Using JOBS EVSE 1.0 to Estimate Employment Impacts of EVSE (Text Version)
This is a text version of the video for Using JOBS EVSE 1.0 to Estimate Employment Impacts of EVSE presented on Dec. 21, 2021.
Sandra: Okay, we're going to go ahead and get started. So, welcome, everyone, to today's webinar. I'm Sandra Loi, from the National Renewable Energy Laboratory. Our team at NREL provides technical assistance to the Department of Energy's Technology Integration Program, and our network of more than 75 Clean Cities Coalitions, located all around the United States. Today, you'll hear about the soon-to-be-launched JOBS EVSE 1.0 Tool that has been created by Argonne National Laboratory, our sister lab who also supports the Department of Energy's Technology Integration Program and the Network of Clean Cities Coalitions.
JOBS EVSE 1.0 is designed to permit quick analyses of economic impacts associated with deploying electric vehicle supply equipment. Built off the Excel-based platform, common to other JOBS models, it allows users to estimate economic impacts for individual states, regions, or the United States as a whole. Argonne's Marianne Mintz and Yue Ke will highlight the new tool and show how coordinators, decision makers, and industry stakeholders can use it to estimate jobs associated with all aspects of EV charging. Before we get started and I introduce today's speakers, I'd like to review a few items so you know how to participate in today's webinar. Next slide please.
All attendees are muted upon entry however, you will be able to unmute yourself if needed. Please remain muted when you are not speaking. You can also turn your camera on and off if you'd like. You can connect today's audio through your computer or over a telephone. For best connection, we suggest connecting via a telephone. You can change the layout of your screen by clicking on the view button, which is located in the top right corner of your screen. If you select "Gallery", you'll see all attendee videos. Sorry, a little technical issue on my end. So, if you select "Gallery", you'll see all attendee videos. In the "Speaker" or "View" layout, the speaker will be highlighted on your screen.
We will host a Q&A session as the conclusion of Marianne and Yue's presentation. We encourage you to submit questions via the chat feature as the presentation is taking place. We'll address as many questions as time allows. You can also use the chat to reach out, should you have any technical difficulties, for assistance, throughout the webinar. Please reach out directly to your host, which is myself, as well as my colleague, Cassandra Sulmeisters. The webinar is being recorded and will be posted on the Clean Cities Coalition Network site in the next seven business days.
So, as I mentioned, today's webinar is being recorded and will be posted on the Clean Cities Coalition Network website or used internally. If you speak during the call or use video, you are presumed to give consent to the recording and use of your voice or image. Next slide.
So, now, I'd like to go ahead and introduce today's speakers. Marianne Mintz is a principal energy analyst within Argonne's Energy Systems Division. She has over 40 years' experience in transportation and energy analysis and has authored over 120 publications in the field. Her current work centers on infrastructure requirements of alternative fuel pathways, especially renewable and natural gas, electricity, and hydrogen, and economic impacts of fuel cells, electricity, hydrogen and natural gas fueling infrastructure. She's an active member of the Transportation Research Board and past chair and emeritus member of TRB's Transportation Energy Committee. She holds a master's degree from UCLA and has completed post-graduate work at the University of Illinois at Chicago.
Yue Ke is a post-doctoral appointee at Argonne National Laboratory from Davidson, North Carolina. He received his PhD in civil engineering from Purdue University and his MS in agricultural economics from Oregon State University. Prior to joining ANL, he has worked for the Oregon Department of Transportation, the United Nations World Food Program, and the U.S. Peace Corps. With over a decade of experience in economic modeling, his research interests include transportation and economic development, transportation energy, regional economics, and spatial econometrics. So, now, I'd like to pass it over to Marianne. Marianne, you can go ahead and get started. Thank you.
Marianne: Okay. Thank you, Sandra. It's really a pleasure to be with you today. We're going to do a tag-team presentation. I will speak, and then Yue will speak, and then I will come back, and then he will finish off. Just a quick overview of today's discussion, we'll, as I said, I will speak. I'll give the overview, and then Yue will provide the methodology, and we'll talk about default data and assumptions, an illustrative scenario, and next steps.
