Process Simulation of Biomass Fast- Pyrolysis into Transportation Fuels Carlos E. Aizpurua 1, Hoyong Kim 1, Stephen S. Kelley 1, Hasan Jameel 1, Mark M. Wrigth 2, and Sunkyu Park 1. 1 Department of Forest Biomaterials, North Carolina State University. Raleigh, NC. 27695, USA 2 Department of Mechanical Engineering, Iowa State University. Ames, IA. 50011, USA The IBSS Partnership is supported by Agriculture and Food Research Initiative Competitive Grant no. 2011-68005-30410 from the USDA National Institute of Food and Agriculture.
OUTLINE Year 3 Progress Year 4 Objectives NC STATE Approach Process Simulation Empirical Equations Preliminary Results Accomplishments to Date Future Work
Year 3 Objectives To develop a gasification process model that is sensitive to the composition of the biomass. Use this model to estimate the yield of biofuels. Use this model to estimate the power co-production (generation or consumption) and emission of GHG, water, and other pollutants from a biofuel production plant. Use gasification model to estate the LCA burdens associated with biofuel production.
Progress Against Objectives Modify the DOE NREL gasification model to account for MC and ash, but not composition. Used process model to estimate biofuel production as a function of MC and ash levels in the biomass. Used the process model to estimate the power production and emissions as a function of MC and ash. Worked with the LCA team to conduct a full LCA of different biomass feedstocks and production alternatives.
Year 4 Objectives To develop a fast-pyrolysis model that is flexible to the changes in biomass chemical composition. This model will allow us to understand the reaction pathway and the effects of feedstock variations (ash, carbon content, and so on) on the final product and life cycle analysis LCA (overall water/nitrogen/carbon)
Year 4 Objectives In order to do so We have collected data and information around process simulation of fast-pyrolysis from: In conjunction with our lab data that will be used to feed our own model
Year 4 Objectives Fast Pyrolysis Bio-oil Upgrading Heat Integration NREL 2006-2010 Biomass Bio-oil Bio-oil Fuels Cooling water, steam/power, waste water NREL 2010 Single Stage Hydrocracker (C8-C10) NREL 2006-2010 NCSU-ISU 2014 PNNL 2013 Multiple Steps Hydrotreat. (Gasoline/Diesel)
Summary of the models 1 NREL 2006 Includes only the pyrolysis oil production (mass balance and heat integration). The result of this model is not affected by the change in biomass properties such as biomass composition, moisture content, etc. 100 WOOD 0.294162 H 2 + 0.23417 CO + 0.12317 CO 2 + 0.6 H 2 O + 0.012143 NH 3 + 0.002174 CH 4 + 0.005072 C 2 H 4 + 0.003623 C 3 H 6-2 + 0.09871 C 2 H 4 O 2-1 + 0.09871 C 3 H 6 O 2 -D + 0.00494 C 7 H 8 O 2 -E + 0.07403 CH 2 O 2 + 0.09076 C 10 H 12 O 3 + 0.02468 C 7 H 8 + 0.19742 C 5 H 4 O 2 + 0.00987 C 6 H 6 + 0.1516 CHAR + 0.01531 ASH + 0.02468 C 8 H 10 O 3 + 0.00494 C 6 H 6 O
Summary of the models 2 NREL 2010 Robust model that includes the pyrolysis oil production and its upgrading. Same assumptions on bio-oil composition were used from the 2006 model. Hydrogen is produced by reforming ~38% of the produced bio-oil. 10 model compounds were chosen for the organic fraction, where the biggest molecule is a C10. Final upgraded product includes only n-octane and n-decane.
NREL 2010 H 2 is produced with a fraction of the biooil. Single Stage Hydrocracking, Less H 2 consumption
NREL 2006-2010 Compounds selection: Gas compounds Bio-Oil compounds Hydrocracking Product Oxygen O2 Acetic Acid C2H4O2 N-octane C8H18 Nitrogen N2 Acetol C3H6O2 N-decane C10H22 Carbon Dioxide CO2 Guaiacol C7H8O2 Carbon Monoxide CO Syringol C8H10O3 Methane CH4 Formic Acid CH2O2 Ethylene C2H4 Coniferyl Alcohol C10H12O3 Hydrogen H2 Phenol C6H6O Propane C3H8 Toluene C7H8 Water Butene C4H8 Benzene C6H6 Char/Ash Ammonia NH3 Furfural C5H4O2 Wood
Summary of the models 3 PNNL 2013 Updated from the NREL 2010 model. Biomass input is still the same. The result is only dependent on biomass amount, not biomass composition. 14 model compounds were chosen from C4 to C21 in bio-oil fraction. Bio-oil upgrading to transportation fuels includes a low temperature stabilizer, two-stage hydrotreaters, and a hydrocracking unit for the biggest molecules. The product from the upgrading is a mixture of liquids spanning the gasoline and diesel range.
PNNL 2013 Converts carbonyls and olefins with low H 2 Conversion is completed with low H 2 Converts remaining oxygenated compounds and saturates aromatics
PNNL 2013 Hydrogen is produced via steam reforming of process Off-gases generated in hydrotreating and hydrocracking and additional natural gas.
