This is the text version of the video Systems Analysis Overview at the DOE Hydrogen Program 2022 Annual Merit Review and Peer Evaluation Meeting.
Neha Rustagi, Hydrogen and Fuel Cell Technologies Office: So I'll be providing an overview of the systems analysis program. So within systems analysis, we fund projects that inform the DOE's RD&D strategies. And so we start with foundational models that characterize the cost of individual technologies so, for example, the Autonomie model, which is used by hundreds of stakeholders throughout the U.S. to characterize the cost and performance of vehicles with specific designs of hydrogen storage or batteries or light-weighting. The H2A modeling suite, which depicts the cost and performance of hydrogen production and infrastructure.
And then these underlying models inform our projections of supply chain dynamics, so, for example, which regions of the country production is most likely to be deployed, where we're most likely to see pipelines or liquefaction or tube trailers, and then also which markets are most likely to adopt hydrogen relative to other decarbonization options. So that ultimately informs our RD&D strategy and then the deployments that result generate data that we use to recalibrate our foundational work to ensure that it reflects the state of the art within industry.
So this past year our key focus has been identifying scenarios of hydrogen demand in support of a net zero economy in 2050. So we've been working in collaboration with many offices across DOE that have been looking at specific segments of the economy so, for example, in collaboration with our vehicles office to understand what the market potential for hydrogen is in transportation. And you can see it's quite a broad range, and it's very dependent on the cost of hydrogen fuel.
We've been working with our bioenergy office to better understand what the demand potential is for hydrogen in biofuels and synthetic fuels, which could particularly be required to decarbonize the aviation sector in support of administration goals to decarbonize jet fuel by 2050. We've been working with our advanced manufacturing office, so they've been doing both analysis and stakeholder outreach to understand the potential for hydrogen, CCUS, electrification, energy efficiency, and other options to decarbonize industry.
And then also offices across DOE have been working to understand what a clean grid could look like in 2050 if we were to electrify end uses to enable a net zero economy and then also how that grid would vary depending on how interconnected it was and then also the availability of technology like CCS for hydrogen or direct air capture. So we see, again, a broad range of potential for hydrogen in energy storage for the grid accounting for all those different sensitivities.
So in parallel with this scenario now, we've also been funding the development of user-friendly tools that folks outside in the stakeholder community at large can use to depict the cost and emissions associated with particular deployments that they're interested in. And then we've been working with the international community to develop mutually agreed-upon methods of life cycle analysis that can inform things like global trade.
So our budget annually is stable at $3 million per year. And most of that is spent on cost and emissions analysis of specific hydrogen pathways, and then also scenario analysis to understand what markets hydrogen has the strongest value proposition in. And that typically informs the types of tools that I was previously describing.
Two of the tools that have been a priority for us this year have been PNNL's Global Change Analysis Model, or GCAM, and the National Energy Modeling System, or NEMS. GCAM and NEMS are both unique in that they're market models that can compete different energy technologies. So hydrogen, electrification, low carbon fuels, conventional fossil fuels, to characterize which of those are most likely to be adopted in the future energy system. They can integrate different aspects of the energy system so, for example, if we were to decarbonize the grid, what would that mean for the cost of hydrogen from electrolysis? And then what would that mean for hydrogen adoption in industry as an example? This is really valuable because these models can be used then to depict what a net zero economy would optimally look like and how sensitive it is to particular variables and then also the impact that policies can have on deployment.
So GCAM and NEMS to date haven't included many different hydrogen production or infrastructure technologies or end uses of hydrogen across industry and then even parts of transportation. So over the course of the past year, we've been funding updates to both of these models to depict hydrogen production from electrolysis, SMR, coal gasification with CCS, biomass, several different methods of hydrogen delivery including tube trailers, liquefaction, pipelines, and then also hydrogen use in a wide range of sectors across industry and transportation and the grid.
We've also been working across EERE on regional deployment scenarios so, for example, with our bioenergy office and several other EERE offices to understand the potential for regional biofuel production from biomass and what that would mean for regional demand for hydrogen. And then also looking, for example, with the STEPS consortium led by UC Davis to understand what the potential for hydrogen could be specifically in the California region. And these types of regional analyses are really valuable because they can typically characterize potential with a greater fidelity in the near term than something at a national scale.
