you see if you're an asset owner and you see these kind of errors or you're seeing deviations then um then pick up the phone the thing is being able to see those things in the first place right because you've got measurement challenges compounding on top of each other you think about I'm sure you know this already but um measuring you know what do you measure at the cell level at the rack level what is the bmsc and then you've got balance of plan and um Transformers where and then you get to the the boundary meter the settlement meter there's a lot of losses and noise in between those things and you get you get paid on the boundary meter right so um how can folks think about you know they own and operate assets making sure that how do they measure that what should they be doing or thinking about to make sure they can find out whether the data is right in the first place what's your what's your guide for sure well you know this is actually something that we we use the the Moto uh tool for and we're going to be getting uh on board with that really soon we're really excited we look for places where people are either you know generally underperforming the market but if we can get down to time series we're looking for places not just where people had base Point deviations but where they appear to have purchased you know energy uh at high prices unexpectedly so particularly um you know uh in markets where the customer might have committed to something after a peak event that's a that's a really really costly day what we see happening is you know prices start to take up during the day the customer starts to discharge their battery and then their state of charge or state of energy reading uh probably goes down faster than anticipated the way we can tell is that maybe because they have an ancillary service or something committed in a future hour they end up purchasing energy at this peak price so you know putting aside base Point deviations the fact that they ended up purchasing energy at you know in in Texas close to the peak sometimes this can wipe out you weeks or a month of of profits to to just had this one event um what we tell customers to look for and an analysis that we'll do for free for you we we'll do a complete analysis for for you in terms of the accuracy of your signals so if you want to understand your balancing State your state of charge your state of energy your power power signals which ones are accurate or inaccurate you can send us data and we'll figure it out but a key place to look is to say my system was reporting that I had 100 megawatt hours at this at this time then my you know Revenue grade meter told told me that I put out 50 megawatt hours over the next hour if my state of energy says less or more than 50 megawatt hours by quite a lot that's where we start asking questions if that makes sense so we compare for that s so does that well reflect actually the percentage of energy in the asset when you compare it to what went out on the revenue grade meter especially if you can correct for things like auxiliary loads that you mentioned yeah everything comes back to that Network diagram that you mentioned at the beginning how about access to data then because um I I just think it's absolutely terrific that we have companies like you guys and there's some other European folks doing similar who are saying who are really challenging what is possible with the data versus the OEM I think it's um I think it's absolutely brilliant um and yeah by being highly specialized there is a there is an argument that you can really add a lot of value versus um the oems but do the oems play nice and don't you need access to data cuz historically a lot of our customers who own assets they're surprised by how in some cases some are really sophisticated but many cases they're surprised how little access to data about their own assets that they even have um and you'd think that that in this this day and age um if you spend $50 million on a on an asset um then you've got a right to see under the hood but that's not always the case so yeah are the oems playing nice what do you advise companies put in their um procurement and and construction uh contracts and how do we how do we create an environment where all this data is open for companies like you to come in and really make a uh a big difference yeah absolutely well you know there's there's one notable vendor in the space uh that's particularly closed with data um uh and that's Tesla probably not a secret um we outside of you know those kinds of projects where honestly we we've steered our customers to looking at evaluating us on on non- Tesla sites of which there are many um you know uh uh we've never had a problem with an oem not wanting us to have access to particular cell level or battery data uh it it ends up working out to much more of an it challenge um if the site hasn't been configured to be get get getting access to the most granular cell level data there may may be elements that just sort of average or down sample that information along the way out the uh out to your historian and you know uh it's a matter of wrestling with your sort of integrator or uh supplier chain to be able to get access to that data um what we have seen though is that more modern systems and things that are getting constructed today the data architecture is generally more modern and and it's easier to get access to whatever data you'd like um you know when we look at assets that were constructed in 2021 2022 again it's not that anybody doesn't want us to have access to the data but sometimes it's a pain in the ass yeah and then if you the last thing you want to do is start demanding that uh you know there's a cost element too and customers uh what asset owners don't want to have on-site servers or