NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Hawaii Hydrogen Initiative (H2I) Financial Scenario Analysis

Michael Penev, Marc Melaina, Aaron Brooker 2013 DOE Hydrogen and Fuel Cells Program Review National Renewable Energy Laboratory May 14, 2013

This presentation does not contain any proprietary, confidential, or otherwise restricted information

Project ID AN042

Overview

National Renewable Energy Laboratory Innovation for Our Energy Future 2

Timeline Project start date: Q1, FY12 Project end date: Q1, FY13 Percent complete: 100%

Barriers 4.5.A: Future Market Behavior 4.5.B: Stove-piped/Siloed Analytical Capability 4.5.D: Insufficient Suite of Models and Tools 4.5.E: Unplanned Studies and Analysis

Budget Total project funding: $230k 100% DOE-funded FY2012: $200k FY2013: $30k

Partners Louis Berger Group [H2I - lead] General Motors [FCEV deployment lead] U.C. Irvine [station placement analysis] Hawaii Gas [gas producer & supplier] Wellford Energy [financial modeling guidance]

3

Project Overview Approach

Analysis Framework

H2A design parameters AEO gasoline prices HSCC* fueling station costs IEA global FCEV adoption NRC cost of FCEVs

Models & Tools SERA Financial ADOPT sales model

Studies & Analysis

H2I Financial Scenario Analysis: Station clusters & rollout, finances and incentive analysis

Outputs & Deliverables

Scenario analysis for H2I Report of findings Improved understanding of market adoption, infrastructure phases, and incentive requirements for FCEV and station deployment.

National Labs None

H2I Analysis Team: General Motors

University of Irvine Hawaii Gas

H2I, NREL, FCT Office, CaFCP, EIN

& External Reviews

Effects of Technology Cost Parameters on Hydrogen Pathway Succession

*HSCC = Hydrogen Station Cost Calculator, NREL Publication Pending

State & Local Officials

Station Equipment OEMs

Relevance: Financial Tool for Stakeholders

National Renewable Energy Laboratory Innovation for Our Energy Future 4

Financial Scenario Analysis

Automotive OEMs

Gas Suppliers

Financing Entities

Model Refinement

DOE Management

External Reporting

Analysis incorporates interests of many stakeholders for station cluster financial analysis

Relevance: Objectives

National Renewable Energy Laboratory Innovation for Our Energy Future 5

Analysis helps to identify opportunities and constraints for equity, debt, and public financing

Produce financial projection scenarios - Consider vehicle adoption rates - Determine infrastructure support requirements - Evaluate full range of expenses - Apply competitive revenue ceiling - Perform accounting cycle analysis - Perform multi-year financing projections Provide Hawaii Hydrogen Initiative (H2I) team with scenario analysis - Communicate risk and sensitivities - Facilitate strategic planning - Evaluate incentive requirements

Promotional introduction Private vehicle adoption Market competition Fleet vehicles Fuel efficiency Driving habits

Station coverage Station size distribution Station types

Vehicle Sales

Fueling Stations

Production sources Delivery methods Supply chain costing

Production & Delivery

Multi-source financing Incentive requirements Risk analysis

Financing & Incentives

National Renewable Energy Laboratory Innovation for Our Energy Future 6

Approach: Model Structure Overall model strategy evaluates station supply

chain with vehicle sales as an input.

FCEV Sales Profile Daily H2 Demand Demand Assignment

to Stations

Initial Coverage + Long term

Market Modeling

Station by Station Annual Cash Flow H2 Resources

Resource Availability

Annual Cost of H2 To Station Owners

Distribution Pathways

Station Costs

Workshop & Model Inputs

Annual Cap Cost & Maintenance

Financing Scenarios

Refueling Industry Annual Cash Flow

∑

Hydrogen Price & Revenue Setting

Competitive Transportation Pricing

¢/mile

ADOPT FCEV sales projections based on: • Station coverage • Fueling costs • Vehicle prices • Vehicle size • Vehicle acceleration

National Renewable Energy Laboratory Innovation for Our Energy Future 7

Approach: Model Structure Model is integrated with vehicle choice modeling

Automotive Deployment Options Projection Tool (ADOPT model)

ADOPT Modeling

Vehicle Performance Projections & Driving Habits

Promotional Seeding & Long-Term

Adoption Model Projections

Model structure quantifies how the revenue shortfall can be filled with multiple types of incentives.

