introduction to economic modeling and forecasting
TRANSCRIPT
Introduction to Economic Modeling and Forecasting
Hawaii PUC Biomass/ Biofuels Training Program
Andy Aden, John Ashworth, Joelle Simonpietri, Scott Turn
April 11, 2012
EIA Forecasts
• Energy Information Administration (EIA) within DOE uses the National Energy Modeling System (NEMS), Energy sector model
• Forecasts include energy production, demand, imports, and prices through 2030/2035
• Regional model – Electricity sector broken into 15 regions (NERC) – Petroleum Market Model uses 5 PADD regions
• Reference case – Generally assumes current laws and regulations – Includes technologies that are commercial or reasonably
expected to become commercial over next decade or so
Key Updates included in the AEO2011 Reference Case
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• Natural Gas and Oil Supply – more than doubled the technically recoverable U.S. shale gas resources assumed in AEO2010 and
added new shale oil resources
– updated offshore data and assumptions, pushing out start dates for several projects as a result of the drilling moratoria and delaying offshore leasing beyond 2017
• Electricity – updated costs for new power plants
– expanded number of electricity regions to 22 from 13, allowing better regional representation of market structure and power flow
• Transport – increased limit for ethanol blending into gasoline from E10 to E15 for approved vehicles
– includes California’s Low Carbon Fuel Standard, which reduces the carbon intensity of gasoline and diesel fuels in that state by 10% from 2012 through 2020
– revised light duty vehicle miles travelled downward
– updated electric and plug-in hybrid electric battery cost and size
AEO2011, April 2011
Renewables grow rapidly, but under current policies fossil fuels still provide 78% of U.S. energy use in 2035
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Nuclear
Oil and other liquid fuels
Liquid biofuels
Natural gas
Coal
Renewables (excluding liquid
biofuels)
0
20
40
60
80
100
120
1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035
U.S. primary energy consumption quadrillion Btu per year
Source: EIA, Annual Energy Outlook 2011
History Projections 2009
37%
25%
21%
9%
7%
1%
33%
24%
21%
10%
8%
3%
Shares of total U.S. energy
AEO2011, April 2011
0
25
50
75
100
125
150
175
200
225
1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035
Oil prices in the Reference case rise steadily; the full AEO2011 will include a wide range of oil prices
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annual average price of low sulfur crude oil real 2009 dollars per barrel
Source: EIA, Annual Energy Outlook 2011
Projections History 2009
High Oil Price
Low Oil Price
AEO2011 Reference
AEO2011, April 2011
$0.00
$0.50
$1.00
$1.50
$2.00
$2.50
$3.00
$3.50
$4.00
$4.50
2005 2010 2015 2020 2025 2030 2035
Prices Forecast - EIA 2011 Annual Energy Outlook (AEO) US Average, Reference Case, year $2009 years dollars
Ethanol (E85) 3/ Ethanol Wholesale Price
Motor Gasoline 4/ Jet Fuel 5/
Diesel Fuel (distillate fuel oil) 6/
U.S. imports of liquid fuels fall due to increased domestic production – including biofuels – and greater fuel efficiency
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U.S. liquid fuels consumption million barrels per day
Source: EIA, Annual Energy Outlook 2011
0
5
10
15
20
25
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035
Projections History
Natural gas plant liquids
Petroleum supply
Biofuels including imports
Net petroleum imports
2009
13%
11%
41%
32%
10%
52%
34%
4%
Liquids from coal 3%
AEO2011, April 2011
0
5
10
15
20
25
30
35
40
45
2009 2022 2035
Other Advanced
Biofuels fall short of the goal in 2022, but exceed the 36 billion gallon RFS target by 2031
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billions ethanol-equivalent gallons
Source: EIA, Annual Energy Outlook 2011
Legislated RFS in 2022
RFS with adjustments under CAA
Sec.211(o)(7)
Biodiesel
Net imports
Cellulosic biofuels
Corn ethanol
AEO2011, April 2011
Exxon-Mobil Outlook for Energy
• Updated yearly • Takes a very long time horizon – to 2040 • Very macro-scale
– Changes in OECD vs. rest of the world – Changing trends among fuels (coal vs. oil vs.
natural gas, vs renewables) – Looks in projected trends in every sector
(electricity, industry, transportation) by region and by technology
Exxon-Mobil Outlook (continued)
• Results are sobering for the U.S. (and for Hawaii)
• Demand for energy in China, India and Latin America will exceed that in the U.S., Europe, and other OECD countries by 2040.