really high bandwidth connections for cloud storage and all the additional cost there it becomes like is it even worth it um so this era can we come back to this era this state of charge error does it get worse over time yes absolutely so generally what we're looking at is the state of charge of individual cells uh within Iraq but there might be 400 cells adding up to your DC bus voltage within that rack and your limit by the state of energy of you know at during discharge the lowest cell in that stock now that could be the most degraded cell in the stack it could be the cell that had had the most you know temperature and therefore had leaked the most internally uh it could be the coldest cell in your stack that is actually going to hit its voltage limit before the rest uh so at any given time your act your algorithm is actually trying to figure out which of these 400 cells is going to limit that rack then behind whatever your kind of uh ACP topology is when are different AC blocks in your system going to turn off so depending on how you've configured things you might have thousands of cells and you're actually trying to guess which is the one that's going to limit you uh at any given time uh so as your cells degrade you anticipate there being more variability from cell to cell and then it becomes that much more complex toig figure out which one's going to be the limiting one um you mentioned you know uh the sort of bandwidth and the data connections this is definitely exactly where zatara tries to solve that problem you know in a particular site there's 400 cells in a rock we might be looking at 10,000 cells or you know tens of thousands of cells in a system uh and uh you know the way that we address this in order to be real time is actually exactly the way you said we put a server into your cabinet and we live primarily on board that server this means that you know we don't have kind of a dashboard or analytics Services the way that some of our friends at twice orur do uh we're just the controls and we're replacing the signals that you're using in your existing system so you know however you are getting data off of your EMS uh however you are using those for Market operation and then whatever telematics are coming from your EMS and going into your Cloud going into your ISO we are replacing those directly at the edge and that means that we need to be on Prem uh in order to be real time in order to be able to soak up all that data quickly enough uh but then also to be compliant um you know you're not allowed to use cloud Solutions in the loop for dispatch and so uh we fit right into your nerp case with our kind of secured server so you're physically going on site with a big metal box and putting it in in a server W somewhere that's exactly right on a per kilowatt hour basis this is much cheaper than getting the data off so um I want to come back to a hold on so a Hot Topic at the moment in our world is cell balancing there's just so much change and Improvement and iteration in how systems are balancing cells and I know that um you and your team spent a lot of time thinking about this um could you just for our audience just go straight from the top what is sell balancing and why does it matter and how are you guys thinking about this problem yeah absolutely well uh you know cell balancing in a system that's brand new where all of your cells are identical and have all started at exactly the same start state of charge should be a nonissue uh unfortunately right after moment one uh this idea that every battery has the same capacity and that every cell has is at the same state of charge goes right out the window so you know as I mentioned uh behind a single rack where you've stacked 400 cells in series and then depending on your AC topology behind that you may be limited by whichever cell in that system has discharged to zero faster and that that may be because you can't discharge more of the cells while you're limited by one you know the simplest example is in a single series rack you can only discharge the cells together now this Cascades up the system right we have racks that are organized into DC buses that then uh kind of Might connect in different configurations to a PCS to form an AC block and depending on how many of these AC blocks are uh in your system as well as what controls you have behind each one to balance across different racks you're going to have different limitations at any given time in your system and different tradeoffs to take those batteries down and allow them to balance so typically what we're seeing from oems today is that in in order to trigger kind of a balancing condition you often need to bring that battery all the way up to 100% or all the way down to 0% uh and let it idle in order to trigger balancing and this is because with those lfp batteries the very top and the very bottom there's a little bit more observability into the state of charge because those voltage curves are a little bit friendlier um if you choose the wrong subsets of your uh asset to take down for this balancing activity you won't be improving the performance of your battery and you may be actually um uh leaving a lot of sort of opportunity cost on the table by picking the wrong element to Balan but because you have to go through this sort of onerous exercise of taking that rack all the way down to zero you know it is very critical to pick the correct element of the system to balance if you do this systematically and and hit the outof balance racks with this balancing activity consistently and it can take a a very long time to get Back in Balance um then you can actually maximize the range over which you have max power in your system so if your cells are you know 20% out of balance you might find that you can only get your