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ions Required revenue

Sales revenue

Expe

nses

and

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nues

Revenues & Required Revenue

1.52.4

3.34.2

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ions Total production

incentives

Total capitalincentives

Ince

ntiv

es

Incentives to Close Revenue Shortfall

Incentives were split in two components: Production incentive

• Incentivizes good station placement & efficient operation

• Closes operating expense revenue gap

Capital incentive

• Reduces up-front cost barrier to market entry

• 50% reduction in capital expenses, tapering out by 10% annually after 2020.

• Applies on first time installations and upgrades

Approach: Model Structure

Conceptual Diagram Only

Conceptual Diagram Only

National Renewable Energy Laboratory Innovation for Our Energy Future 8

National Renewable Energy Laboratory Innovation for Our Energy Future 9

Multiple scenarios were produced internally – Two are articulated in this presentation

Baseline scenario (low vehicle sales) • Modest vehicle incentives (US & HI)

Optimistic scenario (high vehicle sales) • Full parity vehicle incentives • Lower cost fuel

Global inputs for both scenarios • Global hydrogen infrastructure source:

“Transport, Energy and CO2”, IEA 2009 http://www.iea.org/textbase/nppdf/free/2009/transport2009.pdf

• Station cost vs. cumulative infrastructure: NREL Hydrogen Station Cost Calculator (HSCC) 2012

• Vehicle cost vs. global deployment: “Transitions to alternative transportation technologies – a focus on hydrogen”, NRC, 2008 (temporal increase in market share Case 1 was used for all analysis)

Accomplishments: Scenario Analysis Provided

National Renewable Energy Laboratory Innovation for Our Energy Future 10

Key vehicle parameters were selected for ADOPT analysis

Fuel cell vehicle efficiency • Both scenarios use the following on-road, fleet average fuel efficiencies

• 68 mpg in 2015 • 72 mpg in 2050

Acceleration • 6.5 seconds for both scenarios (0-60 mph) • This may be somewhat optimistic, rationale is superior 0-40 mph electric

drive acceleration, and largely urban driving conditions on Oahu. Range

• 300 miles per full refueling

Average vehicle cost (sales-weighted, before incentives) • 2015 = $87,400 • 2020 = $35,600 • 2030 = $28,300 • 2040 = $28,500 • 2050 = $28,700

Accomplishments: Scenario Analysis Provided

ADOPT determines market share based upon price (cost minus

incentives and internal subsidies)

National Renewable Energy Laboratory Innovation for Our Energy Future 11

Feedstock Costs: - Scenario assumes a delivered hydrogen cost of $9/kg to station owner - Price of electricity = 24¢/kWh

Accomplishments: Scenario Analysis Provided

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12

2010 2015 2020 2025 2030 2035 2040 2045 2050

Retail price ceiling of H2Retail price of H2Cost of H2 delivered to station owners

2011

$/kg

H2

Price falls below ceiling due to market competition

Baseline scenario price ceiling targets parity fuel cost per mile with conventional gasoline vehicles (nominal price of gasoline for Oahu, adjusted by FCEV fuel efficiency)

National Renewable Energy Laboratory Innovation for Our Energy Future 12

Feedstock Costs: - Assumption that higher volume production results in lower cost hydrogen - Price of electricity = 24¢/kWh

Prescribed scenario feedstock & fuel price (Optimistic)

Accomplishments: Scenario Analysis Provided Optimistic scenario assumes a price ceiling of $8-$10/kg, which is a more competitive price than gasoline, stimulating market adoption

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2010 2015 2020 2025 2030 2035 2040 2045 2050

Retail price ceiling of H2Retail price of H2Cost of H2 delivered to station owners

2011

$/kg

H2

Price falls below ceiling due to market competition

National Renewable Energy Laboratory Innovation for Our Energy Future 13

Two levels of vehicle incentives were used for scenario differentiation. More FCEV subsidies drive higher sales and improved station economics.

