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Efficient synthesis of large-scale heat exchanger networks using monogenetic algorithm

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Abstract

A promising method for the efficient design of large-scale heat exchanger networks is the genetic algorithm. The heat exchanger network is divided into sub-networks which are optimized by a hybrid genetic algorithm. In additional steps these sub-networks are optimized by a monogenetic algorithm. An example consisting of 39 process streams was considered in detail. Significant improvements were made in reduction of total annual costs and the number of heat exchangers.

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Abbreviations

A :

Heat transfer area of heat exchanger (m2)

a, b :

Parameters for cost of heat exchangers ($/year)

c :

Parameter for cost of heat exchangers

C :

Total annual cost ($/year)

C min :

Minimum total annual cost ($/year)

C Inv :

Investment costs ($/year)

C op :

Operation costs ($/year)

c u :

Specific utility cost per unit duty ($/kWyear)

h :

Heat transfer coefficient (kW/m2K)

N c :

Number of cold process streams

N CU :

Number of cold utilities

N EX :

Number of heat exchangers

N h :

Number of hot process streams

N HU :

Number of hot utilities

N s :

Number of stages of a stage-wise superstructure

N SN :

Number of sub-networks

N U :

Number of heaters and coolers

NTU:

Number of transfer units

Q:

Heat load (kW)

R:

Ratio of heat capacity flow rate of hot stream to that of cold stream

T :

Stream temperature vector (°C)

t′:

Supply stream temperature of stream (°C)

t″:

Outlet stream temperature of a network before the stream is heated or cooled by utilities (°C)

t OUT :

Target temperature (°C)

t +OUT , t −OUT :

Upper and lower bounds of target temperature (°C)

Δt m :

Logarithmic mean temperature difference (LMTD) (°C)

U :

Overall heat transfer coefficient (kW/m2K)

\( \dot{W} \) :

Heat capacity flow rate (kW/K)

Ω:

Set of HEN structures within a superstructure

ω:

Set of possible HEN structures within a superstructure with respect to given constraints

c:

Cold stream

CU:

Cold utility

h:

Hot stream

HU:

Hot utility

i:

Stage index

j:

Hot stream index

k:

Cold stream index

HU:

Hot utility

CU:

Cold utility

HEN:

Heat exchanger network

MINLP:

Mixed-integer-nonlinear-programming

GA:

Genetic algorithm

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Acknowledgments

The present research was supported by Innovation Program of Shanghai Municipal Education Commission (No. 07ZZ89).

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Authors and Affiliations

  1. Institute of Process and Plant Engineering, Hamburg University of Technology, 21071, Hamburg, Germany

    Philipp Ernst & Georg Fieg

  2. Institute of Thermodynamics, Helmut Schmidt University, 22043, Hamburg, Germany

    Xing Luo

  3. Institute of Thermal Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Xing Luo

Authors
  1. Philipp Ernst
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  2. Georg Fieg
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  3. Xing Luo
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Corresponding author

Correspondence to Philipp Ernst.

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Ernst, P., Fieg, G. & Luo, X. Efficient synthesis of large-scale heat exchanger networks using monogenetic algorithm. Heat Mass Transfer 46, 1087–1096 (2010). https://doi.org/10.1007/s00231-010-0685-4

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  • DOI: https://doi.org/10.1007/s00231-010-0685-4

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