So underneath all of these market models, we have the underlying cost and emissions analysis. So most of our emissions analysis is funded at Argonne National Lab, and this year our focus has been largely on industry. So as we know, the majority of hydrogen production in the U.S. today is used for petroleum refining. So if we were to displace that natural gas reforming with the use of clean hydrogen, we would reduce emissions from the refining process by about 12%.
Another sector where there's growing interest in end use of hydrogen is steelmaking. So steelmaking accounts for about 8% of global CO2 emissions. And in the U.S. about a third of steelmaking uses iron refining typically using coke feedstock. So instead of using coke, which is produced from coal, if you were to use clean hydrogen, you could reduce emissions associated with iron refining by up to 70%. Ammonia and methanol are two sectors that rely more heavily on the use of hydrogen so displacing conventional SMR with clean hydrogen would reduce emissions by up to 90%. And then in the trucking sector, largely because of the efficiency of fuel cells, you could reduce emissions by up to 90% if you displace diesel.
So one of the factors we want to better understand with future work is hydrogen blending. This is particularly of interest for heat and power in industry. So today about a third of the emissions from industry come from process heating. So that includes temperatures down to 150°C, which can be electrified, all the way up to over 1,100°C where you would probably need to use a renewable fuel like clean hydrogen. So better understanding and quantifying what the demand for hydrogen could be in those sectors is one of our priorities to better understand the potential for hydrogen energy storage and then also looking at how clean hydrogen could be used in emerging applications like, for example, plastics and specialty chemicals.
So one of the sectors where we have the highest fidelity market models for hydrogen technologies is actually transportation. Over the course of the past several years, our office and the vehicles office and other offices within DOE have been directing the development of a model at NREL called TEMPO. So TEMPO is a model that depicts how new powertrains could be adopted by different segments of the transportation sector depending on the cost of fuel, the cost of the vehicle, expected payback period, as well as changes to driver behavior over time.
So, for example, from now until 2050 demand for shipping via truck is expected to increase by about 40%. And that's just based on economic growth that would increase the demand for shipment. So TEMPO captures variables like that as well as many of the ones that I just mentioned. And if we look at scenarios where our R&D targets for hydrogen fuel storage and fuel cells are met and batteries advance aligned with R&D success funded by our vehicles office, we see that by 2050 10% to 14% of trucks could end up using hydrogen in fuel cells.
This analysis and other prior work we funded has shown that one of the most attractive segments of the trucking sector for hydrogen is long-haul, heavy-duty trucks, which are harder to electrify. And that segment is actually also responsible for a disproportionate share of emissions from the trucking sector. So to put that in perspective, about 9% of trucks in the U.S. go over 250 miles and are also heavy duty. So these long-haul, heavy-duty trucks only account for 9% of vehicle stock. But they actually represent over half of energy consumption from the trucking space because they just travel more miles every year and because they're less efficient than light- and medium-duty vehicles. So targeted deployments of clean powertrains within that sector can really accelerate decarbonization of the transportation space.
But in addition to modeling like TEMPO, we're also funding exploratory work trying to better understand the potential for hydrogen in parcel delivery trucks with autonomous capabilities that would drive up energy consumption within that sector. And then also work with our vehicles office to better understand cradle-to-grave emissions of medium- and heavy-duty vehicles including emissions associated with manufacturing components like fuel cells, storage, batteries, and then the chassis of the vehicle itself, as well as use of the clean fuel.
Most of our emissions analysis, as I mentioned earlier, is done at Argonne using the GREET model. So GREET has been developed over the course of multiple decades, and currently it's used by over 40,000 stakeholders worldwide. This past year one of our priorities with GREET has been funding development of a version of it where users can change core assumptions to depict the emissions of their particular bespoke deployment, so a version where you could easily change, for example, the energy consumption of your electrolyzer, the makeup of your grid, fugitive emissions, length of a particular pipeline that deploys feedstock to your deployment. And so that user-friendly version of GREET is currently near finalization and should be released within the next few months. And then also the GREET team has been expanding their model to reflect global pathways for different fuels and different end uses in collaboration with the International Energy Agency so that the model can be used to depict global decarbonization scenarios.
In parallel we've also been funding a version of the H2A tool that can characterize costs of hydrogen production. So H2A has also been used by DOE over the course of decades, and it has very bottoms-up process modeling underneath it that depicts the design of, for example, electrolyzers, SMR, biomass, coal gasification, CCS. So this H2A Lite tool that we've been funding similarly will allow a user to specify what the cost is of their electrolyzer stack, of their system, what their operating costs are, what the cost of electricity is within their particular deployment. And the model will complete a discounted cash flow analysis that outputs what the cash flow is over the course of a particular period and then also the levelized cost of hydrogen in that scenario.