Incentive sources are not restricted to public subsidies: - Early adopter subsidization - Luxury market premium - “Green” premium - State & federal incentives - OEM subsidization Baseline: - Full parity with conventional platforms in early years - Incentives fade out by 2029 Optimistic: - Full parity with conventional platforms in perpetuity

Vehicle cost source: Transitions to Alternative Transportation Technologies: A Focus on Hydrogen, NRC 2008

Accomplishments: Scenario Analysis Provided

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Baseline Scenario Vehicle Incentives

Optimistic Scenario Vehicle Incentives

Aver

age

per-

vehi

cle

ince

ntiv

e (t

hous

ands

201

1$)

National Renewable Energy Laboratory Innovation for Our Energy Future 14

Linear vehicle retirement function used: 4 years = 100% vehicles on road 25 years = 100% vehicles retired -

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Total vehicle salesHydrogen demand (metric tonnes/year)Number of vehicles on the road N

umber of vehicleson the road

Annu

al v

ehic

le sa

les

& h

ydro

gen

dem

and

(met

ric to

nnes

)

Vehicle sales projections with ADOPT model. Higher vehicle incentives and cheaper fuel result in higher sales in the optimistic case.

Accomplishments: Scenario Analysis Provided

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2010 2015 2020 2025 2030 2035 2040 2045 2050

Total vehicle salesHydrogen demand (metric tonnes/year)Number of vehicles on the road

Num

ber of vehicleson the road

Annu

al v

ehic

le sa

les

& h

ydro

gen

dem

and

(met

ric to

nnes

)

Baseline: - Full parity with conventional platforms in early years - Incentives fade out by 2029 Optimistic: - Full parity with conventional platforms in perpetuity

National Renewable Energy Laboratory Innovation for Our Energy Future 15

Station abundance by capacity: - Initial coverage stations = 100 kg/day - Subsequent stations sizes distributed in lines with gas station

distributions

Accomplishments: Scenario Analysis Provided Scenario station build out projection (Baseline Scenario)

Slower adoption of FCEV results in prevalence of smaller capacity stations.

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ion

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t

Station Sizes

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Average Station Sizekg/day

Aver

age

stat

ion

size

(k

g/da

y)

National Renewable Energy Laboratory Innovation for Our Energy Future 16

Scenario station build out projection (Optimistic Scenario) Accelerated adoption of FCEV provides demand for larger capacity stations.

Station abundance by capacity: - Initial coverage stations = 100 kg/day - Subsequent stations sizes distributed in lines with gas station

distributions

Accomplishments: Scenario Analysis Provided

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Average Station Sizekg/day

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age

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size

(k

g/da

y)

National Renewable Energy Laboratory Innovation for Our Energy Future 17

Station types assignments: - Stations <500 kg/day = gaseous hydrogen delivered to the stations - Stations >500 kg/day = liquid hydrogen delivery to the stations

Accomplishments: Scenario Analysis Provided Scenario station type projection (Baseline Scenario)

Small capacity stations dominate and liquid stations prevail.

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Delivered liquid

Station Count by Type & Year

Stat

ion

Type

Cou

nt

National Renewable Energy Laboratory Innovation for Our Energy Future 18

Station types assignments: - Stations <500 kg/day = gaseous hydrogen delivered to the stations - Stations >500 kg/day = liquid hydrogen delivery to the stations

Accomplishments: Scenario Analysis Provided Scenario station type projection (Optimistic Scenario)

Large capacity stations dominate and liquid stations prevail.

