The characterizations of the production and delivery technologies are based on a review of the public literature, drawing from it the best available information about capital and operating costs, energy and feedstock consumption, and environmental emissions. Some new analysis will be performed. In most cases, information is supported by a process simulation model such as ASPEN Plus.

Information about each analysis case is summarized in a standardized H2A spreadsheet tool that documents the:

• Original source(s) of all the data (i.e., report title, authors, etc.)
• Basic process information (feedstock and energy inputs, size of plant, co-products produced, etc.)
• Process flowsheet and stream summary (flowrate, temperature, pressure, composition of each stream)
• Technology performance assumptions (e.g., process efficiency and hydrogen product conditions)
• Economic assumptions (after tax internal rate of return, depreciation schedule, plant lifetime, income tax rate, capacity factor, etc.)
• Calculation of the discounted cash flow (the calculation procedure is built into the standardized spreadsheet so that all technologies use the same methodology)
• Results (plant-gate hydrogen selling price and cost contributions in $/kg H2, operating efficiency, total fuel and feedstock consumption, and emissions)
• Sensitivity of the results to assumptions (e.g., feedstock cost, co-product selling price, capital cost, operating costs, internal rate of return, conversion efficiencies, etc.)
• Quantification of the level of uncertainty in the analysis.

The spreadsheet facilitates the explanation of any differences between the final results of this effort and previous published results and supports transparency of analysis assumptions and methods.

Where possible, technologies are characterized relative to current technology (2005), potential advanced technology (2010-2020), and potential longer term technology (2020-2030). Advanced and longer-term technology case studies will be posted at a later date.

These analyses are done on a well-to-gate basis for central-plant technologies and a well-to-pump basis for forecourt technologies. In other words, the performance characteristics of the technology (cost, energy consumption, emissions) include all upstream activities associated with the plant. This is straightforward relative to costs (because the cost of upstream activities are included in the price of inputs to the plant). It is less straightforward for energy use, efficiency, and emissions. To help assess the energy and environmental impacts of the upstream activities, the H2A effort uses a model developed by Argonne National Laboratory called GREET, which contains a large database of environmental and energy data for characterizing the total lifecycle energy and emissions of various transportation processes.

Economic Assumptions Used in the Analysis

The results of technology lifecycle costing exercises depend on various financial assumptions. The H2A team has developed a set of base case assumptions. In addition, the analysts will vary those assumptions to test the sensitivity of the costs to a few of the most critical assumptions.

Peer-Review and Industry Input

The H2A Group produces its products in a fully transparent way. Toward that goal, the analyses are well documented and available to the public. Analysts include detailed references or the basis for each value of every cell in the Summary Workbook Spreadsheets.

Interim results are also peer-reviewed. The H2A Group works with experts from industry to ensure that the assumptions and estimation procedures reflect standard industry practice and to provide advice on the technology characterizations. For each technology listed in Exhibit 2, the H2A analysts work closely with experts from at least two industrial companies as appropriate.

Getting Help with the H2A Analysis Tools

Users guides are available for both the H2A production and delivery models.

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H2A Analysis Models: Basic Model Architecture

The Figure below describes the basic architecture for the H2A Model Analysis tools. All of these model tools are Microsoft Excel-based with multiple tabs. Each has the same Feedstock and Utility Prices and Physical Property Data tabs. These allow users to draw from these for a common set of Feedstock and Utility Prices and Physical Property Data in their analyses.

H2A Central and Distributed Production Models

These models have Title, Description, Process Flow Sheet, and Stream Summary tabs to record useful and descriptive information about the analysis in a convenient and consistent manner. The Performance Input, Financial Inputs, Cost Input, and Replacement Capital Tabs contain the inputs that drive the calculated results. The analysis results are presented in tabular and graphical forms on the results tabs. These models also provide tabs to utilize for sensitivity analyses plotted as tornado charts.

These models automatically do a rigorous discounted cash flow analysis over the analysis time period based on the specified economic assumptions to calculate the cost of hydrogen produced over the analysis time with the after tax internal rate of return on capital investment.

H2A Delivery Components Model

This model works in a similar manner to the H2A Production Models. In this case there is a separate tab for each delivery component in the model. Each tab has a section on it for the user to provide inputs pertaining to performance, financial inputs, and cost inputs. The results are presented in tabular form as the cost contribution of that delivery component to the cost of the hydrogen in terms of $/kg of hydrogen directly on each component tab. The cost analysis is done based on the Capital Recovery Factor (CRF) method rather than a rigorous Discounted Cash Flow method. Although the CRF method is not quite as rigorous, the results are comparable when the same economic parameters are used.

Feedstock and Utility Prices Tab

The Feedstock and Utility Prices tab can be used in the H2A modeling tools for feedstock and utility costs throughout the analysis period. If the user would prefer to use their own estimations of feedstock and utility prices, they can enter them directly.