The image that you see on the right is of the webpage where other JOBS models are posted. There is a link from the AFDC to that webpage. This new model, which we've renamed JOBS EVSE, will be posted at that webpage. I can't tell you exactly when because we are starting to run into the holidays and the lab will be closed after Thursday, but we hope that it will be up on the website shortly after the new year. So, stay tuned. We will send out an announcement. With that, I'm just going to start talking about – no – the overview.
The model, JOBS EVSE – and the reason why we've renamed it – in the announcement, it was called JOBS EV – is that we're looking solely at electric vehicle supply equipment. This is only dealing with EV infrastructure. The model does not deal with electric vehicles themselves. We'll talk about that a little bit at the end. But basically, we're just dealing with infrastructure. So, as you can see in this infographic, we deal with the charging infrastructure at the station.
So, from the service drop, we may have a transformer, we'll have a panel, we'll have the charger. That's the biggest piece of equipment. There's more equipment, and we'll get into that in a moment. But we're not just dealing with the equipment that is onsite. That equipment has to be produced. It has to be installed. It has to be shipped. All of that, those expenditures, have an impact on a supply chain.
As you can see in this center circle, expenditures are required for energy, construction and planning, there may be revenues involved at the station, and the various equipment in terms of procuring it and installing it, and the station operation and maintenance. All of those expenditures produce dollar flows, if you will, in the economy. People then are employed to produce that equipment, to move that equipment. Those job holders then go on and spend those dollars elsewhere in the economy. We call that induced economic activity. They may spend their earnings on restaurant meals for their families, on housing, on vacations, all kinds of things. That has an impact on the economy, and it also produces additional jobs. So, this holistic approach is basically what is embodied in the tool, and we'll keep coming back to that as we go along in today's presentation.
JOBS EV 1.0, itself, as Sandra said, is an Excel-based tool that estimates economic impact for user-defined scenarios. As it's designed right now, the tool can be used to address economic impacts at the state level for any of the 50 states or the District of Columbia, at the level of census regions, nine census regions, or for the country as a whole. That map on the left shows the census regions. The user, in their scenario, they define the number of the capacity of the stations that are to be deployed, their utilization, the electricity price. If they don't know that for the state, there are default values in the tool, and they will come up automatically, or the user can override them. All of these inputs go into the calculations.
As I said before, when deploying EV chargers, we consider not just the actual cost of the charger itself, but all of that equipment onsite in terms of the manufacturing, the transporting of that equipment to the site, its installation, and for pre-construction and construction at the site. We also consider station operation and revenue. We'll go into a little bit more of those categories in a moment. So, the expenditures that are required to get that station up and running, and to operate it for an assumed ten-year life, are translated into dollar flows among industries using the U.S. Department of Commerce's RIMS2 input-output model. Now, I'll turn the mic over to Yue, and he'll talk a little bit more about the methodology that underlies the tools. Yue?
Yue: Thanks, Marianne. So, input-output modeling is kind of what this tool is based off of. So, I guess it's useful to kind of know what an input-output model is instead of just considering it to be a black box. But basically, what it does is it is a model of the entire economy of some geography, be at state level of nationwide or a census region. It basically says that the output – so in terms of goods and services of any industry – is an input to other industries as well as to itself. So, an industry's output then depends on the input requirements of all other industries. The outputs of other industries are the inputs of that first industry.
So, you can kind of think of it as just a massive series of feedback effects or a system of equations, even, where what one industry produces goes into another industry and itself. By being able to kind of account for all those flows, you're able to estimate the effects of anything on the economy. So, in this case, anything is the deployment and operations of EVSE equipment. Next slide, please.
These are just some definitions that are used within the tool. The first big one is sort of a job. So, when we say jobs, we mean one year of work, full time, or part time, for one person. This isn't exactly the same as employment since we aren't able to capture whether or not it's a full- or part-time employment. What we call supply chain jobs are jobs are those that are directly involved in the production, shipping, installation, construction, and operations of stations as well as supply inputs for those activities. This includes both the direct or indirect jobs. So, kind of going back to that infographic earlier, this would be the jobs that are in the middle circle.