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Delivered liquid

Station Count by Type & Year

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ion

Type

Cou

nt

National Renewable Energy Laboratory Innovation for Our Energy Future 19

Station Costs: Station costs decrease over time according to world deployment driven learning curves Station scaling factors are provided from industry partners Larger stations are cheaper on per-capacity basis (economies of scale)

Accomplishments: Scenario Analysis Provided Scenario station cost projections (industry inputs).

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ions 5000 kg/day

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Station Costs vs. Capacity & Time

Stat

ion

Cost

(201

1 $/

stat

ion)

National Renewable Energy Laboratory Innovation for Our Energy Future 20

Cash flow analysis inputs. Values are aligned with H2A assumptions

• Depreciation = 7 years, straight-line • Maintenance as % of contemporary station cost = 2.4% • Labor rate = $40/hr • Credit card fees = $2.5% (flow-through) • Property tax & insurance = 2% of cap cost • Interest on debt = 6% • Total tax rate = 38% • Sales tax = 8% (flow-through) • Sales & administrative expenses = 2% • Licensing & permitting = 1115 $/year • Rent = $3,400 • Total capital incentives through 2017 = 15% • Inflation rate = 0%*

• Target after-tax real IRR = 10% (return on investor equity) • Debt/equity ratio = 0.5 (target) • Cash on hand = 1 month of feedstock & utility expense (target)

Note: All analysis is performed on real $, 2011 basis Model can be adjusted to operate with nominal $’s as well

Accomplishments: Scenario Analysis Provided

Cash Flow Analysis Results (Baseline Scenario)

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Cash on hand (years of feedstock & utilities) Return on equityDebt/equity TargetsProduction incentive revenue

Accomplishments: Scenario Analysis Provided

• Financial solver determines revenues to produce 10% return on equity • Debt to equity ratio drops in years when capital is not raised as equity grows • Cash on hand increases in years of low capital expenditures • Production incentive needs diminish by 2035

21 National Renewable Energy Laboratory Innovation for Our Energy Future

Cas

h on

han

d (y

ears

of f

eeds

tock

) D

ebt/e

quity

ratio

(tot

al d

ebt/t

otal

equ

ity)

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urn

on e

quity

(net

inco

me

/ ow

ner e

quity

)

Production incentive (2011$)

Cash Flow Analysis Results (Baseline Scenario)

$0

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Credit card fees

Sales taxes

Income taxes

Depreciation expense

Retail markup (return on equity)

Interest

Selling and administrative

Licensing & permitting

Rent

Property tax and insurance

Maintenance

Labor

Feedstock & utilities

Sales revenue

Accomplishments: Scenario Analysis Provided

Analysis evaluates required revenue to cover all expenses plus a return on equity. Discrepancy between expenses and realizable

revenue is quantified as “production incentive revenue”

Revenue Shortfall / Incentives Needed

22 National Renewable Energy Laboratory Innovation for Our Energy Future

Rev

enue

& e

xpen

ses

(201

1$)

National Renewable Energy Laboratory Innovation for Our Energy Future 23

Investment & Incentives (Baseline Scenario) Vehicle incentives are dominant. Infrastructure incentives diminish by 2035

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Debt issuance

Shareholder investment

Production incentive

Capital incentive

Investments & Incentives by Source (Millions $)

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Total vehicle incentives (Millions $)

Note: Incentives cover dispensing infrastructure only. No estimates are made at this time for finances of hydrogen production and distribution.

Accomplishments: Scenario Analysis Provided In

vest

men

ts &

ince

ntiv

es

(mill

ions

201

1$)

Tota

l veh

icle

ince

ntiv

es

(mill

ions

201

1$)

National Renewable Energy Laboratory Innovation for Our Energy Future 24

Investment & Incentives (Optimistic Scenario) Vehicle incentives are very dominant.

Production incentives are much lower due to higher infrastructure utilization.

- 1 2 3 4 5 6 7 8 9

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Investments & Incentives by Source (Millions $)

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Total vehicle incentives (Millions $)

Note: Incentives cover dispensing infrastructure only. No estimates are made at this time for finances of hydrogen production and distribution.

