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EC FP7 project “Intensified Heat Transfer Technologies for Enhanced Heat Recovery” – INTHEAT

Grant Agreement No.262205

Project Meeting July 8, 2011

Petar Sabev Varbanov, Jiří Jaromír Klemeš, Ferenc Friedler

Centre for Process Integration and Intensification – CPI2, Research Institute of Chemical and Process Engineering, Faculty of Information

Technology, University of Pannonia, Veszprém, Hungary

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Overview of the tasksinvolving UNIPAN for the period

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UNIPAN Tasks WP 4 “Design, retrofit and control of intensified heat

recovery networks”

Task 4.1: “Development of a streamlined and computationally efficient methodology for design of HENs“, started month 1 (December 2010),

Deliverable D4.1 “Report on design methodology for new heat exchanger networks using P-graph and the ABB (Accelerated Branch-and-Bound) optimisation algorithm” due in month 9 (August 2011)

WP 6 “Technology transfer”

Task 6.2: “Dissemination events” : “Intensified heat exchangers – Novel developments (Information day for major stakeholders) (organisers: UNIPAN, PIL, UNIMAN)”

Deliverable D6.3 “Four dissemination events” – event 1, due in month 8 (July 2011).

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Task 4.1Development of a streamlined and

computationally efficient methodology for design of HENs

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• Introduction

• HEN design for flexibility and multiperiod operation

• Need for a rigorous synthesis tool

• P-graph for HEN Synthesis

• Extensions being developed

• Conclusions

Task 4.1 Outline

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Introduction

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Main Approaches

Analyse a base case scenario

Evaluate the expected process variations

Prepare a representative base case for HEN synthesis

Synthesise a heat exchanger network

Classic approach to process synthesis

The main approaches use different views of the system Insight-based : exploit thermodynamic insights such as

the heat recovery pinch and its associated targets

Superstructure-based: a reducible network including all possible options and then optimise and reduce it

Hybrid: combine the thermodynamic insights and the use of superstructures

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Classical HEN Synthesis

Pinch design method

Specify the heat recovery problem

Pinch Analysis

Obtain MER topology

Evolve the network

• Linnhoff and Hindmarsh (1983)

• Follow-ups and elaborations

Capital and total cost targets (Linnhoff and Ahmad, 1990)

Block Decomposition method (Zhu 1997)

Total Sites (Klemeš et al., 1997)

Total Sites integrating renewables (Perry et al., 2008)

• Mathematical Programming

• E.g. Yee and Grossmann (1990)

Yee, T. F., Grossmann I. E., 1990, Simultaneous optimization models for heat integration—II. Heat exchanger network synthesis, Computers & Chemical Engineering 14(10):1165-1184.

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Comparison of Approaches

Pinch design method A suite of techniques for HEN synthesis and process changes

Based on the pinch division and pinch design rules

Generates MER networks and evolves them

The networks may be inflexible

Superstructure-based approaches Build, optimise and reduce a superstructure

MILP and MINLP superstructure formulations are possible

Can treat multiple heat exchanger types non-isothermal mixing

Hybrid approaches Attempt to combine the insights of the Pinch Analysis with the strengths

of the superstructure construction and reduction

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Variable Factors

Ambient conditions

Temperature, humidity, etc.

Production rates

Feedstock variations, market conditions/demand

Catalyst activity

Gradual and steady, catalysts not replaced immediately

Fouling in heat exchangers

Connected batch processes

Inherent variations – e.g. batch distillation

Frequent stops due to batch cycles

Upsets in upstream processes

Gradual variations change steady states.

Transient changes cause transitions between states.

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Recognition of Variations

Introduction of the multi-period optimisation: Floudas and Grossmann (1986), using an MILP model

Follow-ups:

Aaltola (2002) MINLP Verheyen and Zhang (2006) MINLP Ahmad et al. (2008) used Simulated Annealing

MP for multiperiod HEN synthesis faces major challenges and limitations mainly with solution space and efficiency

P-graph is capable of efficiently addressing these limitations

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HEN Design for Flexibilityand Multiperiod Operation

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Main Definitions

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Operability

Flexible – the ability to operate at a variety of different steady-state points.