And then as Sunita was mentioning earlier, last year we released the Hydrogen Business Case Prize Competition. So this was a competition where we were soliciting teams to develop user-friendly tools that characterize regional value propositions for hydrogen accounting for financial viability as well as sustainability metrics. Most of the teams that we had apply were actually teams of students, and those teams got access to mentors from across industry and the national labs for the course of six months. So we're very grateful for the folks who volunteered as mentors. Many of those mentors are also offering the teams in first and second place internships over the course of the summer. And then the teams in first through fourth place additionally got cash prizes. And so these teams will be presenting on Wednesday, and so we really encourage you to check out their presentations.
Much of our work that's in the life cycle analysis space has been done in close collaboration with the international community. So a good example would be the International Partnership for Hydrogen in the Economy or IPHE, which comprises 22 countries and the European Commission. And a key taskforce within IPHE is the Hydrogen Production Analysis Taskforce. So the H2PA team has been developing methods of conducting life cycle analysis that were mutually agreed upon between all members of the taskforce covering, for example, feedstock extraction like natural gas drilling, delivery of the feedstock to the point of use as well as use of the feedstock at the point of production. And so last year the team issued this white paper that describes guidance around producing hydrogen from electrolysis, SMR, as well as coal. And then this year since then, the team's been working on new production pathways like autothermal reforming and biomass use and then also hydrogen carriers like ammonia and LOHC, hydrogen liquefaction and then hydrogen transport. And several of these trackers are expected to be published over the course of the coming year.
As Jesse also mentioned, we've been working in close collaboration with the European Commission to identify knowledge gaps associated with indirect climate impacts of hydrogen, and we're also working to better quantify those impacts in collaboration with NOAA. And then once we have a better handle on these values, we plan to update our standard models on GREET to represent these indirect effects.
And then we've been working in close collaboration with offices throughout DOE in the space of energy storage and the grid. So, for example, quantifying the costs of hydrogen energy storage relative to other energy storage mechanisms, characterizing what grid integrated electrolysis could cost today and then also in a future clean grid, and then also the development of modeling tools that characterize the value of integrating hydrogen with, for example, baseload nuclear power plant direct integration with renewables and then also integration with fossil generators. And several of these tools have been funded through the Grid Modernization Consortium and are expected to be available over the course of the next several months.
As I've mentioned, our work is done in close collaboration with industry, academia, and then offices throughout DOE and then other agencies as well. Many of our projects that inform deployments are through CRADAs. And so folks that are interested in using the national labs' expertise or their tools to characterize a particular deployment, I really encourage you to reach out to the labs. In the past, these tools have been used to characterize really bespoke conditions like, for example, hydrogen production at a particular nuclear power plant or at a particular renewable generator in a region of interest.
We've also been working across DOE on RD&D roadmaps and across the international community and then also using informal partnerships like, for example, the Stanford Energy Modeling Forum where assumptions and analyses can be discussed in advance of their publication.
Our work is funded across five national labs and two universities. Most of the projects I described have been funded in collaboration with other EERE offices or with the Office of Fossil Energy and Carbon Management and the Office of Nuclear Energy. And commonly our work is reviewed and informed by public-private partnerships like the 21st Century Truck Partnership or the US DRIVE Partnership, which encompasses energy companies as well as vehicle manufacturers across sectors.
As we go into FY23, our key priorities include updating key models like, for example, GCAM and NEMS, which I was describing earlier, better understanding the potential for hydrogen in liquid fuels production like biofuels and synthetic fuels, better understanding sustainability impacts of hydrogen, so, for example, regional water use to help optimize deployments. And then also we've been funding analysis of manufacturing of hydrogen components like, for example, electrolyzers and fuel cells, in coordination with other DOE offices that are also funding analysis of manufacturing of power generation.
With that, I really want to thank the great team behind all of this work, so my colleagues Marc Melaina, senior analyst on our team; Masha Koleva, who's on detail to our office from NREL; and then our newest member Tomas Green, who's a fellow on our team. They really manage and direct a lot of this work. And several of our projects will also be presented on Wednesday, so I encourage you to come check out the presentations to hear directly from the PIs. And with that, I thank you for your time.