Managing Renewable Certificates with Molecule + Hive

0:00

Narrator Hello, and thanks for watching!

This video is a previously recorded demo of Hive, Molecule’s add-on for renewables. You’ll see how Hive helps renewable producers and consumers manage the complete lifecycle of production-linked certificates and obligation.

If you have any questions about Molecule and Hive that are more specific to your organization, we’re happy to show you more - reach out to us at molecule.io.

Enjoy the demo!

0:30

Kari Foster Thank you for joining us today as we give you an inside look at Hive, Molecule's specialized add-on for renewable certificates. And if we haven't met already, if you haven't seen me on a previous webinar, my name is Kari Foster. I'm the VP of Marketing at Molecule.

Now, we know that many companies trading renewable certificates and allowances face several challenges, whether it be multiple regulatory regimes, increasing data volumes, manual work involved, or just, you know, all the nuances and complexities that can make it difficult to model renewables in a way that makes sense for informing retirement and predicting the market. And that is why Hive was first developed: to provide functionality within Molecule that allows companies to manage the complete lifecycle of their production-linked renewable certificates.

Now I'd like to introduce our presenters. Tamasin Ford is our Chief Projects Officer here at Molecule. And Alex Cerbone, who will be showing you a demo later, is our Sales Engineer here at Molecule. We have a lot to show you today, so I will step aside and turn the floor over to Tamasin.

1:56

Tamasin Ford My name, as Kari said, is Tamasin Ford. I've been working with Molecule for several years now. And I, during that time, have done quite a lot in terms of implementations and seen, you know, many different customer requirements and ultimately Molecule solutions. At this time, I now work across a variety of teams consulting internally on solution design and architecture and Molecule tools and set up. And so I'm going to talk to you a little bit about what we are trying to accomplish with Hive as well as a brief case study in, in terms of what we've already been able to accomplish.

Just at a high level, Hive is basically our umbrella term for everything to do with renewables. You're probably familiar with the wide range of features that are present in ETRMs and on top of that, we are building on a series of renewable features, and so all of that together makes up Hive for us.

And what we're releasing in late 2024 here is what we call V3 of Hive. And so, all the way up to V2, we've been supporting the full renewables lifecycle across a variety of different certificates, allowances, offsets, some of them are listed on the screen, and, you know, for the full lifecycle from forecasting, minting, buying, selling, delivering, and retiring.

What is new in V3 is the more detailed modeling of eligibility and serial numbers, and then the mapping of specific obligations to inventory and then allocating against them, as well as a sophisticated optimization engine. And so we're going to actually have a demo of some of those new features and kind of hot off the press, so you'll be some of the first people to actually see these. And, you know, we'll also talk about just how the existing set of Hive features work a little bit for those of you who may be new to Hive in general. Here we have sort of a visualization of the renewables lifecycle and landscape. And so we've got various players, renewable producers, renewable consumers on the left and right top corners, the registries down at the bottom, and also a role in the middle for those who might be marketing renewables and on both sides of buying and selling.

The lifecycle for most participants begins with some sort of forecast. And so if you're a producer, Molecule has the ability to take in your production forecast and whether that is generating power through, you know, solar, wind, whether that's generating biofuels, perhaps, you'll be able to be forecasting the, not just the energy itself, which is sort of the bread and butter of the ETRM, but also the associated renewables that will come off of it.

So you have this integration with the ETRM, which is really helpful for you know, using, for example, a common forecast and being able to drive different types of revenue streams and volume streams off of the single forecast. So then the forecast makes it to minting. We are actively building out a series of integrations to various registries.

And so, you know, we have the ability to take in that minting information and essentially move those from forecast certificates now into inventory. And so once they're in inventory, Now you have deliveries to do against your forward cells, I should say, on the producer side. And so the minting comes into inventory and then you start doing deliveries out of inventory to draw down the inventory and ultimately have a forward view on if you have enough inventory, too much inventory, maybe you need to do a small buy, maybe you need to take some of it to market or, you know, adjust what your approach is there. On the consumer side, very similar except for, instead of your forecast representing your generation or your production, they're going to represent the obligations that you have to buy.

So whether those are obligations that are to regulators, compliance type obligations, or whether those are obligations to customers that you've entered into contractually, you're going to be able to model, you know, I'm selling power in Maryland and I need to do 10% of it green, or whatever it may be.

And then at that point, you now have a, a sort of forward looking view of what those will be and those can actualize over time. Meanwhile, you're going to be, again, entering into those same forward trades, except for this time, you're on the buy side instead of the sell side, and those will start to get delivered over time into your inventory.