max power between 10 and 90 in your system and we find that 10% is a very common figure for how much out of balance your system is but over time you might actually be adding one to one and a half% mean imbalance per month and your present balancing strategy may or may not be addressing that at all so we'll see you know customers that have worked for with their OEM for a long time instituting some of these new approaches to balancing but the uh the mean balance is still steadily drifting up at that 1 and a half% a a a a month and they're getting less and less of their actual Max power bound the operational challenges of managing these big batteries are it's just fascinating because you have measurement you have measurement problems like we've just talked about ranging from the granularity of Time series data to where it's actually being measured and then you have these operational challenges once you've measured it you're not sure whether it's right or wrong in some cases you have these operational challenges about you know real physics about different cells um having different voltage curves and then operationally you have this compounding problem of balancing that every month is getting more and more challenging and at some point you have to kind of RI rip the Band-Aid off go down to zero and go back to full full charge which is expensive and um comes with well it's uh an opportunity cost and um figuring all this out is is just fascinating and so how how do you guys approach this problem then if you're thinking about balancing a data l approach to balancing what would you advise asset owners to think about yeah absolutely um we think asset owners should think about Automation and intelligent automation so you know the worst case scenarios we see today we have asset owners that have to take their entire site down in order to perform this balancing activity you know the the better sort of EMS systems that we're seeing out there today enable customers to go PCS by PCS take a partial outage and only balance part of the site but what we think is really merited is what you get when you install Zara which is a prioritized intelligent balancing system you know number one we're giving you realtime observability into the state of imbalance behind every one of your AC blocks so that's not only critical to knowing how much power you have right now but if you go through this activity today we're the first time you're getting feedback on how much you've actually unlocked in your system and so you know ultimately that's best for setting up automations that means that you can identify which blocks are costing you the most hours of power make sure that those are balanced whenever there's an opportunity and then we want to configure things like making sure that we take advantage of time when you're not playing to use that uh asset or where the costs are low for taking that one PCS down and automatically just have the asset always optimizing itself because it does take really a long time and persistence to get these things Back in Balance uh we we just think you need to be taking every possible opportunity uh and you know uh typically a battery is only really making money for six hours a day um so we want to use the rest of the possible time and my last question before we get on to the standard last two questions of the podcast so if you were um some of our listeners well many of our listeners are asset owners and operators so whether that's funds or utilities um companies and Folks at these companies that really know operating real asset let me start again hold on and so can you do me a favor can you for our audience who is primarily folks who own and operate Battery Systems and um you know grid scale assets maybe already online or are developing and financing these at the Contracting stage what should they be adding into the contract what's the bare minimum for data requirements um that they want to make sure is in the contract what your what's your kind of 101 guide for that you know we get this request quite a lot and going to be publishing something here in the next month or so hopefully uh we think that there's a key skate of points list that is really important for making sure that you're monitoring your power reliability as well as your safety and you know that's a big topic uh this week after what happened at Moss Landing uh we think it's really important to ensure that if you want you should be able to go in and get access to high granularity cell level voltage data and if possible this should be hyedes voltages from each rack and for a relatively new system uh this would be okay but you know this is perhaps the most important thing in addition to the the current or power ratings from each Rack in your system as well as the temperature ratings that you're able to get your hands on if you have a problem it's very critical to be able to go back and pull that data that's not that's only at the edge and and use it to be able to debug you know why did I have a safety issue why did I have that baseo deviation if you're not doing it uh already today we we highly recommend it yeah you need to store the boring data when nothing's happening um just for when something does happen okay now to the last two questions so firstly sham um is there anything you'd like to plug for our audience or um our listeners it's generally battery energy storage good scale batter energy storage folks from Europe us and Australia yeah I think uh just a pair attention to uh what we're going to be launching this month uh at at satara so we are coming out with our best owner operator focused solution uh this is our on Prem box and we'll have a couple different flavors uh our on Prem realtime solution for soaking up all of the data that you need hying it correctly and