Note: Vehicle incentives continue to increase as total number of vehicles increases.

Accomplishments: Scenario Analysis Provided In

vest

men

ts &

ince

ntiv

es

(mill

ions

201

1$)

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l veh

icle

ince

ntiv

es

(mill

ions

201

1$)

National Renewable Energy Laboratory Innovation for Our Energy Future 25

17.016.616.4

17.417.016.7

17.517.016.6

17.417.0

16.4

18.017.0

15.6

18.018.0

17.016.9

40.717.0

13.2

63.017.0

13.0

0 10 20 30 40 50 60 70

Total tax rate = 0.38Total tax rate = 0.3

Total tax rate = 0.25

Debt to equity ratio = 0.3Debt to equity ratio = 0.5Debt to equity ratio = 0.7

Interest rate = 0.08Interest rate = 0.06Interest rate = 0.04

Fuel efficiency deviation from average of 70 mpg = +10Fuel efficiency deviation from average of 70 mpg = 0

Fuel efficiency deviation from average of 70 mpg = -10

After-tax return on equity = 0.15After-tax return on equity = 0.1

After-tax return on equity = 0.05

Annual vehicle sales % deviation = -40%Annual vehicle sales % deviation = -20%

Annual vehicle sales % deviation = 0%Annual vehicle sales % deviation = +20%

Sales price of hydrogen offset $/kg = -0.5Sales price of hydrogen offset $/kg = 0

Sales price of hydrogen offset $/kg = +0.5

Hydrogen feedstock cost offset $/kg = +0.5Hydrogen feedstock cost offset $/kg = 0

Hydrogen feedstock cost offset $/kg = -0.5

Production incentives millions of 2011$

Production Incentives Sensitivity to Key Inputs

Accomplishments: Scenario Analysis Provided Sensitivity analysis of key cluster variables (Optimistic Scenario)

Model is fully integrated and can be used for risk analysis.

Note: Fuel efficiency is one of the most important parameters for infrastructure economics. It is however not shown in this specific sensitivity study.

NREL is a member of H2I core analysis team

Collaborations:

Core analysis team collaboration: • Louis Berger [H2I - lead] • General Motors [FCEV deployment lead] • U.C. Irvine [station placement analysis] • Hawaii Gas [gas producer & supplier] • Wellford Energy [financial modeling oversight] Extended H2I team members: • Air Force Research Laboratory • Aloha Petroleum • County of Hawaii • FuelCell Energy • Office of Naval Research • Proton Onsite • State of Hawaii • TARDEC*

• University of Hawaii • U.S. Army, Pacific • U.S. Department of Energy • U.S. Marine Corps, Pacific • U.S. Pacific Air Forces • U.S. Pacific Command • U.S. Pacific Fleet

* TARDEC = U.S. Army Tank Automotive Research, Development and Engineering Center National Renewable Energy Laboratory Innovation for Our Energy Future 26

National Renewable Energy Laboratory Innovation for Our Energy Future 27

Future Work

NREL completed the first phase of support for H2I, and no future work is currently planned. Modeling algorithms developed for H2I are being used for other hydrogen initiative locations Algorithms are being integrated into NREL’s scenario evaluation, regionalization and analysis (SERA) model. Additional model features to be added - Refinement of geographic dependence of station upgrading - Multi-region analysis (multi-state) - Explicit economics at the individual station level - Refine upgrade frequency (and cost) with industry input - Outputs module for communication with stakeholders

National Renewable Energy Laboratory Innovation for Our Energy Future 28

Summary

NREL produced a detailed deployment and financial model for Hawaii infrastructure deployment. The financial model has been used to analyze scenarios of stations and fuel cell vehicle penetration and presented to the Hawaii Hydrogen Initiative (H2I). Key findings: - Early coverage stations will experience low capital utilization - Station finances would need subsidies to support capital and

operational expenses - Debt and equity investments have a significant place in the early market

introduction and subsequent adoption

Future work: - NREL will continue refining and applying station infrastructure

algorithms to support future deployment initiatives.