Appendix C
Modeling a Hydrogen Transition

Joan Ogden, Marc Melaina, and Chris Yang


A goal of the scenario analysis is to estimate the investments needed to bring hydrogen fuel cell vehicles to life-cycle cost competitiveness with a reference gasoline vehicle. To aid this process, researchers at the University of California, Davis (UC Davis,) developed a relative simple, flexible, transparent EXCEL model called STM (Simple Transition Model) that the committee used to look at how hydrogen transition costs depend on key variables.

Inputs to the model include

  • Market penetration rate of hydrogen fuel cell vehicles (HFCVs)

  • Cost of HFCVs versus cumulative production, time (learning rate, scale factors for manufacturing HFCVs)

  • HFCV performance over time (fuel economy)

  • Cost and performance of baseline reference vehicle (gasoline internal combustion engine vehicle [ICEV]) over time

  • Oil (gasoline) price over time

  • Cost of hydrogen ($/kg) over scale, time

    • Costs and performance for H2 infrastructure components are included in H2A and UC Davis models

  • Source of hydrogen over time and greenhouse gas (GHG) emission factors

Outputs include

  • Scenario description

  • “Breakeven” year, when HFCVs become competitive with reference ICEVs on a life-cycle cost basis (cost of the vehicle plus the discounted cost of the H2 to fuel it)

  • Transition costs (How much does it cost to get to break even?)

    • Incremental vehicle costs

    • Infrastructure capital costs

    • Policy costs (subsidies, carbon tax, etc.)

  • Primary energy use over time

  • GHG emissions over time

Figures C.1(a) and C.1(b) show the program’s logic and flow, which involves the following five steps.

Step 1:
Estimating Infrastructure and Delivered Hydrogen Costs (Figure C.2)

  • For each year from 2005 to 2050, the infrastructure needed to serve that H2 demand is designed using the UC Davis or H2A models.

  • The initial H2 infrastructure is built up in “lighthouse” cities (similar to the Department of Energy [DOE] transition analysis).

  • The capital cost for infrastructure is estimated at each time.

  • The feedstock and other operating costs are estimated as well.

  • This allows determination of the delivered H2 cost ($/kg) for each year.

Step 2:
Cash Flow Analysis: Estimating the Life-cycle Cost (LCC) of Transportation

The life-cycle cost of transportation is estimated for each year (i indicates one of these years) from 2005 to 2050 (LCC [i]) for HFCVs compared to what would have been paid for the same number of reference gasoline vehicles.

NOTE: Joan Ogden is a member of the Committee on Assessment of Resource Needs for Fuel Cell and Hydrogen Technologies. Marc Melaina and Chris Yang worked at the University of California, Davis.



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appendix c modeling a hydrogen Transition Joan Ogden, Marc Melaina, and Chris yang A goal of the scenario analysis is to estimate the invest- —Incremental vehicle costs ments needed to bring hydrogen fuel cell vehicles to life- —Infrastructure capital costs cycle cost competitiveness with a reference gasoline vehicle. —Policy costs (subsidies, carbon tax, etc.) To aid this process, researchers at the University of Califor- • Primary energy use over time nia, Davis (UC Davis,) developed a relative simple, flexible, • GHG emissions over time transparent EXCEL model called STM (Simple Transition Model) that the committee used to look at how hydrogen Figures C.1(a) and C.1(b) show the program’s logic and transition costs depend on key variables. flow, which involves the following five steps. Inputs to the model include step 1: estimating infrastructure and delivered hydrogen • Market penetration rate of hydrogen fuel cell vehicles costs (Figure c.2) (HFCVs) • Cost of HFCVs versus cumulative production, time • For each year from 2005 to 2050, the infrastructure (learning rate, scale factors for manufacturing HFCVs) needed to serve that H2 demand is designed using the UC • HFCV performance over time (fuel economy) Davis or H2A models. • Cost and performance of baseline reference vehicle • The initial H2 infrastructure is built up in “lighthouse” (gasoline internal combustion engine vehicle [ICEV]) over cities (similar to the Department of Energy [DOE] transition time analysis). • Oil (gasoline) price over time • The capital cost for infrastructure is estimated at each • Cost of hydrogen ($/kg) over scale, time time. —Costs and performance for H2 infrastructure compo- • The feedstock and other operating costs are estimated nents are included in H2A and UC Davis models as well. • Source of hydrogen over time and greenhouse gas • This allows determination of the delivered H2 cost (GHG) emission factors ($/kg) for each year. Outputs include step 2: cash Flow analysis: estimating the life-cycle cost (lcc) of Transportation • Scenario description • “Breakeven” year, when HFCVs become competitive The life-cycle cost of transportation is estimated for each with reference ICEVs on a life-cycle cost basis (cost of the year (i indicates one of these years) from 2005 to 2050 (LCC [i]) for HFCVs compared to what would have been paid for vehicle plus the discounted cost of the H2 to fuel it) • Transition costs (How much does it cost to get to break the same number of reference gasoline vehicles. even?) NOTE: Joan Ogden is a member of the Committee on Assessment of Resource Needs for Fuel Cell and Hydrogen Technologies. Marc Melaina and Chris Yang worked at the University of California, Davis. 