• Global electricity demand will rise 80%
• Shift will be toward low carbon fuels for power – Natural gas
– Nuclear
– Wind and other renewables
Virtually All the Growth in Energy Demand is Outside the OECD Countries
Exxon-Mobil Outlook (continued)
Exxon – Mobil Outlook (continued)
BP Energy Outlook
• Much more Eurocentric than Exxon-Mobil
• Nearer term focus – to 2030
• Sees near-term penetration of renewables and energy conservation and a rapid transition away from coal for power generation
BP Energy Outlook (continued)
BP Energy Outlook (continued)
• Country by country comparisons of – Power generation by fuel type
– Fossil fuel consumption
– CO2 emissions by country by year
• Mostly focused on current and recent past rather than long-term trends
• Has just started to cover renewable energy trends for the medium term – to 2017
Department of Defense Fuel Budgeting
New techniques under consideration:
1. Market strategy to address price volatility
2. Contracting strategy to address absolute price
3. Commercialization strategy to address absolute price
Scenesetter: Price Movements
Traditional Forecasting
Past Future
Smooth trend
Volatile Performance
Assumptions: Volatility in a global commodity like petroleum is caused by factors beyond our control Absolute price is only marginally controllable
Reality: High Price Volatility
Market Strategy to Deal with Volatility:
Borrow portfolio principles from financial sector
Source: peopleandplanet.com
Even though the inputs become more correlated over time, the portfolio is still better off
Contracting Strategy to Stabilize Price
Non-petroleum Index
$ pe
r G
allo
n
Time (years)
Desired Cost Path
Commercialization Strategy to Reach Competitive Price
Petroleum Reference Price
1) Buy Down the Capital Cost
2) DoD purchase price for bulk fuels includes only the value
it directly receives
Technical: Scale, productivity, coproducts
Business: Grants, loans, tax credits,
private investment etc. provided by DOE,
USDA, DoD DPA Title III, state & local
interests, and others
Profit for supply chain +
Long-term Stable-price premium
+ GHG
Premium/other
$ pe
r G
allo
n
Time (years)
Fuel Cost Trend
Actual Costs (at test quantities)
2010 2011 2009
400
150
50
Target Cost <$3/gal JP8 Ideally by 2016
Progress as To Date Along Cost Reduction Path
Numerous Liquid Biofuels Transportation Options
Biomass Feedstocks
Lignocellulosic Biomass (wood, agri, waste, grasses, etc.)
Sugar/Starch Crops (corn, sugar cane, etc.)
Natural Oils (plants, algae)
Ag residues, (stover, bagasse)
Intermediates
Syn Gas
Bio-Oils
Lignin
Sugars
Gasification
Pyrolysis & Liquefaction
Hydrolysis
* Blending Products
Transportation Fuels
Ethanol & Mixed Alcohols
Diesel*
Methanol
Gasoline*
Diesel*
Gasoline* & Diesel*
Diesel*
Gasoline*
Hydrogen
Ethanol, Butanol, Hydrocarbons
Biodiesel
Green diesel
Catalytic synthesis
FT synthesis
MeOH synthesis
HydroCracking/Treating
APP
Catalytic pyrolysis
APR
Fermentation
Catalytic upgrading
MTG
Transesterification
Hydrodeoxygenation
Fermentation
Collaborate with engineering & construction firm to enhance credibility, quality