Controllable – the ability to manipulate the system, both in terms of feasible dynamic response and in terms of achieving the control system objectives.

Reliable – includes having excess capacities in certain system components to ensure ability to deal with breakdowns and device failures.

A heat exchanger network is termed operable if it is simultaneously:

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Current Focus: Flexibility

Many definitions in the research literature Means ability to retain specific properties and qualities

under varying conditions Applied to a heat exchanger network, the flexibility

can be defined as retaining the following properties for a given set of operating points:

The network satisfies the heating and cooling demands imposed by the process streams

Remains steady-state feasible

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Flexibility Domain

This is the set of operating points over which the flexibility is specified

Two main ways for representing the Flexibility Domain:

i. Ranges of variation = nominal conditions + variation intervals. Conceptual understanding

ii. Multiperiod operation = a list of discrete operating points with periods of activity. More convenient for applying algorithmic synthesis

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Flexible HEN Synthesis – Ranges of Variation

Using a specification of uncertainty ranges Reflects more realistically the uncertain nature of the

process variations Possible to impose the maximum energy requirement

Features

Problems

Impossible to assign the appropriate energy and capital costs to any of the operating points in the uncertainty envelope

Proper estimation of the cost trade-offs cannot be implemented

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Multiperiod Synthesis Approaches

Translates the variability of process parameters into a list of discrete operating points

Form operating cycle of usually one year

The periods can be assigned specific duration weights, ambient conditions and utility costs

Synthesise a minimum total cost network

Features

Problems

Processes almost never operate at fixed points, or it is difficult to predict them precisely

The computational difficulty imposed by the optimisation of the resulting superstructures, since the formulations are generally non-linear (MINLP)

Some of the multiperiod methods for HEN synthesis allow only isothermal mixing

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Synthesis with uncertainty ranges

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Uncertainty Ranges

Permanent and transient stream componentsCerda et al. (1990)

Cold streamT (ºC)

W(kW/ºC)

Fixed target temperature

Range of variation of the inlet temperature

Hot streamT (ºC)

W(kW/ºC)

0 00 WMIN

WMAX

WMIN

WMAX

Pe

rma

nent

com

po

nent

Pe

rma

nent

com

po

nentTransient

components

Fixed target temperature

Range of variation of the inlet temperature

Transient components

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Uncertainty Ranges – Algorithm

1. Thermodynamic targets for heat recovery

Identify the pinch locations Heat recovery targets

2. Decompose the temperature range of the set of process streams into sub-networks (or blocks)

3. Considering each sub-network as an energetically balanced system, obtain a network featuring a minimum number of heat exchanger matches. This stage usually uses the superstructure approach, defining all significant options for implementing the network and further optimising and reducing this superstructure.

4. The resulting heat exchange matches are further assigned to actual exchangers and sized

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Synthesis for multiperiod operation using Mathematical Programming

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Multiperiod HEN Synthesis Algorithms

Floudas & Grossmann (1987) Aaltola (2002)

Specifyoperating points

Utility cost targeting

Feasibility testing

NLP network generation

Flexibility testing

End

Modifications

Specification of the operating points and superstructure

Superstructure reduction MINLP

Minimise utility costs under limited HE areas

LP / NLP

End

Variability translated to a set of discrete operating points and periods

Periods duration weights

Individual ambient conditions and utility costs

Synthesise minimum TAC HEN feasible for all periods

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Need for a rigorous synthesis tool

Complexity caused by combining continuous and combinatorial aspects

Combinatorial complexity increases exponentially with the number of streams and periods

MP – moderate success in reducing superstructures Very few applications of constructing the superstructures

using MP are known Solvers examine topologically clearly infeasible

combinations of integer variable values Rather difficult to build the necessary problem

superstructures without rigorous combinatorial tools

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P-graph for HEN Synthesis

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HE representation with P-graph

