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DOE Launches JOBS and economic impacts of Fuel Cells (JOBS FC) Analysis Model

Below is the text version of the webinar titled, "DOE Launches JOBS and Economic Impacts of Fuel Cells (JOBS FC) Analysis Model," originally presented on May 22, 2012. In addition to this text version of the audio, you can access the presentation slides.

Allison Aman:
All right, thanks for joining today's webinar hosted by the DOE. Just a few housekeeping items: as the webinar is going on, you are able to submit questions via the chat function on Go To Meeting. Everyone is on mute so that is the only way that you are able to submit questions. So please submit questions as they are coming up. We will have a Q&A at the end of the presentation to cover most of those questions. Any questions we do not get to, Mary Anne and her team will do their best to follow up with those questions via email after the webinar.

Just as another quick remember our next webinar will be on June 19, so please check back to the website for details on that webinar. Everything is being recorded today and we will have the PowerPoint and recording of this webinar on our website in the coming weeks. So look out for that as well.

Today we have Fred Joseck from the Department of Energy. He's the lead technology analyst and he is going to introduce today's speaker Marianne. Fred?

Fred Joseck:
Thank you Allison. Good morning and good afternoon everybody. Thank you for participating in the webinar. I would like to introduce Marianne Mintz and her team from RCF who have done an outstanding job in terms of developing this jobs model and they also worked on the previous DOE employment study in 2008. So they come with the background in terms of analyzing job estimation and employment information. Particularly Marianne, she specializes in transportation energy forecasting and policy analysis for Argonne National Laboratory's Center for Transportation Research. She has over 30 years experience in transportation and energy analysis and has authored over 100 publications in the field. Her current work centers on infrastructure requirements for alternative fuel pathways, hydrogen delivery, employment and economic impacts of fuel cells in natural gas vehicles, fuel transitions and energy and greenhouse gas emissions of renewable natural gas bio methane from landfills and anaerobic digestion. She holds a master's degree from UCLA and has completed postgraduate work at the University of Illinois at Chicago.

Also I would like to thank Kristen Nawoj and Allison for setting up the webinar. Allison?

Allison Aman:
Thank you Fred. Marianne the floor is yours.

Marianne Mintz:
Thank you. Good morning or afternoon, whichever the case may be. Just a little structure with the talk today—I am going to be speaking first. I am Marianne Mintz at Argonne National Labs and I will be providing a brief overview of the tool, the JOBS FC version 1, and I will talk a little bit about the why of the tool and the how of the tool, how it works, key concepts and the approach.

Then I will pass the wand over to Eric Stewart at RCF and he will provide a demonstration of how the tool works and go through a few different cases. Then I will talk a little bit about next steps and how we might follow up with additional questions. Then Catherine Mertes, whose name is also on this mission slide, she will coordinate the Q&A after the presentation.

I would just like to comment a little bit upon the fact that this is a joint effort between Argonne National Lab and RCF Economic & Financial Consulting and that it was funded by DOE's EERE Fuel Cell Technologies Program as Fred indicated. I would like to thank them for their support and for the close attention that they have given to this project. In addition to Fred, we have another DOE individual who has been involved, Greg Kleen. We have had bi-weekly meetings for several months and they have provided a lot of very close consultation and advice in the course of developing the model.

As far as why we have developed the model, basically it is to provide a means for calculating employment and other economic implications of fuel cell investments. It translates investments and expenditures into changes in direct, indirect and induced jobs and economic activity and I will say more about that in a moment.

It's also intended to meet DOE and stakeholder needs to measure the economic impact of fuel cell technology deployment by region and by application. This is essential information for local, state, and national policy decisions and for public and private investment decisions as well as for program planning and analysis. Lastly, another reason why the project was undertaken was to collaborate with stakeholders to create a user-friendly tool with the functionality that they need to acquire and review input data and to validate results.

We have come a long way and we're now at the point where the tool has been launched; it's available on the Argonne website and today we'll be explaining a little bit more about how you might use it. Next slide please.

[Next slide]

The model uses the input/output approach to replicate deployment of fuel cells. It is a user-friendly spreadsheet tool written in Microsoft Excel and it calculates direct, indirect, and induced job creation, wages and sales, resulting from fuel cell production, installation, operation, and fueling. As you see in the graphic, when modeling essentially a flow of dollars in the economy they flow both down from raw materials through the suppliers and the production of the items to the consumer and that is in the form of value added. They also flow up through that supply chain in the form of the various inputs that need to be procured.