The induced jobs are jobs that are created by re-spending of wages or income by the supply-chain job-holders. So, going back to the infographic. It would be the last circle. So, an easy way to kind of think about this is a supply chain job, for instance, would be like a construction worker that was involved in the construction of an EVSE station, whereas the induced job would be something like – when that construction worker goes out and spends money at a restaurant or something, an induced job would be maybe a waiter or waitress kind of job.
Other outputs of the model include earnings and economic output. Earnings are wages or proprietor's income while economic output is the gross economic activity associated with the expenditure flows across the economy. So, something like a GDP would be a measure of an economic output.
So, how we calculate everything is based off of economic multipliers that are derived from the Department of Commerce to an input/output model. So, the multipliers are embedded within the tool, and that's how we are able to calculate the number of jobs or earnings or economic output that are created due to the deployment operations of EV infrastructure. Next slide, please.
So, station development, we include the up-front permitting that would be required to have a station as well as engineering and design. We also include site prep and construction. This includes trenching and boring as well. Electrical infrastructure and make ready costs are also some of the dollar flows that we account for. Then project contingency, as well. Project contingency is primarily civil and electrical infrastructure costs. Like Marianne said, we also include the costs of the uninstalled equipment.
So, these costs, the tool considers cable cooling, charger, conduit and cables, on-site electrical storage if it's a DCFC site, switchgear, and transformers again if it's a large sort of capacity required kind of thing, additional transformers outside of what the utility might provide is included within the tool if it fits your scenario. Then, safety and traffic control which also includes any kind of ADA requirements for a site, as well as miscellaneous equipment costs. So, an example of miscellaneous equipment would be any sort of mounting hardware you would need for a level two or whatever charger. As far as development goes, we also consider the cost of shipping on these various pieces to a site, and then the install costs.
The JOB EVSE tool also looks at the operations and maintenance of a station up to, like Marianne said, ten years. So, some of the expenditures in that phase of a station website would include the electricity costs to station, admin and maintenance expenses, any sort of warranties that were purchased for the equipment as well as data and networking fees. There may be cases where the station brings in revenue as well. So, for instance, if you go to charge your EV, you might be at the charger for 20 or 30 minutes or more. So, if the station is located at a retail location, any sort of retail sales that are incurred while you're waiting for your car to be charged would be captured by the model. Additionally, if the charger has those LED screens that like gas station fuel pumps have, that might bring in advertising revenue for the site host. So, that's another revenue stream that we capture. Finally, if there are any access fees associated with using the station, that also gets counted into station operations revenue. So, we can kind of figure out the number of jobs that are created due to those revenue streams.
Then, the tool also looks at the local shares. So, this kind of represents the amount of money that is spent locally, either for any of the processes that have to go on into making the station become reality. So, like permitting or engineering design, those types of things. Then, also, there are local shares that users can put in either a percentage for the production shipping and installation for each piece of equipment.
So, for instance, if everything – if you're looking at a nationwide type of scenario and you know for a fact that everything is produced in the U.S., the local share would be 100 percent. On the other hand, if you're looking at something like a state level type of analysis and nothing is produced locally, then the local share would be a zero percent for that type of scenario. So, these are just some examples of how users can modify the default values to use the tool to better suit their needs. Next slide, please.
So, Marianne is going to talk about the default data.
Marianne: Sorry, I was muted. Yes, I – thank you, Yue. So, in developing the default data for the tool, we talked with a number of people, we reviewed a lot of data sources and documents. This slide shows some of the sources that were reviewed and the folks that we spoke with. We spoke with installers and project developers that were providers, several utilities, equipment manufacturers. We reviewed site plans for projects that we were able to obtain site plans for, very detailed site plans which had information not on the capacities of the various pieces of equipment and their costs.