Grid-diagram representation P-graph

P-graph is a bi-partite graph. It features 2 vertex types: materials (streams) and operating units

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P-graph Example

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BM

BMG

RSGBR

25.9 MW

2.1 t/h

SGF

SGPR

8·10-3 t/h

BG

Q40

FCCC_60(MCFC+ST)

W 10.0 MW

BGD

FRT

2.0 t/h

Q5

2.2 MW

LD_40_5

BLR_BG

15.0 MW

CO2

0.6 t/h0.7 t/h

16.8MW

16.7 MW 0.17

t/h

26.0 MW

12.8 MW

15.1MW

Streams / MaterialsBG: BiogasBM: BiomassBR: Biomass residuesFRT: FertiliserSG: SyngasPR: Particulate matterQ40: Steam at 40 barQ5: Steam at 5 barRSG: Raw syngasW: Electrical power

OperationsBGD: Biogas digesterBMG: Biomass gasifierSGF: Syngas filterFCCC: Fuel Cell Combined CycleBLR_BG: Biogas boilerLD_40_5: Letdown station

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P-graph Combinatorial instruments

Axioms ensuring combinatorially feasible structures

Maximal Structure Generation (MSG) algorithm – builds the union of all combinatorially feasible network structures

Solution Structures Generation (SSG) – generates all combinatorially feasible network structures from the maximal one

ABB: Accelerated Branch-and-Bound algorithm. Combines the “branch-and-bound” search strategy with the SSG logic

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P-graph foundation: axioms

Ensuring a combinatorially feasible structure:

(S1) Every product is included in the structure

(S2) A raw material can’t be an output of any operating unit in the structure

(S3) Every operating unit is defined in the synthesis problem

(S4) At least one path from any operating unit leading to a product

(S5) Every stream belonging to the structure must consumed or produced by at least one operating unit from the structure

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P-graph algorithms:Maximal Structure Generation (MSG)

Problem Formulation

set of raw materials set of products set of candidate operating

unitsReduction part

Composition part

Problem Formulation

Consistent sets O & M

Maximal Structure

Maximal Structure

Union of all combinatorially feasible structures

Rigorous super-structure

Legend:

O: set of operating units

M: set of materials

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P-graph algorithms:Solution Structures Generation (SSG)

Add units producing

New decision mappingfor every decision branch

Invoke SSG(Recursion)

Start from products

All Solution Structures

Solution Structure

A combinatorially feasible network of materials and operating units

Decision Mapping

A mathematical representation of a process network – either incomplete, or a solution structure

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ABB Algorithm – Even Faster Search

• Employs the “branch-and-bound” strategy• Combines this with the P-graph logic (SSG algorithm)• Ensures combinatorial feasibility

• Non-optimal decisions are eliminated• It is possible to select a set of solution structures which are

optimal or near-optimal

ABB: Accelerated Branch-and-BoundFurther acceleration of the synthesis procedure

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PNS ParadigmsExample from Reactor Networks

Conventional MP(MILP, MINLP)

P-graph(MSG, SSG, ABB)

Network Model Formulation

Mostly MANUAL ALGORITHMIC

Automation allowing user interaction

Complexity

(Solution Speed)

Example: separation sequence synthesis

34 Billion

possible combinations

3,465 combinatorially feasible structures

106 ratio(6 orders of magnitude)

Interpretation of results

Flowsheets

(only)

Flowsheets and P-graphs

Easier to spot structural patterns

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Extensions being developed

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Interfaces of the P-graph algorithms

P-graph framework(MSG, SSG, ABB)

Generate candidate

HE

Branching:When to create sub-problems

Bounding:Variation of

Supertargeting

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Multiperiod formulation specifics

Establish the design horizon Define the operation periods (cumulative

durations) and the linked steady-state points (average stream flowrates, temperatures and heat capacity flowrates)

Binding heat exchange matches from different periods to a particular unique heat exchanger unit

