Algal Biofuel Pathway Baseline Costs

Report
Algal Biofuel Pathway Baseline Costs
Algae Peer Review
Annapolis, MD
Andy Aden, NREL
Ryan Davis, NREL
April 7, 2011
This presentation does not contain any
proprietary, confidential, or otherwise restricted
information
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.
Goals and Objectives
• The goal of this task is to develop baseline technoeconomic
analysis and user models for algal biofuels
• Serves as a benchmark against which process variations can be
compared
• This task directly supports the Biomass Program by assisting
in the development of baseline costs and future cost targets
• Leverages decades of experience in cost-driven R&D for other
biomass conversion platforms (biochemical, thermochemical, etc)
• Using technoeconomic analysis (TEA) and modeling, NREL
provides direction, focus, and support to the biomass
program and algae-related projects, guiding R&D towards
program goals
NREL, Sept 15, 2010, Pic #18071
• Algae technologies under development can be incorporated into
the models in order to quantify their economic impact
• Experimentally verified data will be used in the models to quantify
progress towards program goals
• Sensitivity analysis is used to quantify the impact of key variables
on overall economics
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Overview
Barriers
Timeline
Ft-A. Feedstock Availability and Cost
Ft-B. Sustainable Production
Bt-K. Biological Process Integration
June 1, 2010
Sept. 30, 2014
~ 25% Complete
Budget
FY10:
$100,000
FY11:
$125,000
FY12:
$200,000
No ARRA Funding
Partners
NREL, March, 2008, Pic #15689
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DOE OBP HQ and GO
Algae Project PIs
National Labs (INL, PNNL, ANL, etc)
Industrial Partner(s) (undisclosed)
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Project Overview
• Multiple algae economic studies have
been conducted, with enormous
variation
• This project leverages several prior
research activities:
• Conceptual models developed from
scratch
• Phased approach:
1)
2)
3)
4)
Develop baseline models using best
available data
Peer review models
Incorporate technologies under
development
Assist in cost target development
$50
$45
$40
$35
$30
$25
$20
$15
$10
$5
$0
Average = $19.25 USD/gal
Variability is wide; Std. Dev. =
$28.8 USD/gal
Benemann low
Benemann high
NREL low
NREL medium
NREL maximum
NMSU low demo
NMSU high demo
NMSU low…
NMSU high…
Solix - current
Solix -Phase I
Solix - Phase II
Seambiotic/IEC,…
Bayer AG
General…
General…
Cal Poly WWT
Sandia - Raceway
Sandia - PBR
Tapie & Bernard…
Tapie & Bernard…
Aquatic species program (ASP)
DOE Biomass Algal Roadmap
Analysis conducted for EPA under RFS II
USD/gal
•
•
•
Triglyceride Production Cost
Courtesy Amy Sun (Sandia)/ Phil Pienkos (NREL)
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Approach
• Rigorous process models developed in Aspen Plus for material and energy balances
• Capital and operating costs developed in Excel®
• User models developed in Excel® that approximate Aspen output
• Dissemination of user models and documentation for peer review
• Cost data derived from vendors, cost databases, literature, etc.
• Financial assumptions consistent with other platforms
R&D
Conceptual
Process
Design
Material and
Energy Balance
Capital and
Project Cost
Estimates
Economic
Analysis
Environmental /
Sustainability
Analysis
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Accomplishments
Status:
• Completed milestone report 12/15/10
• Developed Excel spreadsheet models
• User-friendly, generally good agreement with Aspen models
• Submitted publication to peer reviewed journal for autotrophic
pathways (Applied Energy)
Scope of analysis:
•3 Pathways
• Autotrophic (“AT”) via open pond
• Autotrophic via photobioreactors (PBRs)
• Heterotrophic (“HT”) via fermentation tanks
• Process boundary carries through to oil upgrading (hydrotreating)
• Green diesel blend stock
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Design Configuration: Autotrophic
0.05% (OP)
0.4% (PBR)
Makeup water
10%
1%
CO2
Algae
Growth
Makeup solvent
Flocculent
Settling
DAF
Hydrogen
Solvent recycle
Offgas
20%
Centrifuge
Recycle water
Lipid
Extraction
Blowdown
Recycle nutrients/ water
Makeup nutrients
Phase
Separation
Solvent
Recovery
Raw
oil
Naphtha
Upgrading
(hydrotreater)
Diesel
Spent algae
+ water
Anaerobic
Digestion
Sludge
Biogas
for
energy
Flue gas from turbine
Power