spitting out replacement real time signals that you can use for Market operation um so we think we're the only Sol on the market that actually does the on Prem real time uh we'll also have a big announcement with our uh kind of corporate partner uh Emerson um related to zitar live being available to customers of the Emerson Ovation DCS uh system so stay tuned for that very cool and also you're doing Hardware which is great Hardware is back in Vogue finally as an engineer I'm so happy that it feels like startups everywhere are getting back into doing real things in the real world um very very cool the hardware itself it's just a hardened you know dull server but ultimately uh I'll give you the Kudos anyway I appreciate it and um Sean what's your contrarian view what's the thing that you believe that not a lot of people do yeah we think that battery signals can work as at the edge and I think we see so many different sort of folks out there that provide Cloud analytics uh and what we think is really underloved in the world today is things that you can do on board Hardware directly at the edge because this is The Edge what is for um folks who aren't in the in in in this world what is the edge well the edge is is a it's basically two things one it's the idea that you don't need to transfer data from your site from your premises across the internet to get anything done you know we can do all of the computation and Analysis of that data directly on premises at your site so the edge is the ability to do that with limited compute you know we're not using a supercomputer in the cloud uh but also it's the ability to do that in a secure and compliant way that doesn't open you to any kind of you know vulnerability or threat and so really a lot of the reasons that we're doing Edge compute it's really twofold one we can get access to so much more data without paying the data transfer costs and then two it's for cyber security and resilience often for your ner zip case if you really wanted to solve this problem you're not allowed to use a Cloud solution you have to use an nonpr One Like Us it's funny there seems to be there was in the last 15 20 years there been a huge shift to Cloud everything's moved to the cloud and that's been enabled with um you know 3 four 5G over those that that period and it's pretty much in every sector you're seeing a a move now to cheaper compute on chip and not bothering to send stuff so for example um a lot of you know you only have to look at um consumer electronics and then use of large language models and the the way that you can squeeze models down now to run locally and all of the security and privacy benefits of that are immense it it would be interesting to see whether this decade we see a switch back away from cloud and back to people doing compute themselves um AWS has had one hell of a run you know growing like 15 20% year on year forever so maybe maybe their time has come to an end maybe I yeah yeah I I I think think that it's always been a partnership and and maybe it's about that privacy element in the end right maybe you could get the best performance with a cloud model but if it's really important that you stay secure or if you don't want your data going up to the cloud then it's always been really important to have that edge compute um you know I was fortunate to be one of the first few Hardware engineers at Nest to start my career and you know we were definitely the a Pioneer in the iot space making a distributed resource available through a cloud API but I think the thing that everybody cared about was making sure that their data about their preferences how how they moved in and out of their home that kind of thing did not go up through the cloud service and so we had to figure out how to marry what you wanted to do locally in order to be private uh with what you could do to to make the the resource available to the grid and so um you know I think we're seeing that scal to front of met Assets Now which is is just wild and and really enjoyable what was it like building let's do this what was it what was it like building nest I Absolut I think everyone who has a nest absolutely loves it it's just by far the best product it looks it looks the part on the wall um it was so awesome when it first came out and even now they are it's kind of it is the leader right so if you were involved at at nest in the early days what was that like you know for a a kid coming around out of college it was the best possible experience in the energy industry I think it was this moment of real optimism and we saw you know utility companies jumping on doing Pilots with us um because I think people loved you know delighting their consumers and it's so rare for a utility Innovation office to to to be loved um by their consumer uh by providing them such a beautiful object but I think the trick was you know how do we actually start to make term resources out of distributed networks like this and I think you know Edge intelligence became a real part of that and you know uh I think everybody's kind of surprised the batteries weren't so firm so it's surprisingly uh the idea of using Edge compute to to to understand what's happening at the battery uh ended up being necessary as well so it's kind of Full Circle for me very cool well sham I want to say a massive thank you for joining us on the podcast um we'll put links to all the stuff that you guys are doing in the show notes so if you're listening to this and want to check them out please do and um when I'm over the West Coast I come come by for a beer absolutely yeah everybody should come visit our battery lab in San Francisco awesome thank you very much indeed see you soon Quinton thank you so much

2025-02-21 13:37

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