You could basically think about this as five supply chains: we have one for fuel cell production; we have one for the fuel supply for the fuel cells; another one for the fueling infrastructure; another one for fuel cell O&M; and lastly one for fueling infrastructure O&M. We are tracking those dollars as they flow through the economy.

If you look at the second bullet, we use the regional input/output modeling system, RIMS II, which is an input/output model developed by the U.S. Department of Commerce and Bureau of Economic Analysis. That model has multipliers that capture the effect of the expenditures as they are made through that supply chain.

A key concept that I would like to emphasize here is that third bullet: that we model gross and net jobs created by three technologies, three applications, and multiple fuel cell capacities, as shown in the table below it. Gross minus displaced equals net jobs. So if you think about putting in a fuel cell, it is going to displace some other technology. If we talk about the difference between the gross jobs and displaced jobs, that is what we call net jobs. I mention this again later, but the net jobs are calculated at the national level and I will explain that in a moment.

If we look at the table these are the default values for the different applications that are in the current version of the tool, JOBS FC 1.0. We have two different categories of forklift, the class I and II forklifts, which are the larger ones, and the class III forklifts, which are the smaller forklifts. We also can look at backup power. To date, we have been looking solely at cell towers but the model itself can be configured to look at any type of backup power within a certain size range for the fuel cells. Those numbers in the table correspond to unit capacity in kilowatts in the default case. We also can look at prime power with combined heat and power in the default case although the user can also run a case without combined heat and power.

Lastly, I'd just like direct your attention to the box on the lower right hand corner that jobs are created at each stage in the supply chain that is shown above it, as well as from the direct and indirect. The direct jobs are the jobs that are actually directly involved in the supply chain; indirect are the jobs that are upstream; also there is re-spending of the dollars to the economy, and that is what we call induced jobs. That's another important concept that we will be talking a little bit about, the fact that not only are jobs created by the actual operation and deployment of fuel cells, but also by the re-spending of the dollars that goes to the employees that are working on fuel cells-related jobs; those dollars are re-spent in the economy when they take their family out to dinner or purchase something in the retail environment. Those dollars create what we call induced jobs. Next slide, please.

[Next slide]

Another way of looking at the supply chain is in this graphic, which shows in a little bit more detail the kinds of things that are modeled in the tool. As you see, the fuel cell cost breakdown, that center box, this is showing low temperature PEM fuel cells. Those dollars can be allocated to the manufacturing, to shipping, to installation, and in manufacturing we have production costs, we also have facility costs, we have testing, and we have all of the various components that go into the fuel cells that must be produced, both stack and balance of plant. All of those dollars are allocated then up the supply chain and that is essentially what the model does for us.

There are a couple of images that I also am showing on the slide. Can you show the end of the screen? We have an image of a facility for manufacturing fuel cells, it is a Ballard plant up in Canada. It shows the type of equipment that we are talking about and that we model in the tool, the type of facility, and the actual construction of the manufacturing plant. When we are talking about a scenario where enough fuel cells are deployed, we want to include a manufacturing facility as well as the actual production of a fuel cell because at a certain point we have to actually build more facilities.

The image on the upper left hand corner is some of the infrastructure that is involved in fueling the fuel cells. This is from a Fed Ex facility warehouse. I believe this is in Missouri. It shows a couple of the dispensers for refueling forklifts and we can see that there is also some overhead equipment shown there. There is quite a bit of infrastructure involved; we do model the tool particularly for the forklift application.

On the lower left-hand corner, we see an image of a warehouse in South Carolina. BMW has a—there is a little circle. Eric, can you click on the circle? If you see on the lower right-hand corner of that slide, you see the actual infrastructure that was installed to fuel the forklifts for that large warehousing facility. There is quite a bit of infrastructure, but it is also part of a large facility as well. We do model the infrastructure that's required for fueling the forklifts. Next, slide please.

[Next slide]

I would like to introduce a couple of additional concepts. The model tracks expenditures for different geographies. The user selects what geography they want to look at, whether it is a state, any one of the 50 states, or whether it is a region. The tool is set up to look at nine different Census regions. I would just like to mention that Alaska and Hawaii, shown on the lower left-hand portion of the screen, those are in the Pacific region. The user can select those regions or they can do an analysis for the U.S. as a whole.

Jobs occur where expenditures occur. So if a fuel cell is being manufactured domestically that creates jobs in manufacturing. If it's being manufactured abroad, or what we call imported from somewhere else, then those jobs for the manufacturing don't occur but there are jobs that do occur for installation and for operation. The point is that imports and exports also create jobs. A little bit differently, but they do create jobs. Most jobs, obviously, are created when the fuel cell is produced and installed and operated domestically.