And then where the new features come in in V3, is in as you're now taking the obligations and the inventory, you're able to do an in app matching of those, including some scenario tests so you can match and then unmatch and match again, and have a support for this optimization because in a lot of jurisdictions, there are multiple eligibilities, whether that is jurisdictional eligibility or vintage eligibility.

Each of those has a market price, you may have an alternative minimum compliance payment, and you'll be able to take all of those variables and the system will suggest to you a retirement strategy or an allocation strategy, which you can then go and retire in the registry accordingly. And again, starting to track this at the serial number level.

So that's kind of an overview of where we're at right now with Hive and as I mentioned on the previous slide, it does cover a wide range of certificates, and you can see some of those listed there on the bottom left corner as well. So just to talk briefly, this is what I would call a Hive V2 case study, but it really does show how Molecule’s sort of full lifecycle approach to it and integrated with the energy modeling really is impactful.

And so what was, sort of distinguishing about this particular customer is just how large their portfolio was. So they had a lot of solar product projects. They were in multiple jurisdictions. They had different types of contracts with those customers. So some of them were PPAs. Others would just fix leases. There were some that were being sold as merchant products on the market. And there were PPAs that had the RECs bundled with them as well as unbundled. So, you know, the whole sort of spectrum of different contract models. What this led to was a lot of spreadsheets in the organization. And also, you had, sort of different groups keeping their own versions of the spreadsheet. So FP\&A might have a certain version, asset management might have another version, risk might have another version, and everybody's version was big and complex. And of course, one of the things that happens with renewables is you're often needing to look at this at an hourly level out for decades. And so, these spreadsheets are not only across, you know, hundreds of projects, but they're also across hundreds of thousands of hours.

So all of this was causing a lot of challenges for them. It was limiting how often they could do reporting, really mostly happening on a quarterly basis. And it was also limiting the ability of the risk team to use modern risk approaches because they just didn't have all the data and analyses they needed.

So what was developed in the Molecule solution was a shared model between the power and the RECs, where we had assets and forecasts shared and the, the data then as it flowed in from the different systems was used in common across those two to develop both your power forecasts and power revenue streams as well as your REC forecasts and REC revenue streams. This customer, because they had such huge volume and such a diverse amount of data, needed a lot of integrations. And so that was a big feature of what we did in the implementation there. And a really key thing was establishing Molecule as a system of record.
[00:11:05] I think the, you know, people on the call who have been in a place where the system of record is spreadsheets or, you know, sort of not officially designated and so scattered across multiple systems, will understand how that one little sentence sort of covers a multitude of pain if you don't have it and benefit if you do have it. So everything in one place, you know where the single source of truth is, no data conflicts at all.

And then we developed their reports and their extracts that allowed them to get the data whenever they needed it and have repeated analyses done automatically. So, you know, we saw impacts of far more frequent reporting being available, higher data quality, you know, effort going from days to hours. And really, this is a growth company, right?

So the bottom line for them is they needed to know that they could continue to acquire assets without kind of losing control from a risk perspective or not knowing what their portfolio looked like and how new assets would fit into it. So at this point, I'm going to hand it off to Alex, and she's going to take a look at what V3 adds to Hive.

12:15

Alex Cerbone Okay, so before I share my screen here and we dive a little bit deeper into getting a look and feel of the system, what this looks like in practice, Hive is a solution that is solving a series of problems that we're seeing at cross sections of the renewable sector. So, Tamasin covered already, that we are seeing this as a solution for renewable producers.

We're seeing it from consumers of renewables and from the middle marketer perspective, but across the board here, we'll see this in carbon sectors, we'll see this in power sectors, we'll see this in biodiesel and fuel, and we'll see this across geographies. So I'm going to show you a specific example here coming from one very small segment of this total environment, but let's keep in mind that this is going to be a different example from what might be your use case just because of the diversity of the market that we're working within. So let me share my screen with that, and we'll pull up something that might look familiar to you, might be something new, which is the home trade screen that we'll get to within Molecule.

Some additional context on this is going to be organization of data within the Molecule structure. So trades, fairly self explanatory what we might find within this space. This is going to be full contractual agreements. So if we are buying and selling our renewable certificates, then we're going to do this with the trades grant and it will be captured there.

