The Costs of Production of Alternative Jet Fuel

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LAE.MIT.EDU ASCENT ADVISORY COMMITTEE MEETING | APRIL 18, 2017 A Harmonized, Stochastic Assessment The Costs of Production of Alternative Jet Fuel

Transcript of The Costs of Production of Alternative Jet Fuel

LAE.MIT.EDU

ASCENT ADVISORY COMMITTEE MEETING | APRIL 18, 2017

A Harmonized, Stochastic Assessment

The Costs of Production of

Alternative Jet Fuel

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AGENDA

Motivation

Conversion process overview

Methods

Results

Policy analysis

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Motivation

• The production and use of alternative jet fuels reduces the emissions associated with conventional jet fuel thus imposing GHG savings

• Alternative aviation fuels are a component of international emissions-reduction strategies

Source: ATAG, 38th ICAO Assembly

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Research focus

Analyze and compare the performance of renewable jet fuel pathways using stochastic estimation (Monte Carlo):

Perform harmonized stochastic and analysis to evaluate uncertainty

Quantify costs of productions in terms of minimum selling price and net present value (TEA)

Quantify performance under the Renewable Fuel Standard (RFS2)

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Study process

Model pathway and determine mass and energy

flows

Estimate capital and operating

costs, collect market data and build

stochastic economic model

Compute minimum selling

price and net present value

Vary policy conditions

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Conversion processes

Conversion processes selected based on ASTM/RFS approval and commercial interest:

Developed

technologies:

HEFA*

Fischer-Tropsch*

Developing

technologies assessed

using industrial- & lab-

scale data:

Advanced fermentation*

Developing

technologies assessed

using lab-scale data:

Aqueous phase

processing

HTL

Fast pyrolysis

*ASTM approved

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Feedstock selection with corresponding pathway

Herbaceous

biomass

Energy crops

Waste greases

Corn grain

Sugarcane MSW

Woody biomass

Corn stover

• HEFA

• Advance fermentation

• Aqueous phase

processing

• Fischer-Tropsch

• Hydrothermal liquefaction

• Fast pyrolysis

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Hydroprocessed esters and fatty acids process (HEFA)

Source: Pearlson et. al., 2013

Soybean oil

Yellow grease

Tallow

Hydro-deoxygena

tion

Isomerization and catalytic

crackingSeparation

Light ends, naphtha, jet and diesel

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Advanced fermentation process (AF)

Source: Staples et. al., 2014

Sugarcane

Corn grain

Switchgrass

Pretreatment Saccharification and Fermentation

TAGs, FattyAcids,

Alkanes, iBuOH, and

EtOH

- Milling/Concentration- Dry milling- Dilute acid pretreatment

- Sugars oligomersàmonomeric sugar

Extraction and Purification

- De-propenation- De-oxygenation- Isomerization/catalytic

cracking

Light ends, jet and diesel

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Aqueous phase processing (APP)

Source: Bond et. al., 2015

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Fischer-Tropsch process (FT)

Source: Niziolek et. al., 2015

Sorted MSW

Pretreatment Gasification

Syngas:

CO and H2

- Drying- Shredding- Sizing

- Partial oxidation (limited

amounts of air or oxygen)

Fischer-Tropsch

- Cooling and conditioning of the syngas

- Synthesis to fuels and

wax- Refining

Light ends, jet and diesel

Gasoline,

jet and

diesel

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Hydrothermal liquefaction process (HTL)

Source: Zhu et. al., 2014

Woody biomass Pretreatment

HTL process

Bio-oil

- Softening & preheating

Hydro-processing

- Hydrotreating- Hydrocracking & product

separation

Gasoline, jet and diesel

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Fast pyrolysis and hydroprocessing (FPH)

Source: Bittner et. al., 2015; Brown et. al. 2012

Corn stover Pretreatment

Pyrolysis reaction

Bio-oil

- Chopping & drying

Hydro-processing

- Hydrotreating- Hydrocracking & product

separation

Gasoline, jet and diesel

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Study process

Model pathway and determine mass and energy

flows

Estimate capital and operating

costs, collect market data and build

stochastic economic model

Compute minimum selling

price and net present value

Vary policy conditions

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Stochasticity: Monte Carlo models of plant performance

• Deterministic DCFROR fails to capture uncertainty:

• Harmonized, stochastic models allow us to calculate minimum selling price (MSP) and net present value (NPV)

Stochasticinputs

Fuel pricesGovernment mandates

Feedstock prices

CAPEX and fixed OPEX

Utility costs Fuel yield

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Capital investment uncertainty

• Typical distributions are symmetric triangular/beta/normal using minimum and maximum bounds of

±20%, with the deterministic point estimate as the mode

• An asymmetrical, pert distribution was assumed in order to resemble realistic cost overruns (mean

overrun of 5%)

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Fuel price uncertainty

• When a large number of samples is available and some expected growth rate is known

• Fit distribution to historical price data to predict price fluctuations in future years around an average projected

price (U.S. EIA price growth projections), using Geometric Brownian motion

• GBM incorporates randomly distributed start values, growth rates, and yearly deviations over a 20-year plant

lifetime

0.00

1.00

2.00

3.00

4.00

5.00

6.00

2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038

Ga

so

line

price

($

/ga

l)

