1. 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

2. The Current Global Situation
6-7 x
Global GDP growth over next ~50 years (in constant dollars)
5-6 x
Production capacity for most commodities (steel, chemicals, lumber, etc.)
3.5 x
Energy demand
7 x
Electricity demand
Increase
Water demand
Increase
GHG emissions
Siirola (2012) Proc 11th Symp PSE (Ed Karimi and Srinivasan) 1

3. The Design Challenge PROCESS Biomass CO2 ...
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)

4. Design Problem Formulation
The decision-making nature of the process design problem makes it an optimization problem
Problems: LP, NLP, MILP, MINLP, Simulation…
Solution strategies: simultaneous, decomposition-based

5. Process Synthesis Needs
Identify alternatives
Mathematical model
Solution strategy
Database
Need: Superstructure representation
Problem
Need: Generic process model
Need: Integration with an optimization environment
Solution

6. 1. Superstructure Representation
The Processing Step-Interval Network (PSIN) representation is suitable for a wide range of problems
Generic processing interval
mixing reaction
separations
Quaglia et al. Comput Chem Eng, 2014
Bertran et al. Comput Chem Eng, 2017

7. 2. Generic Process Model
A generic process model can represent multiple process options at various scales
Bertran et al (2016) Computer Aided Chemical Engineering

8. 3. Optimization Problem Objective function Process interval model
A generic process model can represent multiple process options at various scales
Objective function
Process interval model
Composition, availability and demand constraints
Superstructure connections
Location dependent / Location independent

9. Superstructure of alternatives
Data Management
Databases are used to collect existing process data to make it readily available
Superstructure of alternatives
Model
Solution strategy
Database
Problem
Need: Knowledge management
The bottleneck is data management!
Solution
Bertran et al. Computers and Chemical Engineering (submitted).

10. Data Management with Databases
Process steps
Technologies
Mixing data
Reaction data
Waste data
Separation data
Added
Reference
Ratio
Reaction
Key reactant
Conversion
Compound
Fraction
Recovery
Inlet material stream
Outlet material stream
Utilities data
Utility …
Step
Interval
Components
Properties
Reaction sets
Reactions MW BP
...
Utilities Cp
Hvap
Reaction data
Stoichiometry
Catalyst …
Locations
Countries
Name
Code
Feedstock data
Availability
Composition
Price
Products
Location
Product data
Demand
Specs
Feedstocks
Utilities
Properties Cp
Hvap
...
Data
Biorefinery Database
Components 71
Utilities 4
Processing steps 21
Processing intervals
102
Feedstocks 11
Products 9
Reactions 63
Locations 10
Bertran et al. Computers Chemical Eng (Submitted)

11. Super-O
Bertran et al. Computers and Chemical Engineering (submitted).

12. Superstructure of alternatives
Super-O
Superstructure of alternatives
Model
Solution strategy
Database
Problem
Super-O
Solution

13. Conceptual Examples

14. Application Problems Which 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?

15. Biomass to Chemicals

16. Synthesis Constrained to a Single Location*
*synthesis problem solved for different locations

17. New (more flexible) Model
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, …)
Input information:
Network data (steps, intervals, connections); Processing data (performance of alternatives); Supply/demand data (availability, demand, market price);
Location data (distances, transport prices)
Allows to investigate many more scenarios

18. Example: Biomass to Ethanol
Bertran et al. Computers and Chemical Engineering (submitted).

19. Adding Transportation

20. Distributed Production
Transportation

21. Revisit: Biomass to Ethanol

22. 1. No Transport Cost Profit 91.19 M$/y 152 kt/y ethanol Raw material
700 kt/h cassava rhizome
Pretreatment
Process
Product
Profit M$/y
Bertran et al., AIChE Annual Meeting, 2017

23. 2. Transport Product: Process based in Asia
602 kt/y cassava rhizome 98 kt/y sugarcane bagasse
63 kt/y ethanol
Raw material
100 kt/y ethanol
Pretreatment
Process
Product
Profit M$/y
Bertran et al., AIChE Annual Meeting, 2017

24. 3. Transport Product: Process Based in N. America
700 kt/y wheat straw
152 kt/y ethanol
Raw material
Pretreatment
Process
Product
Profit M$/y
Bertran et al., AIChE Annual Meeting, 2017

25. 4. Transport Intermediate: Process based in N. America
700 kt/y wheat straw
135 kt/y ethanol
Raw material
Pretreatment
Process
Product
Profit M$/y
Bertran et al., AIChE Annual Meeting, 2017

26. Overview of Problems / Applications
Synthesis of a new process
Selection of potential products
Supply-chain management
Distributed production
Process retrofitting
Plant allocation …
Biorefinery
CO2 utilization
Chemical processes
Water management
Pharma processes

27. Concluding Remarks
A 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.