What might be something a little bit more abstract here is the assets side of things. So assets are where we're going to house curves outside of market data. Biggest use case on this is where we're seeing our natural exposures based off of our operational activities. So, if we are generating renewable power, then we're going to have solar power plants. We're going to have wind facilities. We are going to have our curves of our expected and our actual generation coming off of those assets. In this use case that we're defining out we're shoving this from the renewable consumer perspective where I have contracted my customers to provide them power in each of these states and they have chosen a contract.
[00:14:43] So let's go to my supplier plan, New Jersey. I've promised my consumer 65% renewable coverage on the power that they’re purchasing, but I am not a renewable producer myself so I'm going to have to purchase renewable certificates to cover that obligation to my customers. Clicking into this I'll see the curves that are coming in here that I have a consumption forecast coming from that group of customers at the hourly level and the monthly level since this is the grouping that I'm seeing within my certificates. On the other hand of this, I have set up buying programs. So these are the programs that I'm typically buying into to be able to cover the obligations that I have in place.

Now, let's go to the trade side of things and where we go about generating the tickets, which are the inventory positions that we'll see that are going to create the balance of accounts we need for allocations.

When I go to my trades, if I am producing an obligation for something or inventory off of something based off of my natural positions, then I could do that with a as-generated position or an as-consumed position. So I'm going to link this as I have a as-consumed off of my obligations and I could link this to my generation asset.

So I'll go to my New Jersey, 20%, I want my consumption on that at my monthly level, and I can link these pieces together. So, with that 20%, I'm going to say of all of the consumption for my customers in that group, I'm going to need to buy 20% of that consumption in renewable certificates to be able to cover that obligation.

That's how I would do it from a natural position standpoint, and it works the same going in either direction. What this does is you see that this product generated is a physical position. It's going to generate a ticket because of this, that's going to be a negative inventory position. So I'm expected to deliver these units on this date to this counterparty is what it's capturing within that. On the other side of it, I need to buy a position. So if I'm just entering a trade, and I'll cancel this one out, that this is a trading activity I'm taking, then the simplest way is I can just type it in. So I need, let's say, 200 units of M.NYHR5. When I type that in, that M dot symbol means that it's Molecule specific. It'll have the certificate that I'm housing within here. It'll have some of the main outlines of what that product means. But if I jump into my custom fields, then I'll see an option of some type of external identifier. I could put in additional information around the vintage, the eligibility, trace back on that, whatever I might need to carry within this position.

Since this is physical and I'm buying on this side as well, it's going to create a positive inventory position. And now I have exactly what I need for this allocation. I have a positive ticket with positive inventory and I have a negative ticket with an obligation set. So you'll see when we're servicing the different types of customers that we see within this space, whether it's the producer, the consumer, or the middle marketer, how we get to those positive and negative inventory positions is irrelevant for this specific allocation.

So it's a general term, a general screen that we'll see that marries these types of customers together and how we can view the allocations. Once I have those positions in, let's take you over to what the Certificate Allocation screen looks like. So I get these in, let me come back to my So I'm going to click on my home here, and I'll see my current standing.

So I have a track across the top of my time frame here, and I have my existing inventory, and my existing obligations within this space. The red and green delimitation is going to be off of what's already been allocated of my existing inventory and what is outstanding within that. On the bottom, I'll see my current obligations. So for this scenario, these are obligations that I have to my customer set, but these could also be sale positions that are within a particular geography of a particular set. It's very flexible in how we're organizing this to be the most efficient use of our data for our use case. If I click into one of these offsetting positions, so let's go into this New Jersey bucket for March of 2025.

If I have anything existing in my allocations, it'll show for me here. It looks like this one. I have a 0% allocation to find out for this bucket. Going over to my inventory to expand that out, I am able to simply drag and drop to create an allocation. So let's do, this is a total allocation, let's say I only want 200 units from here.

I can allocate this piece and I can continue to drag and drop these pieces to manually allocate my position. And there's really three tiers of automation that we could set here for you. So tier one is strictly matching our positives and our negatives. So we see all of our obligations on the board. We see all of our inventory on the board.

Then I can manually push one to the other. Our level 2 is going to be around eligibility. So we will define this with you as part of the implementation process and understanding the cross-eligibility and the eligibility of our products based off of the geographies and the legislations that we're working within. So I might know off of this case that New Jersey has one of the higher requirements for their renewable certificates and it's really only the New Jersey certs and the New York tier one certs that can be assigned to my New Jersey certificates. So level 2 of this program would only show me in my certificate inventory what is eligible for this.

I'll only see my New Jersey certificates and my New York tier one. Level 3 is where we really get the maximization out of the automation processes and the optimization practices, where we're going to make recommendations for you of which pieces of inventory to assign to these obligations. So that's going to take into account your existing inventory levels, your vintages, your cross eligibility, your expiration dates, and even the cost of your obligations at play or the cost of your alternative compliance payments so that you can make the best decision on where to allocate your resources.