PNNL 2013 Compounds selection: Gas compounds Bio-Oil compounds Model compound (simulation) Oxygen O2 Acids Crotonic Acid C4H6O2 Nitrogen N2 Alcohols 1,4-Benzenediol C6H6O2 Hydrogen H2 Ketones Hydroxyacetone C3H6O2 Carbon Dioxide CO2 Aldehydes 3-methoxy-4-hybenzaldehyde C8H8O3 Carbon Monoxide CO Guaiacols Isoeugenol C10H12O2 Methane CH4 Low MW sugars Levoglucosan C6H10O5 Ethane C2H6 High MW sugars Cellobiose C12H22O11 Ethylene C2H4 Low MW lignin A Dimethoxy stilbene C16H16O2 Propane C3H8 Low MW lignin B Dibenzofuran (diphenyl comp.) C12H8O Propene C3H6 High MW lignin A Oligomeric comp.β-o-4 bond C20H26O8 Butene C4H8 High MW lignin B Phenylcoumaran comp. C21H26O8 N-butane C4H10 Extractives Dehydroabietic acid C20H28O2
The Approach NC STATE Hybrid model in Aspen that considers the best qualities of the three models mentioned. (1) simplicity of the NREL 2006 and 2010 model and (2) better defined bio-oil composition from PNNL 2013 model. We have developed (still working on) an empirical approach to predict fast-pyrolysis products based on biomass characterization.
The Approach Process Simulation Aspen Plus Modeling INPUT Component property data (thermodynamic properties) Stream data (Temp, pressure, flow rate, physical state, MC) Unit operations. Simulation of fuels from lignocellulosic biomass?? OUTPUT Product yield Product composition (%wt, %mol) Physical state. Water and process chemicals consumption. Power/Steam usage. We have to define the components that coexist in the streams throughout the process
The Approach Process Simulation Aspen Plus Modeling. Processes with Solids Chosen based on model compounds used on PNNL 2013 report.
The Approach Process Simulation Aspen Plus Modeling. Processes with Solids Component Attribute Stream Conditions
The Approach What occurs during every reaction step will be determined by the C and Ash content in the ultimate analysis DRY-WOOD 1005
Empirical Equations 100% Mass balance of pyrolysis products 80% 19.8 25.5 32.5 25.3 25.4 25.2 30.5 25.3 30.2 27.5 60% 26.4 19.0 12.9 14.0 10.5 10.2 9.0 13.8 10.1 8.2 40% 29.2 33.8 43.9 50.7 55.1 54.0 53.5 51.4 52.3 58.0 20% 24.6 21.7 0% Beech bark acacia bark acacia loblolly pine 10.7 10.0 9.0 10.6 7.0 9.5 7.4 6.3 sweetgum beech red maple switchgrass yellow poplar sourwood char organics water NCG
Empirical Equations Based on our lab data: 10 types of biomass used; 6 type of hardwoods, 2 hardwood barks, 1 softwood, and switch grass Sample loblolly pine Ultimate composition (wt%) C H N O Volatile matter Proximate composition (wt%) Fixed carbon Ash Fuel ratio DTGmax (wt/min) 48.4 4.7 0.09 46.3 86.1 13.3 0.6 15.4 70.1 switchgrass 46.6 5.1 0.29 46.6 82.6 15.9 1.4 19.3 64.1 acacia 48.4 4.9 0.22 45.9 80.6 18.8 0.6 23.3 72.0 beech 48.2 5.4 0.12 45.8 84.1 15.3 0.5 18.2 75.2 red maple 47.4 5.0 0.09 47.2 87.7 12.0 0.3 13.7 79.1 sourwood 46.9 5.0 0.08 47.5 89.2 10.3 0.5 11.5 82.7 Sweetgum 46.4 5.1 0.10 47.7 87.2 12.1 0.8 13.9 76.8 yellow poplar 47.1 5.0 0.14 47.2 85.5 13.9 0.6 16.2 73.1 acacia bark 49.9 4.8 1.35 40.7 74.9 21.9 3.3 29.2 53.4 beech bark 44.5 4.9 0.43 42.9 74.3 18.4 7.4 24.7 43.4 Note: O%=100%-C%-H%-N%-Ash%; Fuel ratio=fc/vm*100%. 1 st order linear regression Water NCG Organics Char Intercept -29.84 12.97 197.44-80.57 Total Carbon 0.82 0.33-2.99 1.84 Ash 2.63-1.09-4.69 3.15 R square 0.94 0.55 0.93 0.98
Results from the simulation Effects of biomass variation on fast-pyrolysis products Ash 0.5% Carbon 47% Results from the empirical equations that were developed by experimental results. The organics and NCG composition remains constant same way as in the PNNL report (2013).
Results from the simulation Fast Pyrolysis Bio-oil Upgrading Heat Integration Biomass Bio-oil Bio-oil Fuels Cooling water, steam/power, waste water Corn Stover Harwood So.wood SWG Yield Gal/US dton 68 % 65 % 61 % 67 % 176.2 168.6 157.3 174.4 Yield 20 % 20 % 20 % 20 % Gal/US dton 42.6 40.8 38.1 42.1 Make- up water (gal/gal of fuel) 5.3 5.3 5.3 5.3 NREL 2010 PNNL 2013 65 % 76 % 169.1 220.6 25 % 33 % 49.3 85.4 It may vary from ~30 to ~100 depending on assump7ons Different biomass CS vs. Pine Different yield assump7ons USDA vs. Oasmaa 2010
Accomplishments to Date Fast Pyrolysis Bio-oil Upgrading Heat Integration NREL 2006-2010 Biomass Bio-oil Bio-oil Fuels Cooling water, steam/power, waste water NREL 2010 Single Stage Hydrocracker (C8-C10) NREL 2006-2010 NCSU-ISU 2014 PNNL 2013 Multiple Steps Hydrotreat. (Gasoline/Diesel) Mass Balance Mass Balance Energy Balance
Future work Need to address the limitations and work on improving the actual model. Find dependency of liquid fuel on the bio-oil chemical composition. To conduct a full LCA of the process to see the effects of feedstock variations.