Streams temperature-based partitioning and splitting – which first

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Preliminary Results

The approach is being tested on case studies First results look encouraging Solution times are fast For a toluene hydrodealkylation example 105

cold sub-streams and 333 hot sub-streams are generated from 18 temperature intervals

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Conclusions for Task 4.1

Most currently available methods for HEN design are based on mathematical programming

Few are using evolutional and random-search algorithms

The superstructure-based methods are not practical for generation of the superstructures

The P-graph framework offers algorithmic construction of the superstructures and combinatorially efficient reduction of the search space presented to the optimisation solvers

Currently several case studies are in progress

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Task 6.2: “Dissemination events” : “Intensified heat exchangers – Novel developments (Information day for major stakeholders)

(organisers: UNIPAN, PIL, UNIMAN)”

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Dissemination event: PRES’11

PRES’11 has been organised by UNIPAN together with The Italian Association of Chemical Engineering AIDIC. 8-11 May 2011 in Florence, Italy

There was a special session added to the programme, dedicated to intensifying heat transfer. Several works have been presented and discussion:

The Generalized Correlation for Friction Factor in Cris-Cross Flow Channels of Plate Heat Exchangers by Arsenyeva et al. (http://www.aidic.it/cet/11/25/067.pdf)

The Heat and Momentum Transfers Relation in Channels of Plate Heat Exchangers, by Kapustenko et al. (http://www.aidic.it/cet/11/25/060.pdf)

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Task 4.1, Deliverable D4.1

Deliverable D4.1 “Report on design methodology for new heat exchanger networks using P-graph and the ABB (Accelerated Branch-and-Bound) optimisation algorithm”

Due in month 9 (August 2011) The report will be delivered by UNIMAN with the main

input from UNIPAN and help from SORDU and OIKOS

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Dissemination event: PRES’11

There have been also more presentations on intensified heat transfer

Improving Energy Recovery in Heat Exchanger Network with Intensified Tube-side Heat Transfer, by Pan et al., UNIMAN (http://www.aidic.it/cet/11/25/063.pdf)

Heat Exchanger Network Retrofit through Heat Transfer Enhancement, by Wang et al., UNIMAN (http://www.aidic.it/cet/11/25/099.pdf)

Deliverable D6.3 “Four dissemination events” – event 1, due in month 8 (July 2011) will be delivered by UNIPAN by the end of July 2011 with the assistance of UNIMAN, and PIL

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Work for the next period (until month 12) WP 2 “Combined tube-side and shell-side heat exchanger

enhancement”, started in month 1 (December 2010)

Task 2.2. Heat transfer enhancement for the shell-side of heat, deliverable D2.2. “Report on tube side and shell side enhancement research” due in month 9 (August 2011).

UNIPAN is exploring process integration options based on the research of UNIMAN, UNIBATH, EMBAFFLE, led by CALGAVIN

WP 4 “Design, retrofit and control of intensified heat recovery networks”

Deliverable D4.1 “Report on design methodology for new heat exchanger networks using P-graph and the ABB (Accelerated Branch-and-Bound) optimisation algorithm” , Due in month 9 (August 2011). The report will be delivered by UNIMAN with the main input from UNIPAN and help from SORDU and OIKOS

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Work for the next period (until month 12) WP 4 “Design, retrofit and control of intensified heat

recovery networks”

Task 4.2. A systematic retrofit procedure will be developed to account for heat exchanger networks prone to fouling deposition. Deliverable D4.2 “Report on retrofit procedure for heat exchanger networks prone to fouling deposition” , Due in month 14 (January 2012). UNIPAN collaborates with UNIMAN, UPB .

WP 6 “Technology transfer”

Task 6.2: “Dissemination events” : “Intensified heat exchangers – Enhanced heat transfer (Workshop/session at a recognised international conference) (organisers: UNIPAN, CALGAVIN, EMBAFFLE, SODRU)

Suggesting to be organised at CAPE Forum 2012 organised by UNIPAN, 26-28 March 2012

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Thank you!