We also had a JOBS EV working group composed of Clean Cities Coalitions that met on a monthly basis while we were developing the tool. I won't go through the various names of the coalitions. I put them down here in terms of their acronyms or initials, but you can see that we had maybe ten or so coalitions that we worked with. We thank all of them for their help.
We also reviewed documents by ICCT. That's the International Council for Clean Transportation, by the Rocky Mountain Institute, Idaho National Lab, NREL, ICF, the Fuels Institute, and Atlas Public Policy. So, using all of that information, we were able to develop a number of default values and putting them into the supply chain. This image here shows the supply chain as we envision it. So, basically, moving from the power plant to the actual site. You have a number of different pieces of infrastructure that electricity is flowing through and that in a very large-scale scenario might be impacted. However, we're looking at much smaller, much more constrained scenarios of EV charging and EV charging equipment. So, we focused only on those two hexagons on the far right, the site itself, charging station, and the transformer and panel and other equipment that would be – and obviously the charger – that would be located on the site.
Moving upstream, we want to get further back into that supply chain, looking at local distribution and substation and medium voltage distribution. But right now, that's really not impacted. There's enough extra capacity in the electricity infrastructure to accommodate the levels that we're looking at right now. In the future, that could change. But right now, there is enough capacity and JOBS EVSE focuses only on the two hexagons on the far right. We consider that portion of the supply chain as well as the recurring expenditures that you mentioned for things like electricity, network and data fees, revenues, warrantees, O&M, administrative expenses, and access fees.
Now this next slide goes into a little bit more detail on those two hexagons on the far right. So, from the service drop, there could be an extra transformer where you're talking about higher-power charging or a lot of chargers. In many cases, that wouldn't be necessary. And the meter, obviously. Then, to the right of the meter, you have the equipment that would pretty much always be required for a scenario. You have a panel. You have conduit and writing. You have a charger, and some of the smaller, less-expensive pieces of equipment that might be required onsite like traffic control bollards, things like that.
So, basically, JOBS EVSE looks at the expenditures – [dogs barking] I apologize for my dogs. It looks at the expenditures to the far right of the meter – the panel, the conduit and wiring, and the charger, and the various ancillary equipment that are required. As we indicate in that asterisk, we also include things as you mentioned, engineering and design, installation, permitting, and things like that.
We envision generic stations. The next few slides are just going to show the kinds of station that we envision. They're not actually in the tool but that's what we envision in the default. So, for example, a level-two station, we do include a transformer upgrade. In most cases, that's not required. The user would simply zero that out. However, we put it in there simply if it is required at a particular level for a scenario. The user will be able to invoke the default. But most cases, a transformer would not be needed. The transformer upgrade is assumed – we're assuming at 90 percent of charger maximum power at the station. That's basically the number of charges times their kilowatt capacity and utilization rates.
So, basically, in the default, we assume three chargers, two port or cords per charger. We don't assume future proofing, although that might be in a particular case. User input would be required for that. For trenching and boring, from the cabinet or perhaps the transformer to the chargers, we assume 75 feet at $80.00 per foot, and that can be overridden by the user. If they more specific project-level data, then we encourage them to override these assumptions. We do assume that there's compliance with the Americans for Disabilities Act, which would include retractable cords, signage, bollards and curbs and some striping and sidewalks. Those are in the miscellaneous expenses.
This next slide shows the same type of generic 50-kilowatt station. Here, again, we include a transformer for the user's information. On most cases, it might would not be required. Again, it depends upon the numbers of chargers. Here, we have for 50 kilowatts. If you had a lot of them, you might need an extra transformer. We assumed, again, three chargers: two ports or cords per charger. Same default number for the trenching and boring to the cabinet. Again, ADA compliance. Again, as I said with the level-two chargers, user is encouraged to put in their own information if they have better information particularly if they have documents pertaining to the actual installation.
