Locationdependent Synthesis of Biorefinery Networks Mariona Bertran John
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 3 rd Workshop on Pro. Bio. Refine |
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 Increase 7 x Electricity demand Water demand GHG emissions Siirola (2012) Proc 11 th Symp PSE (Ed Karimi and Srinivasan) 1
The Design Challenge PROCESS Biomass CO 2. . . New process synthesis-design problems arise from: (i) Switch to renewable raw materials (biomass, CO 2) (ii) Discovery of new technologies (catalysts, solvents, bioprocesses) (iii) New design objectives and constraints (sustainability)
Design Problem Formulation The decision-making nature of the process design problem makes it an optimization problem Problems: LP, NLP, MINLP, Simulation… Solution strategies: simultaneous, decomposition-based
Process Synthesis Needs Problem Identify alternatives Mathematical model Database Solution Need: Superstructure representation Solution strategy Need: Generic process model Need: Integration with an optimization environment
1. Superstructure Representation The Processing Step-Interval Network (PSIN) representation is suitable for a wide range of problems Generic processing interval separations mixing Quaglia et al. Comput Chem Eng, 2014 Bertran et al. Comput Chem Eng, 2017 reaction
2. Generic Process Model A generic process model can represent multiple process options at various scales Bertran et al (2016) Computer Aided Chemical Engineering
3. Optimization Problem 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
Data Management Databases are used to collect existing process data to make it readily available Superstructure of alternatives Problem Need: Knowledge Database management Solution Model Solution strategy Bertran et al. Computers and Chemical Engineering (submitted).
Data Management with Databases Process Step steps Feedstocks Data Components Products Locations Utilities Components 71 Technologies Interval Location Properties Utilities Inlet material stream Outlet material stream Utilities Reaction sets Biorefinery Database Location Properties Countries Properties 4 Reactions Processing steps 21 MW Name Cp data Feedstock data Processing 102 Mixing dataintervals Reaction data Product Waste data BP Hvap Code Feedstocks 11 Demand Compound Added. Availability Reaction. . . Products 9 Key Specs Composition Fraction Reference Reactions 63 reactant Locations Ratio Price Conversion Price 10 Cp Separation Reaction data Hvap Stoichiometry Compound. . . Catalyst Recovery … Utilities data Utility Ratio … Bertran et al. Computers Chemical Eng (Submitted)
Super-O Bertran et al. Computers and Chemical Engineering (submitted).
Super-O Problem Superstructure of alternatives Super-O Database Solution Model Solution strategy
Conceptual Examples
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?
Biomass to Chemicals
Synthesis Constrained to a Single Location* *synthesis problem solved for different locations
New (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
Example: Biomass to Ethanol Bertran et al. Computers and Chemical Engineering (submitted).
Adding Transportation
Distributed Production Transportation
Revisit: Biomass to Ethanol
1. No Transport Cost 152 kt/y ethanol Raw material 700 kt/h cassava rhizome Pretreatment Process Product Profit 91. 19 M$/y Bertran et al. , AICh. E Annual Meeting, 2017
2. Transport Product: Process based in Asia 63 kt/y ethanol Raw material 602 kt/y cassava rhizome 98 kt/y sugarcane bagasse 100 kt/y ethanol Pretreatment Process Product Profit 30. 90 M$/y Bertran et al. , AICh. E Annual Meeting, 2017
3. 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$/y Bertran et al. , AICh. E Annual Meeting, 2017
4. Transport Intermediate: Process based in N. America 700 kt/y wheat straw 135 kt/y ethanol Raw material Pretreatment Process Product Profit 30. 90 M$/y Bertran et al. , AICh. E Annual Meeting, 2017
Overview of Problems / Applications • Synthesis of a new process • Selection of potential products • Supply-chain management • Distributed production • Process retrofitting • Plant allocation • … Pharma processes Water management Chemical processes CO 2 utilization Biorefinery
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.
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