So that pushes a recommendation here. And then once I view my recommendation, I can go in here and finalize this transaction. So when I finalize this, if this is meeting an obligation with a registry, then I could automatically push it back to registry, or if this is finalizing a trade agreement, then I could push the serial number of the certificate that I got out of my inventory to the trade that is showing the sale on that agreement. So I see the full traceback in my history from, we sold this unit to this counterparty and it was either minted coming from this area or we bought it from this area and it went through this registry to get there. So it's going to connect all of those pieces.

So let's hop back here, and I've done that one individual allocation as example of the main focus for the certificate screen. There's three main points that we were trying to get through here, consolidation. So one is getting all of your renewable certificates, your Guarantees of Origin, your RGGIs into one place here.

What we see a lot within the renewable space is, since there's so many different registries we're working with, there's so many different legislations, we have some Excel spreadsheets sitting here, some direct connection adapter sitting there. If we can consolidate that information, then we have a better understanding of our total risk position and our total exposures within the space.

Next is going to be automation. So it'll talk about the registry connectivity. We'll talk about automation of connecting our supply or our demand for these renewables to our natural exposures within the market. And how we can match these automatically, push through the finalization process. And the last piece is optimization.

At the end of the day, we're all here to make money. So if we can find the best way to take our most expensive obligations and meet them with our least expensive inventory, then that's going to translate directly to a bigger bottom line for all of us. I think that is a good cover of what we were looking, what we were looking to cover in the new Hive screens here. I'm going to pass it back to Kari.

24:55

Kari Foster Thank you so much, Alex. Really appreciate that comprehensive demo. And now as, as she mentioned, we are going to open it up to Q and A. We do have a few questions. First one broadly, how does Hive Handle different certificate rules across countries?

25:19

Alex Cerbone Yeah, I could take that one. So for different certificate rules across countries, it works the same way that we see in the U.S. across states and markets that we are seeing as a collaborative effort between our implementation teams and you guys, since you are the experts in the markets that you are engaging in, then we're going to take input from you and building the algorithm for where we see the cross-eligibility and then we will be able to overlay our industry expertise in how we see the vintages, how we tie in the cost structures to be able to give you the best output for allocation.

26:01

Kari Foster Another question. Thank you, Alexander. Can you enter obligations only by percent of sales or alternatively as absolute numbers?

26:12

Alex Cerbone Yeah, it could go in by either. So percent of sales was strictly for this example and to show you how we can tie it to your natural processes. If you have an actual value, then we could link that as well through a ticket. So like I said before, it's really just about creating the obligation as a negative inventory. It's an expected outflow of the certificates that we hold within the space, how it gets in their absolute number or percent. It works either way.

26:44

Kari Foster Thank you, Alex. And another question we received beforehand: How are alternate minimum compliance payments handled?

26:57

Alex Cerbone Yeah, Tamasin, you want to?

26:58

Tamasin Ford Yeah, sure. I think the way that I like to think of alternate minimum compliance payments is sort of like an unlimited inventory at a certain price. And so when you're doing an optimization, if that price is lower than the price of the value of the other inventory that you have that you bought on the market, then obviously you would want to, you know, use the cheaper compliance payment rather than the more expensive certificates in your inventory. So, you know, from a, configuration perspective, we would be configuring kind of like an inventory bucket that has a, I guess you could say, unlimited fictional amount of alternative compliance payments, and the only difference would be that if you select that there's no retirement to do, it would just be something you would report out and close out that obligation. And, you know, it wouldn't be as much about tracking your inventory for that particular item.

28:06

Kari Foster Right. Thank you, Tamasin. Another question that we've just received: Does Hive have an external connection to the CERT platform, such as PJM GATS, that would auto create the trades in Hive, or would trades be manually entered in Hive, replicating the transfers already captured in GATS?

28:31

Tamasin Ford Yeah, I can talk about this one. So we have a few integrations that are already live, and we are actively developing a larger set of integrations, and so typically an integration and I don't believe we have GATS, I think we have GIS, which is ISO New England, and we have EMA, which does cover GATS, if you are using EMA, or APX is the other name for that. The connection would then pull them in and it would create them often as tickets rather than trades. Although in some cases, if you have your forward trades in EMA, we do create them as trades as well. So, there's a few different variations within that integration that pull the data in at different points in the lifecycle, just depending on what kind of data it is in the platform.

29:38

Alex Cerbone And a big piece of that, too, is how you want to handle settlement. So if you're using GATS as your avenue for trading, and they're handling the settlement process for you, then it's simple. We'll simply take the delivery on it, and we don't need to worry about carrying the trade. If you want to run your invoicing and your settlement out of Molecule, then we will need to have some representation of that trade within the system.

30:02

Kari Foster Big thanks to our presenters, Tamasin Ford and Alex Cerbone. Thank you again for joining us today, and have a great rest of your day.