For the 150-kilowatt station, a little bit different. This image comes from an INL report done for DOE. Here, we assume somewhat heftier components, a transformer upgrade, though, again, we have at 90 percent of maximum capacity. Three chargers, again. But here, only one port per charger. But again, the user can override that. They can assume two. Same numbers for trenching and boring. Then, again, ADA compliance.
This image is of the actual tool, the start page. The user would select whether to just look at station development which is basically just the expenses involved in putting that station into operation. All of the permitting, the installation of the equipment, the purchasing of the equipment, the shipping, and also anything involved in planning the station. They can click on that first box. If they're only interested in stations and operation, if perhaps the stations have already been built and they're just looking at the impacts and continuing them, their operation, then they would click on that second button. If they want both, then they would click on both of them. Then, the second – the next two pages they would go to would be the station development inputs and the stations and operation inputs.
I'm going to turn the mic over to Yue to go into a bit more detail on these. This is, again, what the tool looks like and what the user would be entering values for in order to look at the impacts of a particular scenario. Yue will be putting in – will be showing you the inputs for a particular scenario that we've run, which is for the Virginia Electrification Plan. Yue?
Yue: Thanks, Marianne. So, this is a scenario we did for Virginia Clean Cities. Kind of sort of like a case study kind of thing. They wanted for us to map out the economic impacts of a large-scale electrification plan for the State of Virginia over the course of many, many years. So, what the tool does is – it can only account for a ten-year period. This limitation is largely just due to the underlying IO model and the multipliers that we're using. Next slide, please.
So, they wanted to have 4 million level-2 home chargers by 2040, 1 million workplace level-2 chargers by 2040, 580,000 public level-2 chargers, and 65,000 public DCFC chargers. So, that was kind of the task that we were given. Because of the, like I said, sort of the limitations of the underlying input/output model, we only could do up to 2030. So, we're only looking at a third of these values, as seen in the table below. We assume that there are going to be two ports or plugs per charger. So, two vehicles could be charged at a time by a single charger. We assume that for every work or public station, there were going to be two chargers. Like I said, a third of these sort of target values for up to 2030.
Additionally, we assumed that there would be onsite electrical storage for the DCFC chargers, but the idea that maybe site operators will want to help – not have to deal with on-demand charging fees. So, an onsite battery could help offsite those fees. We also assume that all components are made in the U.S., but not within Virginia. So, these are just kind of the simplifying assumptions we used to calculate the jobs impacts because we didn't really know sort of any more specifics for the plan. Next slide, please.
These two pie charts are based off of mostly the default values included within the tool. So, when you put it in values or use default values, the tool will automatically create these pie charts that kind of split up the costs at a station level for any scenario that you give it. So, to the left, you'll see the level-two station cost breakdowns, and then to the right, you'll see the DCFC station cost breakdowns. It's worth noting that the cost of the equipment versus the cost of doing stuff with the equipment are roughly even. So, it's about a 50/50 split. If you add up all the equipment costs and then you add up all the engineering design, permitting, construction, installation, shipping. Those two costs are roughly the same. Next slide, please.
So, for public stations, we assumed that there would be some monthly revenues associated with operating them. These are just the default values that are provided within the tool. We assumed that, with two chargers or four vehicles being charged at a time, there would be about $1,200.00 of retail sales, two ad buys. So, at $700.00 each would be $1,400.00 a month. We also assumed that there weren't going to be any access fees.
Expenses, the electricity cost depends on the region of analysis or the geography. We used sort of the Virginia average value we found, based on literature, which was $0.33 per kilowatt hour. We also assumed that there was a monthly administration expense of $10.00, maintenance would be $5.00, warranty would be $10.00, and then $30.00 for data networking fees per month. Again, these are default values. But if you do know more about the scenario that you have in mind, we encourage users to change the values as needed. Yeah. Then the graph on the right was just showing the estimated – just the expenditures. Can you go back a slide, please? Sorry.
So, for Virginia, the results are as shown. Again, just kind of a reminder. These jobs include supply chain jobs as well as induced jobs. So, the total employment by charger type and location – home, workplace, public, or public DCFC 50-kilowatt are shown. Then the bottom graph shows the development versus operations jobs.