Better access to vendors for quotations
Conceptual design reports are transparent, highly peer reviewed
Assumes nth-plant project costs and financing (ignores first-of-a-kind risks)
Iteration with researchers and experimentalists is crucial
Minimum product selling price (MESP or MFSP) = minimum price fuel must sell for in order for net present value (NPV) of zero or greater Includes internal rate of return (IRR)
Conceptual Process Design
Material and Energy Balance
Capital and Project Cost Estimates
Economic Analysis
Environmental / Sustainability Analysis
R&D
DOE Goals
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Technoeconomic Analysis - Approach
Hybrid Saccharification & Fermentation - HSF
Pretreatment Conditioning
Co- fermentation of C5 & C6 Sugars
Product Recovery Ethanol
By-products
Enzyme Production
Enzymatic Hydrolysis
Residue Processing
•Conceptual design of a 2,000 tonnes/day commercial plant – one possible tech package, not optimized
•NREL pilot plant based on this process •Basis for connecting R&D targets to cost targets •Has undergone rigorous peer review •Basis for comparison against other technology options
Cellulosic Ethanol Design Report - Biochemical
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2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Min
imum
Eth
anol
Sel
ling
Pric
e (2
007$
per
gal
lon)
Conversion Feedstock
$3.85 $3.64 $3.57
$3.18 $2.77
$2.56 $2.15
$4.27
$5.33
$6.90
$9.16
Bench Scale - Enzymes
Scale Up Pretreatment
Scale Up Saccharification
BC Conversion to Cellulosic Ethanol Historic State of Technology
Significant Cost Reduction of Cellulosic Ethanol Resulting from R&D
2007 2008 2009 2010 2011 2012
Targets Minimum Ethanol Selling Price ($/gal) $3.64 $3.56 $3.19 $2.77 $2.56 $2.15 Feedstock Contribution ($/gal) $1.12 $1.04 $0.95 $0.82 $0.76 $0.74 Conversion Contribution ($/gal) $2.52 $2.52 $2.24 $1.95 $1.80 $1.41 Yield (Gallon/dry ton) 69 70 73 75 78 79 Feedstock Feedstock Cost ($/dry ton) $77.20 $72.90 $69.65 $61.30 $59.60 $58.50 Pretreatment Solids Loading (wt%) 30% 30% 30% 30% 30% 30% Xylan to Xylose (including enzymatic) 75% 75% 84% 85% 88% 90% Xylan to Degradation Products 13% 11% 6% 8% 5% 5% Conditioning Ammonia Loading (mL per L Hydrolyzate) 50 50 38 23 25 25 Hydrolyzate solid-liquid separation Yes Yes Yes Yes Yes No Xylose Sugar Loss 2% 2% 2% 2% 1% 1% Glucose Sugar Loss 1% 1% 1% 1% 1% 0% Enzymes Enzyme Contribution ($/gal EtOH) $0.39 $0.38 $0.36 $0.36 $0.34 $0.34 Enzymatic Hydrolysis & Fermentation Total Solids Loading (wt%) 20% 20% 20% 17.5% 17.5% 20% Combined Saccharification & Fermentation Time (d) 7 7 7 5 5 5 Corn Steep Liquor Loading (wt%) 1% 1% 1% 1% 0.25% 0.25% Overall Cellulose to Ethanol 86% 86% 84% 86% 89% 86% Xylose to Ethanol 76% 80% 82% 79% 85% 85% Arabinose to Ethanol 0% 0% 51% 68% 47% 85%
State of Technology – Biochemical Platform
Cost by Area
Biomass Refinery-Ready Intermediates
Finished Fuels and Blendstocks
Existing Refinery Infrastructure
Atm
osph
eric
and
Va
cuum
Dis
tilla
tion
Gas L Naphtha H Naphtha LGO VGO Atm. Res. Vac. Res.
