Optimizing heat exchanger networks with genetic algorithms for designing each heat exchanger including condensers

Abstract This paper presents a procedure for the design of the components of a heat exchanger network (HEN). The procedure first uses pinch analysis to maximize heat recovery for a given minimum temperature difference. Using a genetic algorithm (GA), each exchanger of the network is designed in order to minimize its total annual cost. Eleven design variables related to the exchanger geometry are considered. For exchanger involving hot or cold utilities, mass flow rate of the utility fluid is also considered as a design variable. Partial or complete condensation of hot utility fluid (i.e., water vapor) is allowed. Purchase cost and operational cost are considered in the optimization of each exchanger. Combining every exchanger minimized cost with the cost of hot utility and cold utility gives the total cost of the HEN for a particular Δ T min . The minimum temperature difference yielding the more economical heat exchanger network is chosen as the optimal solution. Two test cases are studied, for which we show the minimized total cost as a function of the minimum temperature difference. A comparison is also made between the optimal solution with the cost of utilities and without it.

[1]  Ignacio E. Grossmann,et al.  Simultaneous optimization models for heat integration—I. Area and energy targeting and modeling of multi-stream exchangers , 1990 .

[2]  G. Polley,et al.  Pressure drop considerations in the retrofit of heat exchanger networks , 1990 .

[3]  G. L. Shires,et al.  Process Heat Transfer , 1994 .

[4]  Mubarak Ebrahim,et al.  Pinch technology: an efficient tool for chemical-plant energy and capital-cost saving , 2000 .

[5]  Mariusz Markowski.  Reconstruction of a heat exchanger network under industrial constraints - the case of a crude distillation unit , 2000 .

[6]  Stephen G. Hall,et al.  Targeting for Furnace Systems Using Pinch Analysis , 1994 .

[7]  Frank P. Incropera,et al.  Fundamentals of Heat and Mass Transfer , 1981 .

[8]  Venkat Venkatasubramanian,et al.  A genetic algorithmic framework for process design and optimization , 1991 .

[9]  Louis Gosselin,et al.  Optimal geometry and flow arrangement for minimizing the cost of shell‐and‐tube condensers , 2008 .

[10]  Mikhail Sorin,et al.  Synthesis of heat exchanger networks using genetic algorithms , 2008 .

[11]  D. P. Sekulic,et al.  Fundamentals of Heat Exchanger Design , 2003 .

[12]  G. T. Polley,et al.  Interfacing heat exchanger network synthesis and detailed heat exchanger design , 1991 .

[13]  Mauro A.S.S. Ravagnani,et al.  Heat exchanger network synthesis and optimisation using genetic algorithm , 2005 .

[14]  Mauro A.S.S. Ravagnani,et al.  Detailed equipment design in heat exchanger networks synthesis and optimisation , 2003 .

[15]  Hongmei Yu,et al.  A combined genetic algorithm/simulated annealing algorithm for large scale system energy integration , 2000 .

[16]  Roger Josef Zemp,et al.  Retrofit of pressure drop constrained heat exchanger networks , 2000 .

[17]  Leon Lapidus,et al.  Topics in computer‐aided design: Part II. Synthesis of optimal heat exchanger networks by tree searching algorithms , 1973 .

[18]  Robin Smith,et al.  Chemical Process: Design and Integration , 2005 .

[19]  Mikhail Sorin,et al.  Direct and Indirect Heat Transfer in Water Network Systems , 2001 .

[20]  Daniel R. Lewin,et al.  A generalized method for HEN synthesis using stochastic optimization. II. : The synthesis of cost-optimal networks , 1998 .

[21]  M. Serna,et al.  A Compact Formulation of the Bell–Delaware Method for Heat Exchanger Design and Optimization , 2005 .

[22]  Liliane Maria Ferrareso Lona,et al.  The economics of the detailed design of heat exchanger networks using the Bell Delaware method , 2000 .

[23]  M. Ravagnani,et al.  Optimal heat exchanger network synthesis with the detailed heat transfer equipment design , 2007, Comput. Chem. Eng..

[24]  Antonis C. Kokossis,et al.  Hypertargets: a Conceptual Programming approach for the optimisation of industrial heat exchanger networks—Part III. Industrial applications , 1999 .

[25]  Nilay Shah,et al.  Heat exchanger network design for multipurpose batch plants , 1996 .

[26]  Louis Gosselin,et al.  Minimizing shell‐and‐tube heat exchanger cost with genetic algorithms and considering maintenance , 2007 .

[27]  Luigi Piroddi,et al.  Nonlinear identification and control of a heat exchanger: a neural network approach , 1997 .

[28]  Pingjing Yao,et al.  Synthesis and optimization of heat integrated distillation systems using an improved genetic algorithm , 1998 .

[29]  Daniel R. Lewin,et al.  A generalized method for HEN synthesis using stochastic optimization. I. General framework and MER optimal synthesis , 1998 .

[30]  Louis Gosselin,et al.  Review of utilization of genetic algorithms in heat transfer problems , 2009 .

[31]  Kevin C. Furman,et al.  A Critical Review and Annotated Bibliography for Heat Exchanger Network Synthesis in the 20th Century , 2002 .

[32]  Yourun Li,et al.  Optimal pinch approach temperature in heat-exchanger networks , 1986 .

[33]  John C. Chato,et al.  Laminar condensation inside horizontal and inclined tubes , 1960 .

[34]  Arturo Jiménez-Gutiérrez,et al.  MINLP synthesis of heat exchanger networks considering pressure drop effects , 2003, Comput. Chem. Eng..

[35]  Robin Smith,et al.  Cooling water system design , 2001 .