So, we estimated roughly 14,000 jobs a year will occur due to station development. We also estimated about point-two jobs per year per cumulative charger and operation. If this number seems a little bit low, a lot of it is due to sort of the at-home stations kind of being the majority of chargers that were being deployed under this plan. So, obviously, you don't have retail revenue with a charger at home.
All we calculated roughly just under – sorry – 274,000 to 291,000 jobs would be created over the course of 10 years and roughly 40,000 jobs created within just 2030. We also ran this analysis using – because we weren't really told what type of DCFC chargers were going to be used at public locations, we also ran a similar analysis using the ACFC 150-kilowatt chargers, and I can provide those results for you offline if you're interested. Next slide, please.
So, next steps. We're continuing with some sensitivity analysis within sort of this JOBS EVSE tool. We want to be able to better be able to tell what is sort of driving the job growth, both at the sort of the station development phase as well as the stations operation phase. So, that's kind of an ongoing effort. We're going to, like Marianne said, also, going to actually post this tool somewhere online, and then the tutorial that was created for using the tool as well as any presentation materials will be posted to this Argonne JOBS models website with a link to it from the AFDC "tools" page. We'll let you know when that happens.
Looking ahead for next year, we're working on JOBS EVSE 1.1, which is going to include higher power chargers, like DCFC 350, for instance, as well as heterogeneous high-charger types. So, right now, what the tools does is, if you have an EVSE hub in mind with multiple level-twos and DCFC 50s or 150s or whatnot, the way the tool works right now is you would have to run the tool several times to be able to account for those various types of chargers. So, the goal with version 1.1 is that instead of having to do multiple tool runs and then doing some backend addition calculations, you'd be able to just run the tool once and it would spit out the right results. We would like to have more granular defaults as well. So, this is just sort of a hunt for data on our end. Then we'd like to also account for additional revenue sources. So, for instance, if there are any sort of parking fees or vehicle leasing rental-type fees, TNC hubs, that type of stuff.
The other thing they're working on is – well, we're calling JOBS EV 1.0. So, this is kind of where the change in the name of these two tools is coming from. JOBS EVSE is looking strictly at the infrastructure deployment that would be necessary to support electric vehicles. So, charging equipment, primarily. Whereas JOBS EV would look at actual electric vehicle manufacturing, the battery supply chain, that type of stuff. Then we're also, in addition to all that, looking at upgrading sort of the software platform so that it's a little more flexible to use.
So, thank you for listening. This is our contact information. Questions?
Sandra: Great. Thank you, Marianne, and Yue. Appreciate that presentation. If anyone has a question, feel free to type it into the chat. We have a little bit of time here, so we'd love to hear from you all. Thank you all for your attention. Marianne, and Yue, I guess there was a question about if – why ChargePoint wasn't noted or listed.
Marianne: Well, we have been in contact. It's not listed because we didn't actually use – well, I could've – we did actually – we did use one thing from ChargePoint. I probably should revise that. We did not talk with them specifically on this project. We've talked with them on other projects. I can certainly update that slide because I'm just thinking that we did use some data from another project which was helpful. But as far as talking with them specifically, there were a number of changes in personnel while we were developing the tool. It became difficult to actually get the data that we needed for this tool. We were not able to talk to the technical people. It was more the administrative side. But I'm happy to talk to Bob Spatz. Thank you.
Sandra: Great. Thank you, Marianne. So, feel free to input questions. I'm not seeing any questions. But I have a couple questions here. Are there other geographies that can be modeled in the tool?
Marianne: Yes. Actually, the multipliers that are in the tool are specific to the 50 States, the District of Columbia, the nine census regions, and the U.S. as a whole. However, the Department of Commerce does develop multipliers that are consistent with the RIMS2 Model at the county level for every county in the country. So, if we request those multipliers, they can be obtained for an individual county or for any contiguous groups of counties or groups of states. So, any contiguous geography can be modeled, but it's not in the version that will be posted online. We would have to do a separate offline analysis containing those multipliers. But if anybody's interested in that, we'd be happy to talk to you.