Green = algae cell density
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Design Basis: Autotrophic Cases
Growth stage
•Open ponds:
•
•
•
•
•
Unlined raceways
Paddle wheel mixing
20 cm depth
CO2 feed via sumps, spargers
CO2 scrubbed from “nearby” source
Shen et al (2009), “Microalgae
mass production methods”
•PBR
•
•
•
•
Tubular design
8 cm ID x 80 m sections
Plastic tubes (“low” cost)
Temp control via sprinklers
Bryan Willson (2009),
“Solix Technology Overview”
Harvesting
•Bioflocculation (1°)  flocculation/DAF (2°)  centrifuge (3°)
•
Concentrates algal biomass to 20% solids
Extraction
•Homogenization + butanol solvent extraction
•
•
Proven technologies in keeping with “baseline” emphasis
Extraction is currently a limiting step for scale-up due to scarcity of public data (DOE Algal Biofuel Roadmap)
Spent biomass utilization
•Anaerobic digestion
•
Improves sustainability: generates power coproduct, enables nutrient recycle
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Design Configuration: Heterotrophic
Makeup solvent
Vent
5%
Sugar stream
Algae
Growth
Hydrogen
Solvent recycle
20%
Concentration
(centrifuge)
Water/solubles
Air
Recycle nutrients/ water
Makeup nutrients
Lipid
Extraction
Phase
Separation
Solvent
Recovery
Raw
oil
Offgas
Naphtha
Upgrading
(hydrotreater)
Diesel
Spent algae
+ water
Biogas for
energy
Anaerobic
Digestion
Sludge
Flue gas from turbine
Power
Green = algae cell density
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Design Basis: Heterotrophic Case
Aerobic fermentation
• Carbon source from cellulosic sugars (corn
stover)
•
Leverage NREL expertise, design report
models
• 50% lipid baseline (vs 25% for autotrophic)
• NREL model: 20% saccharification solids =
110 g/L sugars
• 50% algae yield = 50 g/L algae
• 4 day batch time
• 1,000 m3/tank
• Concentration via centrifuge from 5%  20%
• All other downstream units equal to AT cases
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Design Assumptions
Autotrophic
Base case
Scale of production [MM gal/yr algal oil]
Algae productivity
Algal cell density [g/L]
Lipid content [dry wt%]
CO2 consumed [lb/lb algae]
Operating days/yr
Open pond
10
25 [g/m2/day]
0.5
25%
1.9
330
PBR
10
1.25 [kg/m3/day]
4
25%
1.9
330
Heterotrophic
Scale of production [MM gal/yr algal oil]
Sugar source
Algal cell density [g/L]
Lipid content [dry wt%]
Algae productivity [g algae/g sugar]
% Sugar conversion
Operating days/yr
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Base case
13 (1,000 dry tonne/day corn stover)
Corn stover via NREL cellulosic ethanol design report model
50 (set per sugar model @20% saccharification solids)
50%
0.5
95%
350
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Baseline Cost Results
Minimum Fuel Selling Price
Direct Installed Capital, MM$ (Ponds)
$25
Ponds
$22
$20.53
Selling Price ($2007/gal)
$20
$30
CO2 Delivery
Harvesting
$21
$12
$18.10
Extraction
Digestion
$9
Inoculum System
$15
Hydrotreating
$41
$24
$10
Operating ($/gal of
product)
$9.84
$8.52
Capital ($/gal of
product)
Land Costs
$23
$16
Total = $195MM
Direct Installed Capital, MM$ (PBR)
$5
PBR system
$108
CO2 Delivery
$522
$0
OP
(TAG)
PBR
(TAG)
OP
(Diesel)
PBR
(Diesel)
OSBL Equipment
Harvesting
Extraction
Digestion
Inoculum System
Baselines show high costs of today’s
currently available technologies,
opportunities for cost reduction
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Hydrotreating
OSBL Equipment
Land Costs
Total = $631MM
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Results: Land, Resource, Cost Assessment
Open pond
PBR
Heterotrophic
Yield
Lipid production [MM gal/yr]
Diesel production [MM gal/yr]
10.0
9.3
10.0
9.3
13.1
12.2
Land Use:
Pond/PBR/Fermentor land use [acre]
Total plant land required [acre]
4,820
7,190
4,820
7,190
Resource Assessment:
Net makeup water demand [MM gal/yr]1
-Water evaporated [gal/gal lipid]
-Water blowdown to treatment/discharge [gal/gal lipid]
10,000
570
430
3,000
250
50
Fresh CO2/ sugar demand [ton/yr]2
145,000
145,000
Power coproduct [MM kwh/yr]3
Naphtha coproduct [gal/yr]
80
340,000
100
340,000
$390
$37
$6
$990
$55
$7
System cost:
Total capital cost (direct + indirect) [$MM]
Net operating cost [$MM/yr]
-Coproduct credit [$MM/yr]
1.
2.
3.
Includes evaporation (consumptive loss) plus blowdown (treated offsite)
After recycling turbine flue gas + digestion effluent
After considering all ISBL facility power demands; includes CO2 capture step (autotrophic).
