Algal Biofuel Pathway Baseline Costs

1. 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

2. 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 • 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 NREL, Sept 15, 2010, Pic #18071

3. June 1, 2010 Sept. 30, 2014 ~ 25% Complete Ft-A. Feedstock Availability and Cost Ft-B. Sustainable Production Bt-K. Biological Process Integration Overview Barriers Timeline Budget Partners FY10: $100,000 FY11: $125,000 FY12: $200,000 No ARRA Funding DOE OBP HQ and GO Algae Project PIs National Labs (INL, PNNL, ANL, etc) Industrial Partner(s) (undisclosed) NREL, March, 2008, Pic #15689

4. Project Overview • 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: • Develop baseline models using best available data • Peer review models • Incorporate technologies under development • Assist in cost target development Courtesy Amy Sun (Sandia)/ Phil Pienkos (NREL)

5. 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

6. 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

7. Makeup water Hydrogen Makeup solvent Solvent recycle Flocculent Design Configuration: Autotrophic Offgas Raw oil Naphtha CO2 Algae Growth DAF Centrifuge Lipid Extraction Phase Separation Solvent Recovery Upgrading (hydrotreater) Settling Diesel Spent algae + water Biogas for energy 0.05% (OP) 0.4% (PBR) Recycle water Blowdown Flue gas from turbine Anaerobic Digestion Recycle nutrients/ water Makeup nutrients Power Sludge 10% 1% 20% Green = algae cell density

8. 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 • PBR • Tubular design • 8 cm ID x 80 m sections • Plastic tubes (“low” cost) • Temp control via sprinklers • 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 Shen et al (2009), “Microalgae mass production methods” Bryan Willson (2009), “Solix Technology Overview”

9. Hydrogen Makeup solvent Solvent recycle Design Configuration: Heterotrophic Vent Offgas Raw oil Naphtha Sugar stream Algae Growth Concentration (centrifuge) Lipid Extraction PhaseSeparation Solvent Recovery Upgrading (hydrotreater) Diesel Spent algae + water Water/solubles Biogas for energy Air Flue gas from turbine Recycle nutrients/ water Anaerobic Digestion Makeup nutrients Power Sludge 5% 20% Green = algae cell density

10. 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

11. Design Assumptions Autotrophic Heterotrophic

12. Baseline Cost Results Total = $195MM $108 Baselines show high costs of today’s currently available technologies, opportunities for cost reduction Total = $631MM

13. Results: Land, Resource, Cost Assessment • 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).

14. Sensitivity Analysis: Autotrophic

15. Sensitivity: Ponds More “bang for the buck” targeting lipids vs growth rate (Realistically, cannot maximize both simultaneously) [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

16. Sensitivity: PBR Tube cost = 50% of total production cost

17. 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

18. 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)

19. 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

20. 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

21. 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)