Sandra: Great. Thank you. So, we have a couple questions coming in here. So, that's great. So, first question here. "Can you explain the methodology behind choosing the number of home chargers, work chargers, et cetera, and was that based upon any particular emissions goals?"
Marianne: I can chime in unless Yue wants to. We were given those numbers. The Virginia Department of Energy was in the process of developing their EV charging strategy goals, their plan. Virginia Clean Cities gave us those numbers and asked us to run them in the model. So, I can refer you to make – I guess Alleyn Harned would be the person to talk to. He may be able to refer you to how those numbers were developed.
Yue: Yeah, just to add on a little bit. I think the premise of those numbers, by year 2040, was for full electrification of Virginia's sort of transportation sector. So, those were the numbers we got. Then we just divided by three in order to be able to model sort of what could be built within the time limitations of the tool. So, 2030.
Sandra: All right. Thank you. So, next question here. Will the NAICS codes used to define the various associated industries be defined as part of the appendices of the project?
Yue: Yeah. So, the index codes that we used, the NAICS codes, they are listed in various parts of the tool as well as, yeah, in sort of the documentation of the tool. You'll be able to see which six-digit codes correspond to which industries and how it kind of gets tied in.
Sandra: Okay, great. Thank you, Yue.
Marianne: Yeah, can I add-in also?
Sandra: Of course.
Marianne: Yes, actually, the – we didn't really talk too much about the documentation. There are separate tabs that provide documentation. They're actually part of the tool. As you said, they do indicate the NAICS codes. Also, there is a tutorial that Yue has recorded to actually walk people through the tool showing you how to use it. The reason why we didn't do that today was we were afraid that we would connectivity issues and going back and forth that we would have a problem. It just wasn't worth it. But all of that will be posted on the website and, as I said, along with more information.
Sandra: Okay, great. Next question here. "So, I think maybe a point of clarification. I may have misunderstood, but will there be another tool that will model economic impacts of EV manufacturing and supply chain, EV 1.0? It was mentioned on that last slide."
Marianne: Yue, do you want to do that one or do you want me to?
Yue: Yeah, there will be another tool. It will be a separate thing. It'll be – the methodology will be the same. It'll still rely on the Department of Commerce's RIMS2 Input/Output Model, but it will focus solely on EV manufacturing and supply chain. We're going to call it EV 1.0 just to kind of disambiguate these two tools. The tool that we shared today will be called JOBS EVSE for electrical supply equipment, and then the second tool will be looking at cars and trucks and those types of things. It'll be JOBS EV.
Marianne: Right. I should also mention that it will include not just the manufacturing but also the distribution and retail. So, the selling, if you will, of the vehicles. We've done other work, in the past, looking at fuel cell vehicles and we've found that actually the retail sale, the dealers and the distribution of the vehicles, those also generate jobs. In the same type of holistic approach, we will be considering that as well in the JOBS EV tool. Is there a timeframe for its release? It hasn't been developed yet, so I can't give you a timeframe. DOE has authorized us to begin work. It's an FY22 activity. Stay tuned.
Sandra: Great. Thank you, both. So, we still have a little bit of time. So, feel free to continue inputting questions. I have another one here, Marianne, Yue. Which industries are most likely to be affected by deploying EVSE?
Marianne: Yue? Should I take that or do you want to?
Yue: It's all yours.
Marianne: Okay. Actually, we have done a little bit of playing with the tool. As you mentioned, we will be doing more sensitivity analysis. But one thing that we have found is that a lot of the impact occurs on the revenue side. If stations are generating revenue, typically electricity, retail sales, advertising – we mentioned marketing is something that we're going to get into – that really has a surprising impact. We hadn't anticipated that. So, that is one area that we are going to be looking at a lot more. Another thing is access fees. In the defaults, we've only – we basically had assumed no access fees, but that also may be another big piece.