Reform
FCC
Alky/Poly
HT/HC
Coker
Gasoline Jet Fuel Diesel Fuel
Crude Oil
Insertion Point #1:
Insertion Point #3:
Insertion Point #2:
Integration With Existing Fuels Infrastructure
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National Advanced Biofuels Consortium (NABC), www.nabcprojects.org
Algae Technoeconomics and Dashboard Tools
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OP (TAG)
PBR (TAG)
OP (Diesel)
PBR (Diesel)
Cost
of P
rodu
ctio
n ($
/gal
)
Cost of TAG/Diesel Production (OP vs PBR)
Operating ($/gal of product)
Capital ($/gal of product)
Land ($/gal of product)
NREL has developed for DOE baseline economics for algae pathways: - Open pond (autotrophic) - Closed photobioreactor (autotrophic)
NREL has also created simple spreadsheet dashboard tools
Biomass Scenario Model (BSM) – Systems Dynamics SUPPLY CHAIN
Feedstock Production
Feedstock Logistics
Biofuels Production
Biofuels Distribution
Biofuels End Use
DYNAMIC MODELS OF SUPPLY INFRASTRUCTURE,PHYSICAL CONSTRAINTS, MARKETS, AND DECISION MAKING
Feedstock Supply Moduleo 6 Feedstock typeso 10 geographic regionso 10+ land useso Farmer decision logico Land allocation dynamicso New agriculture practiceso Markets and prices
Feedstock Logistics Moduleo Multiple logistics stageso Cost breakdownso Transportation distanceo Land eligibility
Conversion Moduleo 5 conversion platformso 4 development stageso 6 learning attributeso Cascading learning curveso Project economicso Industry growth and
investment dynamics
Distribution Logistics Moduleo Implicit distribution modeso Regional depot/storageo Transport costso Inter-regional transport
Dispensing Station Moduleo Fueling-station economicso Fuel-choice dynamicso Distribution-coverage effects
Vehicle Moduleo 7 vehicle technologieso 4 efficiency classeso Fleet ageingo E10/E20/E85 potential
POLICIES INCENTIVES EXTERNALITIES
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Hawaii Specific Economic Models
Jobs and Economic Development Impacts (JEDI)
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• 1. A project-level tool in Excel (http://www.nrel.gov/analysis/jedi/)
• To estimate the number of jobs (and income, economic activity), that will accrue to the state from the project
• 2. Input-output analysis (or multiplier analysis)
• A method of summing the impacts of a series of effects generated by an expenditure (e.g., jobs/million dollar purchase of inputs)
• Multipliers in JEDI derived from IMPLAN
• 2008 multipliers: reflect the economic conditions (e.g., inter-industry relationships, jobs supported by industries, and industry demand) in 2008
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3. Total employment effects, including
• Direct jobs: project development and onsite labor
• Indirect jobs: local revenue and supply chain effects
• Induced jobs: effects driven by re-investment and
spending of earnings
• Total jobs:
• Total jobs = Direct + Indirect + Induced
JEDI model (cont’d)
Jobs Creation – JEDI Model Estimation for Hawaii
Local Economic Impacts - Summary Results Jobs Earnings Output
During construction period $MM (2007) $MM (2007) Direct Impacts 683 $58.18 $94.65 Construction Sector Only 385 $45.59 Indirect Impacts 258 $9.52 $28.48 Induced Impacts 417 $13.70 $44.35 Total Impacts (Direct, Indirect, Induced) 1,358 $81.39 $167.47 During operating years (annual) Direct Impacts 1067 $20.62 $66.74 Plant Workers Only 68 $2.44 Agricultural Sector Only 944 $15.98 Other Workers 54 $2.19 Indirect Impacts 162 $4.62 $16.01 Induced Impacts 205 $6.72 $21.74 Total Impacts (Direct, Indirect, Induced) 1,434 $31.95 $104.50 Notes: Earnings and Output values are millions of dollars in year 2007 dollars. Construction period related jobs are full- time equivalent for the 3 year construction period. Plant workers includes operators, maintenance, administration and management. Economic impacts "During operating years" represent impacts that occur from plant operations/
expenditures. The analysis does not include impacts associated with spending of plant "profits" and assumes no tax abatement unless noted. Totals may not add up due to independent rounding.
Assumptions: 61 MM gal/yr cellulosic ethanol, bagasse at $75/dry ton, Biochemical Conversion
Analysis at NREL
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Biomass Key Analytic Strengths and Capabilities at NREL
1) Technoeconomics – Cost Driven R&D
2) Sustainability Analysis
– Life cycle assessment, metrics and optimization strategies
3) Other Analyses (resource assessment, policy, etc) - Biomass Scenario Model
- Biorefinery Linear Programming (LP) model
NREL centers collaborate with each other and other national labs
– ORNL (Resource availability, production, land use change)
– INL (Feedstock harvesting, storage and logistics)
– NREL (Biomass conversion technologies, analysis)
– PNNL (Thermochemical conversion)
– ANL (Separations, life cycle assessment)
NREL analysis helping to shape the future of biomass industry: - RFS II - Industrial models - Energy outlooks