(410e) Life Cycle Optimization for Sustainable Design and Operations of Hydrocarbon Biorefinery Via Fast Pyrolysis, Hydrotreating and Hydrocracking | AIChE

(410e) Life Cycle Optimization for Sustainable Design and Operations of Hydrocarbon Biorefinery Via Fast Pyrolysis, Hydrotreating and Hydrocracking

Authors 

Slivinsky, M. - Presenter, Northwestern University
Wang, B., Northwestern University
You, F., Cornell University
Gebreslassie, B. H., University Rovira i Virgili



Life cycle
optimization for sustainable design and operations of

hydrocarbon
biorefinery via fast pyrolysis, hydrotreating and hydrocracking

Berhane H. Gebreslassie, Maxim Slivinsky, Belinda
Wang, Fengqi You*

Submitted to session 23B20 Biofuels Production: Design, Simulation, and Economic
Analysis

Abstract

As world energy demand grows despite finite fossil
fuel reserves, the development of new sources of energy is becoming ever more
critical, especially with growing concerns about climate change.  Biofuels
provide a promising alternative to fossil fuels for transportation due to their
compatibility with current infrastructure.  Hydrocarbon biofuels can be used in
gasoline and diesel engines, providing vehicle performance similar to that of
fossil fuels.  They also can use the current fuel distribution and utilization
infrastructure, including pipelines and pumping stations.  The advantage of
biofuels lays in their sustainability and lower life cycle greenhouse gas (GHG)
emissions than conventional fuels [1].  A larger
share of a nation's energy portfolio from biomass has the added benefit of
increasing energy independence.  Fast pyrolysis is a high temperature
thermochemical conversion in the absence of oxygen; it can potentially produce
biofuels at lower production cost and environmental impact than other biomass
conversion pathways.  This work addresses the design and optimization of
biomass conversion to biofuels through fast pyrolysis under two objectives: maximizing
net present value (NPV) and minimizing project global warming potential (GWP) [2].  This work
presents the first mathematical programming model for rigorous optimization of
a hydrocarbon bio-refinery via fast pyrolysis, hydrotreating, and
hydrocracking.

In this work a multi-objective nonlinear programming
model (NLP) is used for the optimal design and operation of hydrocarbon
bio-refinery using hybrid poplar as the feedstock.  This NLP is solved using
the ε-constraint method, using varying ε values to determine Pareto-optimal solutions given
the two objectives [3].  The economic objective takes into account feedstock
and utilities costs, selling price of biofuels, demand for products, and
processing limits [4, 5, 6].  The environmental
objective uses life cycle analysis (LCA), considering gate-to-gate
environmental impact analysis of the bio-refinery.  GWP is calculated using the
100 year timeframe per the Kyoto Protocol [7]. 

The hydrocarbon bio-refinery is composed of the
following units: pyrolysis, hydrotreating, separation and hydrocracking, and
steam reforming for hydrogen production [8, 9].  Gallon of
gasoline equivalent (GGE) is the functional unit for the bio-refinery products,
namely naphtha and diesel.  The optimization results show unit production costs
to be $2.31/GGE for the maximum NPV solution and $3.67/GGE for the minimum GWP
solution, and the resulting Pareto curve shows the tradeoffs between the two
objectives.  

References

[1]        Hsu,
D. D. (2012), ?Life cycle assessment of gasoline and diesel produced via fast
pyrolysis and hydroprocessing,? Biomass and Bioenergy, Vol. 45,
Pages 41?47

[2]        Gebreslassie,
B. H., Slivinsky, M., Wang, B., & You, F. (2013).
Life Cycle Optimization for Sustainable Design and Operations
of Hydrocarbon Biorefinery via Fast Pyrolysis, Hydrotreating and Hydrocracking.
Computers & Chemical Engineering, 50, 71-91

[3]        Gebreslassie, B. H., Yao, Y., and You, F. (2012)
"Design under uncertainty of hydrocarbon biorefinery supply chains:
Multiobjective stochastic programming models, decomposition algorithm, and a
Comparison between CVaR and downside risk," AIChE Journal, vol. 58,
pp. 2155-2179.

[4]        Wang,
B., Gebreslassie, B. H., & You, F. (2013). Sustainable
Design and Synthesis of Hydrocarbon Biorefinery via Gasification Pathway:
Integrated Life Cycle Assessment and Technoeconomic Analysis with
Multiobjective Superstructure Optimization.
Computers
& Chemical Engineering
, 52, 55?76

[5]        Gebreslassie,
B. H., Waymire, R., & You, F. (2013). Sustainable Design and Synthesis of Algae-Based Biorefinery for
Simultaneous Hydrocarbon Biofuel Production and Carbon Sequestration
AIChE
Journal
, 59, 1599?1621

[6]        You, F., & Wang, B. (2011). Life Cycle
Optimization of Biomass-to-Liquids Supply Chains with Distributed-Centralized
Processing Networks.
Industrial
& Engineering Chemistry Research
, 50, 10102?10127

[7]        Gian-Kasper, P., Stocker,
T., Midgley, P., & Tignor, M. (2009). IPCC expert meeting on

the science of alternative Q5 metrics.

[8]        Jones, S. B., Valkenburg,
C., Holladay, J. E., Stevens, D. J., Walton, C. W., Kinchin, C.,

et al. (2007). "Production of
gasoline and diesel from biomass via fast pyrolysis,

hydrotreating and hydrocracking: A
design case," In DE-AC05-76RL01830: Pacific

Northwest
National Laboratory and National Renewable Energy Laboratory.

[9]        Wright,
M. M., Daugaard, D. E., Satrio, J. A., Brown, R. C. (2010) ?Techno-economic
analysis of biomass fast pyrolysis to transportation fuels,? Fuel, Vol.
89, Supplement 1, 1, Pages S2?S10.




* Corresponding author. Email: you@northwestern.edu