One thing I should mention, which we really haven't focused on, is the numbers that the tool produces are gross numbers. They're gross jobs. We don't account for job losses that might occur as people switch away from gasoline vehicles. In some cases, it would be basically a wash. If you have charging stations at gasoline stations and they're basically doing the same kinds of things, then there really wouldn't be too much impact. Similarly, if you're producing electric vehicles instead of gasoline vehicles, there would be an impact in terms of specific components and where they come from, but as far as when you're shipping them or retailing them, there's not likely to be as much of an impact.
So, a lot of that will – it depends as you're looking at these particular sectors and zeroing in on those results for those sectors. We haven't really shown any of that today, but there are these more discreet impacts that the tool enables you to focus on and do more detail analysis on and looking at why they change. That's what we're going to be doing, also, with the sensitivity analysis, looking at how sensitive these impacts are to different assumptions and how they might change based upon how we modify the different scenarios. Sandra, thank you for putting the link to the tools and how that's accessed from the FDC "tools" page.
Sandra: Oh, sure.
Marianne: Also, as far as this presentation, making this presentation available, we have the same problem that we have with this presentation as we have with the tool itself in that we've gotten approval from DOE yesterday to actually release the tool, but now we have to then get it posted and get it cleared at the Argonne site, and we have a problem with the shutdown, which will happen on Thursday. So, I cannot promise that this presentation or the tool or anything is going to be posted before the holidays, but we're running into this wall, if you will, of the holidays. But we will definitely jump on it in the new year. This material from today as well as I mentioned a tutorial that Yue recorded a little while back on how to use the JOBS tool, and all of the – the model itself, and other presentations that we've done, all of that will be posted on JOBS models, which is the link that Sandra has supplied. That page has to be edited to add the JOBS EVSE to it and make sure that the text is revised to reflect that.
Sandra: Okay, great. So, I did get another question here. Will there be a quick non-Excel version with graphic outputs similar to AFLEET or other tools?
Marianne: Well, the Excel output does produce some of the figures that we showed. It does produce the pie charts of operating expenses, numbers of stations in operation, by year. It basically takes the inputs and converts them into chart form. It also produces outputs on numbers of jobs, earnings, and economic output for the entire run. That's in the Excel tool. In the platform, the upgraded platform that Yue mentioned, that will produce the same type of output, but it will enable us to do it across a combined scenario, if you will. So, it will produce that type of output for numbers of level-two, at-home, and public locations, work locations, and for DCFC in different configurations. So, that's where it becomes more complicated. We're not certain that the Excel platform will work as desired. That's why we're talking about a different platform.
Sandra: Okay, great. Thank you for that. I'm not seeing any other questions, but we do have a few minutes. I don't know. Marianne, or Yue, did you have anything else you wanted to add or maybe expand on from your presentation since we have a few minutes?
Marianne: I think the main thing had to do with when the tool would be available. As I said, we're still working through those things. We have cleared the legal issues in terms of copyright and opensource license. It is opensourced. There's no issues. It's just a legal hurdle, and DOE approval. It's just a question of getting through the holidays and getting it posted. Again, I apologize.
Sandra: Not a problem. Yue, did you have anything else you wanted to add?
Yue: No. Just thanks, everyone, for coming and listening to us.
Marianne: I'll second that as well. Thank you, everybody. I realize this is a difficult time of the year. Everyone's running in circles trying to get things done before the holidays. We do appreciate you taking the time to be with us this afternoon. Stay tuned. We will be, like I said, launching more tools and doing more in this space. It's a very exciting time to be in this space. Thank you.
Sandra: Wonderful. Well, thank – yeah, thank you. Thank you, Marianne, and Yue. Thank you for your presentation today. Thank you to everyone for being here with us, and happy holidays. We'll send an email once everything launches in the new year to everyone that was listening in today to point you to where you can find the tools as well as the videos and everything else associated with it once it is released. So, thank you, again, and have a wonderful holiday. This concludes today's webinar. Thank you, all.
Marianne: Thank you. Bye-bye.
Yue: Thank you. Bye-bye.