Bio4Energy Process Integration Platform
Advanced techniques for process integration
Andrea Toffolo
Energy Engineering
Division of Energy Science
Department of Engineering Sciences & Mathematics
Luleå University of Technology, SWEDEN
E-mail: [email protected]
Bio4Energy miniconference, Umeå, 25 October 2011
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Outline of the presentation

background

past research activity on energy systems

plans for the process integration platform of the Bio4Energy project
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Background
University of Padova, ITALY
1996
5-year degree in Mechanical Engineering
1996-2000
consultant (university, engineering company)
2000-2002
PhD in Energetics
2002-2005
research fellow
2005-2011
hired external professor
Luleå University of Technology, SWEDEN
2011professor in the Energy Engineering subject
author or co-author of >30 papers in international journals
2007
ASME Obert Award
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Research interests

modeling and analysis of energy systems
combined cycle power plants, advanced cycles (HAT, S-Graz),
ORCs for geothermal binary plants
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Research interests

diagnosis of energy system malfunctions
3 techniques to locate the origin of malfunctions:
- thermoeconomic indicators
- evolutionary algorithms
- fuzzy expert systems (automatic generation of rules)

synthesis/design optimization of energy systems
- ad hoc multi-objective evolutionary (or hybrid) algorithms
- optimization of the design parameters
- synthesis of components into system flowsheet
- synthesis of HENs
- process integration
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flowsheet
(two pressure level
combined cycle)
The HEATSEP method


it suggests to separate the heat transfer
section of the system from the rest of
the flowsheet
system flowsheet is decomposed into
-
-
a “basic configuration” which comprises
all the fundamental components that are
not involved in heat transfers
(basic components)
an unspecified “black-box” in which all
heat transfer processes are assumed
to occur
basic configuration
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The HEATSEP method (thermal black-box)



all heat transfer devices are replaced by “thermal cuts”,
which interrupt the thermal link between two subsequent
basic components
this generates potential hot and cold thermal streams
that interact in the undefined black-box
the synthesis of the heat exchanger
network inside the black-box can
be treated separately from the
synthesis/design of the basic
configuration (which involves
the conditions at the boundaries
of the black-box as well)
thermal cuts
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The HEATSEP method (basic configuration)


in the basic configuration of energy conversion systems
the basic components are found to be organized
according to elementary thermodynamic cycles
this means that
-
-
the basic configuration is in general
the outcome of the superimposition
of a set of elementary cycles
the overwhelming number of possible
combinations of the basic components
is drastically reduced
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The HEATSEP method (basic configuration)
GAS TURBINE
30
H2O RECOVERY
HRSG
25
26
To
Saturator
MG
QFUEL

QMUHRSG
mNOX
mIC
External
Make-up
Water
32
in the basic configuration of industrial processes the basic components
are found to be organized into sub-processes
having a predefined
STEAM
SECTION
configuration with given hot and cold thermal
streams (which are
included in the black-box)
HPT
DEAER
ATOR
MG
LPT
Exhaust
to HRSG
IC
Air
Exhaust
to Recovery
CCR
CC
C
1
2
Recovered
H2O
Exhaust
from HRSG
6
5
27
To
Stack
7
GASESDP
GASESCND
28
33
QMHP
QMIP
29
To
Reformer
From
Reformer
3
To
Stripper
Reboiler
mREF
4
From
Stripper
Reboiler
SYNREF
22
MG
M
SATURATOR
31
20
Natural Gas
(ISO conditions)
QSYNREF
24
21
8
SAT
QMSAT
19
Isothermal
volumetric
Compressor
Make-up
Water
34
Steam to
reactive
mixture
QMUSAT
18
Compressed
Natural Gas
(50 bar)
black-box
9
QMREF
REFORMING
H2OW
Excess
Wash
Water
WASH
RAW2
12
QNG
PCC
10
ABSORPTION/
STRIPPING/
COMPRESSION
14
15
HTS
LTS
REF
11
Syngas
without
CO2
DIOX2
M
DIOX1
Liquid
CO2
Gas
CO2
17
Make-up
MEA
CROW
STR
Recovered H2O
to Wash Column
QHTS
ABS
Reformed
Gas with CO2
MG
16
13
RAWDP
RAW1
QNGREF
RAWCND
35
Idraulic
Turbine
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36
Design optimization of basic configurations


S-Graz cycle: can be seen as
the partial superimposition of
a CO2/H2O Brayton cycle and
a water/steam Rankine cycle
objective: maximum net power generation;
some significant design changes are obtained
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Design optimization of basic configurations


combined sugar and ethanol
production process
the design of process subsystems
is fixed, except for the multi-effect
evaporator (effect pressures and
increments of juice solid content)
101.7 MW
62.4 MW

optimal heat integration
of the process alone
results in a one third
reduction of the hot
utility requirement
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Design optimization of basic configurations


integration of the process with a CHP plant fuelled with bagasse
objective: maximum total site net power generation by varying
multi-effect evaporator and steam cycle design parameters
integrated grand composite curves
process + bagasse gasification +
gas turbine exhaust gases (red)
steam cycles (blue)
C
Steam cycle
H
H
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Hybrid algorithms for synthesis/design optimization



organized in two levels
the overall search is driven by
the upper level evolutionary
algorithm (topology and intensive
design parameters of the basic
configuration)
the lower level traditional algorithm
optimizes the objective function(s)
by varying the mass flow rates
in the basic configuration to be
evaluated (heat transfer feasibility
must be verified inside the black-box)
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Step 1 Single plants: modelling software





Models of the same plant in different software environments:
- MATLAB
- ReMIND
- ASPEN
Comparison of software capabilities
Interfaces with optimization algorithms
Selection of design variables to be
optimized for better integration
Optimization (1-obj or 2-obj)
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Step 2 Single plants: heat integration

Integration of the plant with a
steam network or a CHP plant

Optimization (1-obj or 2-obj)
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Step 3 Biorefinery and other industries

Test case consisting of a
biorefinery + another plant
(fixed configuration)

Selection of design variables to be
optimized for better integration
Optimization (1-obj or 2-obj)


+
Further integration with a
steam network or a CHP plant
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Step 4 Optimization of system topology

-
“Enumeration” of the alternatives to
be explored due to:
subprocesses within the biorefinery
integration with different plants
(which may consist of different
subprocesses as well)

Is a superstructure (the P-graph by
Friedler and co-workers) sufficient
to describe them all?

Algorithms to optimize the topology
of the system and the design
parameters of the subprocesses
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Step 4 Optimization of system topology

Different kinds of
optimization can be
performed:
- fixed resources
- desired products
- existing plants
(considering possible
modifications as well)
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Thank you for your kind attention!
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