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 TRANSITIONS TO ALTERNATIVE TRANSPORTATION TECHNOLOGIES—A FOCUS ON HyDROGEN FIGURE C.1(a) Flow diagram of simple transition model (STM) (part 1). HFCVs come down via learning, under some conditions HFCV LCC (i) ($/yr) = number of new HFCVs (in year i) ∆LCC (i) becomes positive. × vehicle first cost (in that year) ($/yr) + Σ [H2 fuel cost When the costs are equal, the annual cash flow ∆LCC (i) = (i) + O&M cost (i) + policy cost (i)] × total number of 0. The year that this happens is termed the “LCC breakeven” HFCVs in the fleet (i) year. Presumably, at this point the net cost to the economy is the same for FCVs and gasoline reference vehicles. Reference vehicle LCC (i) ($/yr) = # number of new HFCVs (i) × reference vehicle first cost (i) ($/yr) + Σ [gasoline fuel cost (i) + O&M cost (i) + policy cost (i)] × step 3: estimating Transition costs total number of FCVs in the fleet (i) Add up incremental HFCV vehicle and fuel costs to get to ∆LCC (i) = reference vehicle LCC (i) ($/yr) − LCC HFCV the LCC breakeven year (compared to the gasoline reference vehicle). These are transition or “buydown” costs. (i) ($/yr) = number of new HFCVs (i) × [reference vehicle first cost (i) − HFCV first cost (i) ($/yr)] + Σ [gasoline Buydown cost ($) = Σ ∆LCC (i) i = 1 to the breakeven fuel cost (i) − H2 fuel cost (i) + ∆policy cost (i)] × total year number of HFCVs in the fleet (i) The difference in life-cycle costs ∆LCC at each year (cash Initially, the first cost of the HFCV will be much higher than that of the reference vehicle. This cost falls over time flow) represents the funding that would have to be supplied (with increased learning and mass production of HFCVs), so each year to make the cost of HFCVs equivalent to that of that eventually, under some conditions ∆LCC (i) = 0, and the the reference gasoline vehicles. Initially, HFCVs cost a lot negative cash flow “bottoms out.” more than gasoline vehicles (but the number of new HFCVs is low) so the cash flow is negative. Eventually as costs for

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 APPENDIX C FIGURE C.1(b) Flow diagram of simple transition model (part 2), oil and greenhouse gas emissions saved. 0.24 8 Los Angeles, California New York, New York 0.22 Miami, Florida Denver, Colorado Levelized cost of H 2 ($/kWh, $2005) 7 Washington, DC Dallas, Texas Levelized cost of H2 ($/kg, $2005) 0.20 Albuquerque, New Mexico Atlanta, Georgia 0.18 6 0.16 5 0.14 0.12 4 0.10 3 0.08 0.06 2 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 Year FIGURE C.2 Delivered hydrogen costs in selected cities. FigureAppC-2.eps

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 TRANSITIONS TO ALTERNATIVE TRANSPORTATION TECHNOLOGIES—A FOCUS ON HyDROGEN step 5: estimating savings in oil Use and GhG emissions Consider incremental costs for vehicles and H 2 fuel (Figures c.3 and c.4) separately: • Using a vehicle stock model, keep track of the number Incremental vehicle cost ($) = Σ Number of new HFCVs of HFCVs of each model year in the fleet. (i) × [first cost HFCV (i) – first cost reference vehicle (i)], • Each year, the H2 vehicles displace a certain amount i = 1 to the breakeven year of gasoline use (the gasoline that would have been used by reference gasoline cars, if the HFCVs had not been Incremental fuel cost ($) = number of HFCVs in the fleet introduced). (i) × [fuel cost HFCV (i) – fuel cost reference vehicle (i)], • The HFCVs have certain well-to-wheels GHG emis- i = 1 to the breakeven year sions, depending on the assumed H2 supply options (which are estimated separately and input to the scenario). These Adding up the infrastructure capital costs to the breakeven emissions are lower than those of the reference gasoline year gives an indication of cumulative costs to energy compa- vehicle, and GHG emission reductions can be estimated for nies. These are the cumulative costs that would be borne by each year. automakers or energy companies to reach breakeven. step 4: estimating Policy costs • Vehicle subsidy is subtracted from vehicle first cost. 140 • Fuel subsidy is subtracted from fuel cost. 120 Billion gallons per year • Carbon tax is added to operating costs. 100 80 Cost for each vehicle becomes: 60 Case 1 (H2 Success) Case 2 (ICEV Eff) LCC ($) = (vehicle first cost ($) − vehicle subsidy ($)) 40 Case 3 (Biofuels) + Σ [(fuel costs − fuel subsidy) + O&M costs + carbon 20 emissions × carbon tax)] 0 2000 2010 2020 2030 2040 2050 The cost of policies can be estimated over time, either to Year the breakeven year or to some set “policy horizon.” FIGURE C.3 Oil saved per year with different scenarios compared The cost of a direct subsidy to energy providers (e.g., pay to the reference case. FigureAppC-3.eps for 50 percent of cost of first stations) could be calculated in an analogous fashion. 1600 Million tonnes CO2 eq/yr 1400 1200 Case 1 (H2 Success) 1000 800 Case 2 (ICEV Eff) 600 400 Case 3 (Biofuels) 200 0 2000 2010 2020 2030 2040 2050 Year FIGURE C.4 Greenhouse gas emissions avoided compared to the reference case. FigureAppC-4.eps