Master thesis in biorefinery pathways selection using MILP with Integer-Cuts constraint method
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Transcript of Master thesis in biorefinery pathways selection using MILP with Integer-Cuts constraint method
Optimum biorefinery pathways
selection using MILP with
Integer-Cuts constraint method
Student:
Stefano Maronese Supervisors:
Andrea Lazzaretto
François Maréchal
Adriano Viana Ensinas
Project outline
1. Study of Biorefinery technologies
2. Create a superstructure of different pathways to convert
biomass into useful products
3. Define a methodology to select and rank different technologies
for converting biomass according to the objective function.
A rank enlarge the view and help in the decision process
Method robust and fast → MILP.
4. Apply the method to a case study: evaluate the best
technologies to convert wooden biomass (Switzerland)
Objective: systematic generation of a rank of pathways creating a
light and quick tool.
Tool: software developed @LENI and applied to the OSMOSE
Wood2CHem Platform, a joint project between SNSF, EPF Lausanne
and ETH Zurich.
The biorefinery concept
Biorefinery is the sustainable processing of biomass into a
spectrum of marketable products (food, feed, materials,
chemicals) and energy (fuels, power, heat)“ (IEA 2009)
Biorefineries are designed to be sustainable in the whole chain,
thus maximizing the efficiency and minimizing the waste.
The OSMOSE Wood2CHem Platform is a tool for joining numerous
models to create complex energy systems.
Elements of the structure:
Units
Represent the conversion processes
Layers
Mass and energy balance nodes
Streams
Connect units and layers
Type of unit inside the platform:
Process unit (technologies)
Resource unit (input)
Service unit (output)
The tool: OSMOSE Wood2CHem Platform
The tool: OSMOSE Wood2CHem PlatformCreating the superstructure
Steps to build a process unit for the Wood2CHem Platform:
1. Create flow-sheet model of the process (or take it from literature)
2. Set the boundary of the system and analyse the cross-boundary flows
3. Extract input/output data (mass, energy, economics)
4. Create the black box model to be plugged into the platform
ElectricityInvestment
Maintenance
Labour
Acknowledgement: FICFB gasifier and SNG synthesis (PhD thesis Gassner 2009)
The tool: Wood2CHem Platform models
Wood SNG
MILP problem statement
Objective function:
Subject to:
With:
Parameters:
• Efficiency (supposed constant)
• Investment and operating cost (supposed linear)
• Prices of resources and products
• Stream reference value es+ (scaled by fs)
Variables:
• multiplication factor
(real)
• unit use
(integer)
Existence of subsystem
Mass/energy balance at layers
positive (cost in
resource unit) or
negative
(revenue in
service unit)
Cost function linearized in the range [fmin, fmax]
Generate multiple pathways: Integer-Cuts Constraint
Integer Cut (original):
Single condition
‼ Non linear function
Integer Cut (Fazlollahi et al. 2012)
Linear
‼ Number of constraints increases at each run
Generate multiple pathways: computational issues
Definition of solution used to analyze the output of the Platform:
Simple solution: only one process utility;
Complex solution: two or more processes of different kind in parallel
Meaningless solution: two or more process of the same kind in parallel
(same kind: same input and output)
Fake solution: size of the unit is too small (or at least zero). Most
outstanding example of fake solution: combination of unit use=1 and unit
mult=0
Because of fake solutions, the Platform is slow. The solver analyzes all the
combinations of integer that gives the optimal solution before moving to
the sub-optimal one.
Unit 1
Unit 2
Unit 3
Unit 1 Unit 2 Unit 3
Solution f y f y f y1 S1 1 S2 1 0 0
2 S1 1 S2 1 0 1
3 S1 1 0 0 S3 1
Fake solution:
unit 3 is active
but size is zero
Generate multiple pathways:
Adding constraints to accelerate the Platform
Method to speed up needed → Additional constraints
Set a minimum size of each process:
Fake solution avoided
‼ Do not reduce the number of runs
Epsilon constraint:
Reduce number of runs
‼ Not reliable (loss of solutions!)
Sum of unit use:
Reduce number of runs
‼ Np must be chosen accordingly
Tests proved that ICC + fmin>0 + Σy≤Np are the best set of
constraints → rank of solutions in the shortest time
Case Study
Technologies and
superstructure for
converting wood into
energy products:
SNG
Methanol
DME
FT
Several configuration
for each technology.
Case Study: input dataThe superstructure is made of three sub-models:
1. Wood model → assess wood cost (harvesting + transport) and availability (Resource unit);
2. Techno-economic models of the processes → assessing efficiency and cost of each technology (Process Units)
3. Market condition → assessing prices for the products (Service units)
Parameter MeOH-a MeOH-b MeOH-c MeOH-d FT-EF_ind FT-EF_dir FT-a FT-b FT-c DME SNG-a SNG-b
Technology FICFB FICFB CFB CFB EF EF CFB CFB FICFB FICFB FICFB CFB
Output [kW/MW] 570 570 318 318 637 458 303 352 601 561 693 750
Electricity [kW/MW] -85 -59 -18 35 -14 55 155 126 -4 -48 37 26
20 MW biomass plant
Investment [M€] 27 28 15 15 7 10 11 12 19 23 24 16.6
400 MW biomass plant 100 MW biomass plant
Investment [M€] 365 363 156 136 88 101 115 133 295 311 103 51
Case Study: 20 MW input biomass
Top 10 solutions
FT-a + Eout
FT-b + Eout
FT-EFdir + Eout
SNG-a + Eout
Ein + FT-EFind
MeOH-d + Eout
FT-EFind + MeOH-d
FT-EFind + SNG-a
FT-a + MeOH-b
FT-EFind + SNG-b
Case Study: 200 MW input biomass
Top 10 solutions
FT-a + Eout
FT-b + Eout
SNG-a + Eout
MeOH-d + Eout
FT-EFdir + Eout
FT-a + MeOH-b
MeOH-b + SNG-a
FT-b + MeOH-b
MeOH-a + SNG-a
Ein + FT-EFind
Conclusions I
Methodology to generate pathways to convert
wooden biomass according to the objective function:
Rank of pathways obtained;
Optimal set of constraint developed (form -40% to -45%
computational time);
No loss of solutions;
Light and robust tool to analyse different concept and
technologies;
First analysis performed according to simple models.
Conclusions II
Conclusions from the case study
Trend in technologies is defined:
For Switzerland Fischer-Tropsch is the best conversion
process (but FT fuel needs further refinement)
Then comes SNG and MeOH
DME is the worst technology (any size)
Break even price of wood is from 30% (20 MW) 10% (200
MW) lower than wood cost
Break even price for the fuel produced is from 50% (20
MW) to 20% (200 MW) higher than the fossil counterparts.
Conclusions III – Perspectives & future research
The Wood2CHem Platform, as it was developed, opens a broad
variety of future developments:
Short term: expand the platform adding more processes in
series → compare different products and add recirculating
flows
Mid term: More detailed approach → Add energy integration
Long term: uncertainty in cost estimation → Depict scenarios
to assess most promising technologies that worth developing