AEO Gas Prices 2018-2038

Gas Mid

Gas Low

Gas High

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Study process

Model pathway and determine mass and energy

flows

Estimate capital and operating

costs, collect market data and build

stochastic economic model

Compute minimum selling

price and net present value

Vary policy conditions

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Minimum selling price (MSP) comparisons

Pathway, Feedstock Median ($/L MD) Mean ($/L MD)

HEFA Soybean oil 1.16 1.19

HEFA Tallow 1.04 1.06

HEFA Yellow grease 0.89 0.91

AF Corn grain 1.64 1.66

AF Sugarcane 1.43 1.47

AF Herbaceous

biomass2.50 2.51

HTL 2.75 2.78

APP 2.05 2.07

FT 1.14 1.15

FPH 1.50 1.52

EIA 5- year avg.

jet price = $0.64/L

0 0.5 1 1.5 2 2.5 3 3.5 4

$/liter middle distillate

FPH, Corn stover

FT, MSW

APP, Woody biomass

HTL, Woody biomass

AF, Herbacecous Biomass

AF, Sugarcane

AF, Corn grain

HEFA, Yellow grease

HEFA, Tallow

HEFA, Soybean oil

EIA current jet

price = $0.41/LEIA projected high

price= $1.08/L

EIA projected low

price= $0.44/L

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Minimum selling price (MSP) contributions

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

HEFA Soybean

Oil

HEFA Tallow HEFA Yellow

Grease

AF Corn Grain AF Sugarcane AF Herbaceous

Biomass

HTL Woody

Biomass

APP Woody

Biomass

FT MSW FP Corn Stover

MS

P (

$/L

mid

dle

dis

till

ate

)

Minimum Selling Price Contributions

Capital costs Fixed OPEX Non-Feedstock Variable OPEX Feedstock

Income tax Revenue from gasoline/naphtha Revenue from other co-products Revenue from scrap

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Net present value (NPV) comparisons

Pathway,

FeedstockMedian ($B) Mean ($B) Prob. >0

HEFA Soybean oil -0.278 -0.281 8.6%

HEFA Tallow -0.199 -0.202 14.8%

HEFA Yellow

grease-0.110 -0.112 27.7%

AF Corn grain -0.549 -0.552 0.21%

AF Sugarcane -0.414 -0.420 1.8%

AF Herbaceous

biomass-1.044 -1.036 0.00%

HTL -0.863 -0.854 0.00%

APP -0.721 -0.716 0.00%

FT -0.217 -0.210 7.9%

FPH -0.351 -0.344 2.1%-2 -1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2

$B

FPH, Corn stover

FT, MSW

APP, Woody biomass

HTL, Woody biomass

AF, Herbacecous Biomass

AF, Sugarcane

AF, Corn grain

HEFA, Yellow grease

HEFA, Tallow

HEFA, Soybean oil

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Net present value (NPV) contributions

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

600

800

HEFA Soybean

Oil

HEFA Tallow HEFA Yellow

Grease

AF Corn Grain AF Sugarcane AF Herbaceous

Biomass

HTL Woody

Biomass

APP Woody

Biomass

FT MSW FP Corn Stover

NP

V (

$M

M)

Net Present Value (NPV) Contributions

Capital costs Fixed OPEX Non-Feedstock Variable OPEX

Feedstock Income tax Revenue from MD fuels

Revenue from gasoline/naphtha Revenue from other co-products Revenue from scrap

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Study process

Model pathway and determine mass and energy

flows

Estimate capital and operating

costs, collect market data and build

stochastic economic model

Compute minimum selling

price and net present value

Vary policy conditions

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Renewable Identification Numbers (RINs)

RIN CategoryGHG Intensity

Reduction

Feedstock

Examples

Pathway

Examples

Renewable fuel 20% Corn starch

Dry mill

process,

fermentation

Advanced

biofuel50%

Sugarcane,

corn stover,

soybean oil

HEFA, AF

Biomass-based

diesel50%

Sugarcane,

corn stover,

soybean oil

HEFA, AF

Cellulosic

biofuel/biodiesel60%

Woody

biomass,

switchgrass

FPH, HTL

Incre

asin

g v

alu

e

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NPV policy comparison

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Pro

ba

bil

ity

of

Po

sit

ive

NP

V100% credit share + RIN market

75% credit share + RIN market

50% credit share + RIN market

25% credit share + RIN market

Blender's credit expiry + no RIN

market

No Policy

Seamus [email protected]

LAE.MIT.EDU

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Sensitivity analysis

0.8 1 1.2 1.4 1.6

Discount rate % (3.2, 15, 22)

Feedstock cost $/Mlb (225, 370, 525)

Income tax rate % (0, 16.9, 39)

Fuel yield GGE/MT (240, 304, 320)

FCI % (80, 100, 150)

Fixed Operating Cost, % of FCI (8, 11, 16)

$/L

HEFA Soybean Oil

Baseline: $1.19

1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8

Discount rate % (3.2, 15, 22)

Feedstock cost $/MT (40, 66, 100)

Income tax rate % (0, 16.9, 39)

Fuel yield GGE/MT (49, 62, 65.4)

FCI % (80, 100, 150)

Fixed Operating Cost % of FCI (2, 3, 6)

$/L