One other point—see those arrows from imports and exports. For example, if an analyst was looking at the State of Nevada, imports from California would be considered an import when you are only looking at the State of California. Imports from Japan would also be an import. So it really depends upon the geography that you are looking at, whether or not an import is from overseas or just from another state or another region.

Also, if you look at the curved arrows on the right, if a fuel cell was produced in Ohio and installed in Pennsylvania, it would be an export from Ohio and an import to Pennsylvania. However, for the U.S. as a whole, it is just a domestically produced and installed fuel cell.

The other point I wanted to make was the net effects, the last bullet. That net effects excludes jobs that are displaced by fuel cells unless the fuel cells displaced imports. So for example, if you are replacing battery forklifts with fuel cell forklifts and the batteries are produced in Germany, those displaced jobs associated with battery production do not count in this model because they are overseas. We are only interested in domestic jobs. So there is a functionality in the tool to estimate only the domestic jobs that are displaced, and because that data tends not be available on anything other than the national level, we can only do that in the national analysis. Therefore, the user cannot choose to conduct a net analysis on a state or regional level because that data is simply not available. We do not know, for example, if a battery that is being displaced was produced or manufactured in Pennsylvania or Ohio or Arkansas; all you know is that it is domestic versus imported. Next, slide please.

[Next slide]

Now, to actually run the model, there are a few obvious things that I just wanted to mention. You need to register and you need to download the model from the website, which is indicated on this slide. In case you have not noticed this, you do not want to add "www"; just the http://. It does not work with the www. Also you need Excel 2010 in order to get the full functionality of the tool. You may be able to view some of the screens, but the model won't work in older versions of Excel. You also need to review the copyright and the information screens when you first open the tool; that will really help you. Also you might want to look at the user's guide, which is also posted on that website.

Once you have registered and downloaded the tool, you need to open the model and select the application from the four different screens I've listed: forklift INPUTS, backup INPUTS, prime INPUTS, or PEM facility construction INPUTS. Eric will go over those in more detail in a moment. So once you have selected the application, then you select your geography of interest, and as I said a moment ago, you can either do a gross or a net analysis, but the net analysis is only available from a national level. That question may come up if you are choosing to do a net analysis.

Then you define a scenario of interest by inputting the—Eric will go into those in a moment—required user inputs or you can go further inputting optional or advanced inputs. The model will work with just the required user inputs and it will just run with the defaults that are preloaded; the user does not put anything else in there. Then you view your results in the form of charts and tables.

With that, I will pass the baton over to Eric and he will demonstrate a few different pieces. Eric?

[Next slide]

Eric Stewart:
Hello, my name is Eric Stewart at RCF Economic & Financial Consulting.

[Next slide]

[Next slide]

When you open up the tool like Marianne just described, the first page that is visible is the information page. Much of this information is repetitive of what Marianne just went over.

[Next slide]

The first section shows the model version, the project team, system requirements, and some suggestions about how to enter values in addition to the available modules.

[Next slide]

There is some cell color-coding information here that just kind of guides the user, which might be helpful to look at. Yellow typically implies that the step has not been completed yet and the user is encouraged to enter more information. There is also some more information here on the input/output model that is used, which relates to multipliers. The available regions, as Marianne mentioned, there's the U.S. region, which is the contiguous 48 states, as well as the nine Census regions, and then all the states. The economic impacts are employment earnings and output, and I should mention that employment, at least in this model, is capturing both full and part-time jobs and they are in job years. The dollars, all the expenditures or expenses that are being modeled, are in 2010 dollars and so any user inputs would also need to be specified in 2010 dollars. Then finally, Marianne's contact information is here.

[Next slide]

The layout, from a sheet standpoint, there is the information sheet and there is also a copyright sheet.

[Next slide]

Then, for each of the modules, there is an input sheet, which I will go into in a second.

[Next slide]

For charts, some default charts are created, but those can be edited or changed by the user. In addition, there are detailed tables for each of the modules and of course the four modules are forklifts, backup power, prime power, facility construction; and then finally we have a market forecast tab, which I'll mention how that comes into play in a moment.

[Next slide]

I am going to go through a couple examples, some in more detail than others. The first one that I am going to start with is just a national forklift scenario. In all these modules and all the input sheets, the first steps are very similar, and so this will be applicable to whatever module the user is interested in.

The first step is of course to choose the region that the user is interested in analyzing. For this example, I will just choose the U.S. region from the dropdown. The second step, and an important one as Marianne mentioned several times, is the distinction between a gross and net analysis. For this example, I will choose a net analysis, which is available for the national region only.