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Sensitivity Analysis: Autotrophic
Cost of TAG: Alternative Growth Cases
$20
1.25 g/L/day
25% TAG
$18
$16
Cost of Production ($/gal)
Operating ($/gal of lipid)
Capital ($/gal of lipid)
$14
Land ($/gal of lipid)
$12
25 g/m2/day
25% TAG
$10
2.0 g/L/day
50% TAG
$8
3.0 g/L/day
60% TAG
$6
40 g/m2/day
50% TAG
$4
60 g/m2/day
60% TAG
$2
$0
OP
(base)
OP
OP
(aggressive) (max growth)
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PBR
(base)
PBR
PBR
(aggressive) (max growth)
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Sensitivity: Ponds
Open Pond Sensitivities
Lipid content (50 : 25 : 12.5%)
Growth rate (50 : 25 : 12.5 g/m2/day)
More “bang for the buck”
targeting lipids vs growth rate
(Realistically, cannot maximize both
simultaneously)
Operating factor (365 : 330 : 250 days/yr)
Nutrient recycle (100% : base : 0%)
Water supply (undergound : utility purchase)
Inoculum system (not required : required)
Nutrient demand (source 1 : base : source 2)
Flocculant required (15 : 40 : 80 mg/L)
CO2 cost basis ($0 : $36 : $70/ton)
CO2 delivery (pure CO2 : flue gas)
Water recycle (100% : 95% : 80%)
Evaporation rate (0.15 : 0.3 : 0.6 cm/day)
-$6
-$4
-$2
$0
$2
$4
$6
Change to TAG production cost ($/gal)
$8
$10
[1] Benemann, J. et al., “Systems and Economic Analysis of Microalgae Ponds for Conversion of CO2 to Biomass.”
Final Report to the Department of Energy, Pittsburgh Energy Technology Center (1996) DOE/PC/93204-T5
[2] Hassannia, Jeff. “Algae Biofuels Economic Viability: A Project-Based Perspective.” Article posted online: http://www.biofuelreview.com/content/view/1897/1
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Sensitivity: PBR
PBR Sensitivities
Lipid content (50 : 25 : 12.5%)
Growth rate (2.5 : 1.25 : 0.63 kg/m3/day)
Tube cost basis (-50% : $1.05/ft : +50%)
Tube cost = 50%
of total production cost
Operating factor (365 : 330 : 250 days/yr)
Nutrient recycle (100% : base : 0%)
Nutrient demand (source 1 : base : source 2)
Flocculant required (15 : 40 : 80 mg/L)
CO2 cost basis ($0 : $36 : $70/ton)
Inoculum system (not required : required)
Water supply (undergound : utility purchase)
-$10
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-$5
$0
$5
$10
Change to TAG production cost ($/gal)
$15
$20
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Relevance
• The baseline models and analysis are supporting a number of program
activities and milestones
•
•
For example: GREET algae analysis
Models are important for development of cost-competitive biofuels from algae
• Baseline results demonstrate that for systems modeled, fuels production
is not yet cost competitive with current fossil fuels
•
•
High-value coproducts required to improve economics
Significant R&D required
• The analysis thus far shows primary cost drivers are lipid content and
growth rate
• This analysis can serve a wide variety of stakeholders
•
•
•
Industry (analysis facilitates communication between industry and DOE)
Research community
Decision makers
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Success Factors
Success Factors:
– Maintaining close interaction with researchers is crucial
– Transparent communication of all assumptions and results to ensure
proper use of data
– Buy-in from all stakeholders is critical
– Common financial assumptions for program
Challenges
– Much of the current model data is derived from literature. Experimentally
verified data will be more meaningful
– Several process unit operations possess high degree of uncertainty
• Harvesting
• Extraction
– There are many possible combinations of process technology and
configuration not currently modeled
– Scalability of technologies
– Sustainability (e.g. water and resource requirements)
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Future Work
• Publication
• Incorporate technologies under development into models
• Assist DOE in target development for algae
• Sustainability analysis
• Analyze feasibility of using wastewater / alternative water sources
• Investigate lower-cost materials for PBR
• Comparative analysis for heterotrophic vs. autotrophic over time
• Investigate process alternatives
NREL, Sept, 2010, Pic #18229
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Summary
• Rigorous algae baseline technoeconomic analysis and user models have
been developed for the Biomass Program and algae community
•
3 pathways: open pond, photobioreactor, heterotrophic
• Models currently calculate high costs for algal biofuels
• Primary cost drivers are lipid content and yield
• Models will be useful in assisting DOE with target development and research
interaction
• Thank you to….
•
•
•
•
•
Biomass Program Algae Team (Valerie Sarisky-Reed, Joyce Yang, Ron Pate, Joanne
Morello, Zia Haq, Leslie Pezzullo, Paul Bryan, Brian Duff, Alison Goss Eng, Christine
English, Dan Fishman)
NREL researchers: Phil Pienkos, Lieve Laurens, Eric Jarvis, Eric Knoshaug, Mary Biddy,
David Humbird, Abhijit Dutta, Danny Inman
National Laboratory partners: (INL, PNNL, ORNL, ANL, SNL)
NAABB (Jose Olivares)
Industrial partners
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Publications
Ryan Davis, Andy Aden, Philip T Pienkos. Techno-Economic Analysis
of Autotrophic Microalgae for Fuel Production. Submitted for
publication to Applied Energy (2011, in review).
Davis, Ryan. November 2009. Techno-economic analysis of
microalgae-derived biofuel production. National Renewable Energy
Laboratory (NREL)
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