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.

NREL, Sept 15, 2010, Pic #18071
• 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
• 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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June 1, 2010
Sept. 30, 2014
~ 25% Complete
FY10: $100,000
FY11: $125,000
FY12: $200,000
No ARRA Funding
Ft-A. Feedstock Availability and Cost
Ft-B. Sustainable Production
Bt-K. Biological Process Integration
NREL, March, 2008, Pic #15689
DOE OBP HQ and GO
Algae Project PIs
National Labs (INL, PNNL, ANL, etc)
Industrial Partner(s) (undisclosed)
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• Multiple algae economic studies have been conducted, with enormous variation
• This project leverages several prior research activities:
• Aquatic species program (ASP)
• DOE Biomass Algal Roadmap
• Analysis conducted for EPA under RFS II
• Conceptual models developed from scratch
• Phased approach:
1) Develop baseline models using best available data
2) Peer review models
3) Incorporate technologies under development
4) Assist in cost target development
$50
$45
$40
$35
$30
$25
$20
$15
$10
$5
$0
Triglyceride Production Cost
Average = $19.25 USD/gal
Variability is wide; Std. Dev. =
$28.8 USD/gal
Courtesy Amy Sun (Sandia)/ Phil Pienkos (NREL)
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• 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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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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0.05% (OP)
0.4% (PBR)
CO2
Makeup water
Algae
Growth
Settling
1%
Flocculent
10%
DAF
Makeup solvent
20%
Centrifuge
Lipid
Extraction
Recycle water
Blowdown
Solvent recycle
Phase
Separation
Spent algae
+ water
Anaerobic
Digestion
Makeup nutrients
Recycle nutrients/ water
Sludge
Solvent
Recovery
Biogas for energy
Raw oil
Hydrogen
Offgas
Naphtha
Upgrading
(hydrotreater)
Diesel
Flue gas from turbine
Power
Green = algae cell density
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Growth stage
•Open ponds:
•
Unlined raceways
•
Paddle wheel mixing
•
20 cm depth
• CO
2
• CO
2 feed via sumps, spargers scrubbed from “nearby” source
•PBR
•
Tubular design
•
8 cm ID x 80 m sections
• Plastic tubes (“low” cost)
•
Temp control via sprinklers
Shen et al (2009), “Microalgae mass production methods”
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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Sugar stream
Algae
Growth
Vent
5%
Concentration
(centrifuge)
Makeup solvent
20%
Lipid
Extraction
Air
Water/solubles
Recycle nutrients/ water
Solvent recycle
Phase
Separation
Spent algae
+ water
Anaerobic
Digestion
Makeup nutrients
Sludge
Solvent
Recovery
Raw oil
Hydrogen
Offgas
Naphtha
Upgrading
(hydrotreater)
Diesel
Biogas for energy
Flue gas from turbine
Power
Green = algae cell density
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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 m 3 /tank
• Concentration via centrifuge from 5%  20%
• All other downstream units equal to AT cases
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Scale of production [MM gal/yr algal oil]
Algae productivity
Algal cell density [g/L]
Lipid content [dry wt%]
CO
2 consumed [lb/lb algae]
Operating days/yr
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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Open pond
10
25 [g/m 2 /day]
0.5
25%
1.9
330
Base case
PBR
10
1.25 [kg/m 3 /day]
4
25%
1.9
330
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
11

Minimum Fuel Selling Price
$25
$20
$15
$10
$5
$0
$8,52
OP
(TAG)
$18,10
PBR
(TAG)
$9,84
$20,53
OP
(Diesel)
PBR
(Diesel)
Baselines show high costs of today’s currently available technologies, opportunities for cost reduction
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$21
$9
$24
Direct Installed Capital, MM$ (Ponds)
$22
$30
$12
$41
Ponds
CO2 Delivery
Harvesting
Extraction
Digestion
Inoculum System
Hydrotreating
OSBL Equipment
Land Costs
Operating ($/gal of product) $23 $16
Total = $195MM
Capital ($/gal of product)
$108
Direct Installed Capital, MM$ (PBR)
$522
PBR system
CO2 Delivery
Harvesting
Extraction
Digestion
Inoculum System
Hydrotreating
OSBL Equipment
Land Costs
Total = $631MM
12

Yield
Lipid production [MM gal/yr]
Diesel production [MM gal/yr]
Land Use:
Pond/PBR/Fermentor land use [acre]
Total plant land required [acre]
Resource Assessment:
Net makeup water demand [MM gal/yr] 1
-Water evaporated [gal/gal lipid]
-Water blowdown to treatment/discharge [gal/gal lipid]
Fresh CO2/ sugar demand [ton/yr] 2
Power coproduct [MM kwh/yr] 3
Naphtha coproduct [gal/yr]
System cost:
Total capital cost (direct + indirect) [$MM]
Net operating cost [$MM/yr]
-Coproduct credit [$MM/yr]
1.
Includes evaporation (consumptive loss) plus blowdown (treated offsite)
2.
After recycling turbine flue gas + digestion effluent
3.
After considering all ISBL facility power demands; includes CO
2 capture step (autotrophic).
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Open pond
10.0
9.3
4,820
7,190
10,000
570
430
145,000
80
340,000
$390
$37
$6
PBR
10.0
9.3
4,820
7,190
3,000
250
50
145,000
100
340,000
$990
$55
$7
Heterotrophic
13.1
12.2
13

$14
$12
$10
$8
$6
$4
$2
$0
$20
$18
$16
Cost of TAG: Alternative Growth Cases
1.25 g/L/day
25% TAG
25 g/m 2 /day
25% TAG
40 g/m 2 /day
50% TAG
60 g/m 2 /day
60% TAG
Operating ($/gal of lipid)
Capital ($/gal of lipid)
Land ($/gal of lipid)
2.0 g/L/day
50% TAG
3.0 g/L/day
60% TAG
OP
(base)
OP
(aggressive)
OP
(max growth)
PBR
(base)
PBR
(aggressive)
PBR
(max growth)
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Open Pond Sensitivities
Lipid content (50 : 25 : 12.5%)
Growth rate (50 : 25 : 12.5 g/m2/day)
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)
More “bang for the buck” targeting lipids vs growth rate
(Realistically, cannot maximize both simultaneously)
-$6 -$4 -$2 $0 $2 $4 $6 $8
Change to TAG production cost ($/gal)
[1] Benemann, J. et al., “Systems and Economic Analysis of Microalgae Ponds for Conversion of CO
2 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
$10
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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%)
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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Tube cost = 50% of total production cost
-$5 $0 $5 $10
Change to TAG production cost ($/gal)
$15 $20
16

• 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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– 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
– 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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• 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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• 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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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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