Step two in all of these modules has some particularly important operation or related variables that have significant impacts on price or other default expenditure calculation. For forklifts, an important variable that we have in step two is the size of the fuel cell. So for class I and II forklifts, we have ten-kilowatt units and for class III forklifts, we have two-kilowatt units.

[Next slide]

In step three, the user has a choice of entering the number of units as a pure number, just a raw number, or as a percentage of the market forecast, which is representing not a forecasted fuel cell market, but the overall potential market for fuel cells. In this example, I will just choose the number of units manufactured. To keep things simple, we won't worry about exports right now for this U.S. analysis so we can skip right to step 3C. This is simply where we enter the number of units. I have pre-entered an increasing amount of units from 1,500 for each class in 2015 to 4,000 for each class in 2020.

[Next slide]

And that's basically it. At that point, all the other values have defaults, which will yield the results that it will show you, so at this point the user can simply go to the chart sheet…

[Next slide]

… and begin to look at the results.

[Next slide]

On the chart sheet and the table sheet, the top sections show the key scenario assumption that the user has either explicitly entered or that is assumed from the default value, and those are shown in the top table here.

[Next slide]

The second table shows the list of charts that are available and then where those charts exist to just kind of guide the user. The first charts that are available for all these modules include a graph of the estimated retail price or the user-specified retail price; I'll show that in a second in addition to the manufacturing cost for the two different technologies. It also shows the number of units manufactured in the region, the number of units installed in the region, and either the user-specified or the estimated number of sites where the forklifts are actually installed.

[Next slide]

That brings us to the actual economic impacts charts, which show—for this graph we're looking at employment in job years. The different colors represent the different categories of expenditures, so the forklift power source, because we did a net analysis would be the comparison between the fuel cell manufacturing and the domestic battery manufacturing. We also have the installation, the fuel or electricity and also the maintenance of the fuel cell and the related infrastructure. The black line is showing the net domestic job years for each year for the scenario that has been specified.

There are also charts that show the earnings with the same types of categories and economic output and then there are some simpler charts which just show the overall totals showing the net economic impacts in black, the gross economic impacts in blue and then the displaced economic impacts in gray, and that would be related to battery.

[Next slide]

I am going to jump back to the forklift inputs to show you what some of the optional or advanced user input fields are. The first one, and a very important one, is the retail price and manufacturing cost assumptions. The default values are dynamic; they are calculated based upon the number of units that are entered, but the user can also specify any values for any of the years that they have different information on.

Step 5 represents the expenditures associated with shipping, so the per-unit costs for shipping the fuel cells, and then step six is trying to capture the expenditures for the installation of the on-site hydrogen fueling infrastructure. So the first part of the step is a representation of the average dollars per site for installation, which includes expenses like site design, construction, the hydrogen storage tank and then the actual fueling infrastructure equipment.

The second part of this step, step 6B, calculates the number of sites that are actually installed based upon the scenario that has been specified. So the user can accept the defaults, which assume 60 units per site on average, or they can specify the number of units per site, or they are able to specify the number of sites that the forklifts are actually being installed at, which might be useful for some users who are modeling a smaller number of installations.

Step 7 represents the fueling expenditures, so we have the price of hydrogen as well as the cost of hydrogen production. In this step is where many of our operations variables come in. There is hydrogen consumption as well as the operating hours per shift, shifts per day, days per week, and so on. Those ultimately yield an annual hydrogen expense.

Step 8 is capturing two types of maintenance, the fuel cell maintenance for both classes on a dollars per unit per year basis and then also the maintenance of the onsite hydrogen fueling infrastructure and that's on a dollars per site per year basis.

Because we did a net analysis, step 9, which allows the user to enter pre-existing sites or pre-existing fuel cells and capture the associated economic impacts with the operation of those units and sites, is not available. However, what is available is the variables associated with the displaced technology. Marianne mentioned we are trying to capture domestic economic impact, specifically employment, and to do that what we primarily need to know is what percentage of the units—the batteries in this case, that are being used in the United States or in the region that we have chosen— are actually manufactured in the U.S.? That is what step 10A captures.

The remaining steps or the remaining sections of step 10 are just a mirror of the earlier fuel cell-related expenditures. We have the forklift battery retail prices, the installation expenses, the battery charging or the electricity expenditures, battery maintenance expenses and then the infrastructure maintenance.

One note—with the battery infrastructure, the assumption is that the users of these fuel cells are choosing between replacing an old battery and a new fuel cell. One consequence of that is the assumption that the battery infrastructure already exists, and that is why these default values are at zero.

[Recording ends abruptly]