Biorefinery Networks Mariona Bertran John M Woodley and Rafiqul Gani Department of Chemical and Biochemical Engineering Technical University of Denmark DTU DK2800 Lyngby ID: 803188
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Slide1
Location-dependent Synthesis of Biorefinery Networks
Mariona
Bertran
, John
M.
Woodley and
Rafiqul Gani
Department
of Chemical and Biochemical
Engineering
Technical
University of Denmark (DTU
)
DK-2800
Lyngby
Denmark
Slide2The Current Global SituationSiirola (2012) Proc 11th
Symp
PSE (Ed Karimi and Srinivasan) 1
6-7 x
5-6 x
3.5 x
7 x
Increase
Global GDP growth over next ~50 years
(in constant dollars)
Production capacity for most commodities
(steel, chemicals, lumber, etc.)
Energy demand
Water demand
Electricity demand
Increase
GHG emissions
Slide3The Design Challenge
PROCESS
Biomass
CO
2
...
New
process
synthesis
-design
problems
arise
from
:
(i) Switch
to renewable raw materials (biomass, CO2
)
(ii)
Discovery
of new technologies (catalysts,
solvents, bioprocesses)
(iii) New
design objectives and constraints (sustainability)
Slide4Design Problem FormulationThe decision-making
nature of the
process
design problem
makes it an optimization
problem
Problems
:
LP, NLP, MILP, MINLP, Simulation…
Solution
strategies
:
simultaneous
,
decomposition-based
Slide5Process Synthesis Needs
Problem
Solution
Need
:
Superstructure
representation
Need: Generic process
modelNeed
: Integration with an optimization
environment
Slide61. Superstructure
Representation
The Processing Step-Interval Network
(PSIN) representation
is suitable for a wide range of problems
mixing reaction
Generic processing interval
Quaglia
et al
.
Comput
Chem
Eng
,
2014
Bertran
et al
.
Comput
Chem
Eng
, 2017
separations
Slide72. Generic Process Model
A
generic
process
model can
represent multiple
process options at various
scales
Bertran
et al (
2016)
Computer Aided
Chemical Engineering
Slide83. Optimization Problem
A generic process model can represent multiple process options at various scales
Composition, availability
and demand constraints
Superstructure connections
Process interval model
Objective function
Location dependent
/
Location independent
Slide9Data Management
Databases
are
used to collect
existing
process data to make
it readily
available
Bertran
et al.
Computers and Chemical Engineering (submitted
).
Problem
Solution
Need
:
Knowledge
management
Slide10DataBiorefinery DatabaseComponents
71
Utilities
4
Processing steps
21Processing intervals
102
Feedstocks11
Products9
Reactions63
Locations
10
Data
Management with
Databases
Bertran et al. Computers Chemical Eng
(
Submitted)
Process steps
Technologies
Mixing data
Reaction data
Waste data
Separation data
Added
Reference
Ratio
Reaction
Key reactant
Conversion
Compound
Fraction
Compound
Recovery
Inlet material stream
Outlet material stream
Utilities data
Utility
Ratio
…
Process steps
Technologies
Mixing data
Reaction data
Waste data
Separation data
Added
Reference
Ratio
Reaction
Key reactant
Conversion
Compound
Fraction
Compound
Recovery
Inlet material stream
Outlet material stream
Utilities data
Utility
Ratio
…
Step
Interval
Mixing data
Reaction data
Waste data
Separation data
Added
Reference
Ratio
Reaction
Key reactant
Conversion
Compound
Fraction
Compound
Recovery
Inlet material stream
Outlet material stream
Utilities data
Utility
Ratio
…
Feedstock data
Availability
Composition
Price
Products
Location
Product data
Demand
Specs
Price
Feedstock data
Availability
Composition
Price
Products
Location
Product data
Demand
Specs
Price
Feedstocks
Location
Feedstock data
Availability
Composition
Price
Products
Location
Product data
Demand
Specs
Price
Utilities
Properties
Cp
Hvap
...
Components
Properties
Reaction sets
Reactions
MW
BP
...
Utilities
Properties
Cp
Hvap
...
Components
Properties
Reaction sets
Reactions
MW
BP
...
Utilities
Properties
Cp
Hvap
...
Components
Properties
Reaction sets
Reactions
MW
BP
...
Reaction data
Stoichiometry
Catalyst
…
Locations
Countries
Name
Code
...
Slide11Super-OBertran et al.
Computers and Chemical Engineering
(
submitted
).
Slide12Super-O
Super-O
Problem
Solution
Slide13Conceptual Examples
Slide14Application ProblemsWhich biomass-derived feedstocks can be used?
Where are they available?
What are the different routes to convert the feedstocks
to the product?
What are the processing technologies available?
Is the solution location-dependent?Which set of feedstock-topology-location is optimal?
Slide15Biomass
to
Chemicals
Slide16Synthesis
Constrained
to a
Single Location
*
*synthesis problem solved for different locations
Slide17New (more flexible)
Model
Input information:
Network
data (steps, intervals, connections);
Processing
data (performance of alternatives);
Supply/demand
data (availability, demand, market price);
Location
data (distances, transport prices)
Output information:
Optimal
processing route (steps & technologies);
Flowrates;
Capacities
of technologies;
Environmental impacts,
LCA
indicators;
Location of each section; Economics (revenue, capital costs, operating costs, waste handling costs, transport costs,
…)
Allows to investigate many more scenarios
Slide18Example: Biomass to
Ethanol
Bertran
et al.
Computers and Chemical Engineering (
submitted).
Slide19Transportation
Transportation
Adding Transportation
Slide20Transportation
Transportation
Transportation
Distributed
Production
Slide21Revisit: Biomass to Ethanol
Slide221. No Transport Cost
152 kt/y ethanol
700 kt/h cassava rhizome
Bertran et al.,
AIChE
Annual
Meeting, 2017
Raw material
Pretreatment
Process
Product
Profit 91.19 M$/y
Slide232. Transport Product: Process based in
Asia
602
kt
/y cassava rhizome
98
kt
/y sugarcane bagasse
63 kt/y ethanol
100 kt/y ethanol
Raw material
Pretreatment
Process
Product
Profit 30.90 M$/y
Bertran et al.,
AIChE
Annual
Meeting, 2017
Slide243. Transport Product:
Process Based
in
N. America
700
kt
/y wheat straw
152 kt/y ethanol
Raw material
Pretreatment
Process
Product
Profit 84.90 M$/y
Bertran et al.,
AIChE
Annual
Meeting, 2017
Slide254. Transport Intermediate: Process based in
N. America
700 kt/y wheat straw
135 kt/y ethanol
Raw material
Pretreatment
Process
Product
Profit 30.90 M$/y
Bertran et al.,
AIChE
Annual
Meeting, 2017
Slide26Overview of Problems / ApplicationsSynthesis
of a new
process
Selection
of potential productsSupply-
chain managementDistributed
production
Process retrofitting
Plant allocation
…
Slide27Concluding RemarksA framework
for biorefinery process synthesis using
superstructure optimization has been developed.
The
associated methods and tools are: superstructure representation,
generic process model, data management system.
A software implementation of the framework is available (Super-O).
The framework has been exemplified in a series of
applications.
Options for transportation
between locations to be developed further.We are interested in
collaboration, to build the database and refine information.