Projections for the following feedstocks and utilities were derived from the Annual Energy Outlook 2005 (AEO) Reference Case and High A Case developed by the U.S. Department of Energy's Energy Information Administration (EIA).

• Commercial natural gas
• Industrial natural gas
• Electric utility natural gas
• Commercial electricity
• Industrial electricity
• Electric utility steam coal
• Diesel fuel
• Gasoline
• Biomass

EIA makes projections for every year between 2000 and 2025. For the period between 2025 and 2035, the values were simply extrapolated using the 2015-2025 growth rate.

For the period between 2035 and 2070, for all feedstocks and utilities listed above except for biomass, the prices were extrapolated using price projections from the MiniCAM model developed by Pacific Northwest National Laboratory (PNNL).¹

Note that EIA does not provide the biomass prices in their published AEO reports, but the projected biomass prices were obtained by special request. The biomass projected prices were based on a review of literature.

Physical Property Data Tab

Several energy sources are being considered as feedstocks and energy for the production and delivery of hydrogen. In order to provide consistent information for H2A production and delivery analyses for physical properties and carbon and other emissions, it was decided to base this information on the GREET model developed at Argonne National Laboratory.

Although feedstock properties can be different for the same feedstock from different production or consumption sites, it is intended here that national average properties be summarized for H2A. Data for the following feedstocks are provided on the H2A Physical Property Tab.

1. Biomass — switchgrass
2. Biomass — poplar
3. Coal
4. Natural gas
5. Ethanol
6. Methanol
7. Gasoline (without oxygenate)
8. Conventional diesel
9. Low-sulfur diesel
10. Gaseous hydrogen
11. Liquid hydrogen

Among the 11 feedstocks and fuels, the first six are feedstocks for hydrogen production either at central plants (in the cases of switchgrass, poplar, coal, and natural gas) or at forecourt (in the cases of natural gas, ethanol, and methanol). Gasoline and diesel are presented for calculating energy and emissions of well-to-pump activities in the H2A models. Gaseous and liquid hydrogen are presented for conversion between feedstocks and hydrogen.

For information see the H2A Users Guides.

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DOE H2A Standard Economic Assumptions

DOE funded the development of H2A Analysis tools in order to address the need for consistent and transparent hydrogen production and delivery analyses. To allow for consistent and comparable results across technology options, it is necessary to utilize a common set of economic assumptions and approaches. The following set of key economic parameters was selected by the H2A analysts to utilize within their analyses. These were discussed with the Industry Collaborators who participated in the H2A effort. The user of the H2A analysis model tools is free to change these parameters to any value they chose for their own purposes.

• Reference year dollars: 2016
• Debt versus equity financing: 40% equity
• After tax internal rate of return: 8% real
• Inflation rate: 1.9%
• Effective total tax rate: 25.7%
• Depreciation period and schedule: MACRS
  • Central plant depreciation period: 20 yrs.
  • Distributed depreciation period: 7 yrs.
  • Delivery components: typically 5 years with a few exceptions
• Economic analysis period: Central plant production — 40yrs., Distributed production — 20 yrs., Delivery Components Model — 20 yrs.
• Decommissioning costs are assumed equal to salvage value

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¹MiniCAM models the global energy and industrial system, including land use, in an economically consistent global framework. MiniCAM is referred to as a partial equilibrium model in that it explicitly models specific markets and solves for equilibrium prices only in its areas of focus: energy, agriculture, and other land uses, and emissions. The supply and demand behaviors for all of these markets are modeled as a function of market prices, technology characteristics, and demand sector preferences. Market prices, including feedbacks between energy markets, are adjusted until supply and demand for each market good are equal. At this equilibrium set of prices, production levels, demand, and market penetration are mutually consistent. For example, gas production will increase with a rise in gas price, which drives a decrease in gas demand. In equilibrium, these market clearing prices (e.g., the prices of gas, coal, electricity, etc.) are by definition internally consistent with all other prices. And in parallel, all supply and demand behavior is consistent with assumptions about the key model parameters and drivers, including the following: (1) technology characteristics (from production to end-use), (2) fossil fuel resource bases (cost-graded resources of coal, oil, and natural gas); (3) renewable and land resources (hydroelectric potential, cropland, etc.); (4) population and economic growth (drivers of demand growth); (5) policies (about energy, emissions, etc.). The MiniCAM is based on three end-use sectors (buildings, industry, transportation) and a range of energy supply sectors, including fossil-fuels, biomass (traditional biomass such as use of wood for heat, and modern biomass that can be used as a fuel for electricity production or as a feedstock for bio-fuels or hydrogen production), electricity, hydrogen, and synthetic fuels. For electricity generation, the model's technological detail covers generation from coal, oil, natural gas, biomass, hydroelectric power, fuel cells, nuclear, wind, solar photovoltaics, electricity storage (e.g., coupled with production of electricity using solar and wind generation), and exotic technologies such as space solar and fusion.