Synthesis of heat exchanger networks: II. Evolutionary generation of networks with various criteria of optimality

Abstract

An evolutionary method is presented for the synthesis of heat exchanger networks. Starting from feasible solutions which preferably exhibit maximum energy recovery, the method allows systematic promotion of desired design features such as low overall cost, suitability for starting‐up procedures, observation of safety constraints, etc. Seven examples based on standard literature problems are used to illustrate the method.

Evaluating the efficiency of integrated systems in the process industry–Case: Steam cracker

“…The studies by Umeda et al [6] and Linnhoff and Flower, [7], [8] were milestones in the systematic synthesis of heat exchanger networks using pinch analysis. The heat recovery pinch was a new concept used to connect unit processes and process flows to save energy.…”

Chemical engineering systems modeling and efficiency analysis of heat and mass exchange

“…Change of the system structure leads to the heat exchangers networks replenishment. One of the methods for synthesis problem solving is the pinch analysis use [17][18][19]. Pinch analysis allows to integrate heat streams within the production cycle.…”

Synthesis of Heat-Integrated Resource Conservation Networks

“…insight-based pinch analysis techniques such as heat transfer composite curves (Hohmann, 1971;Umeda et al, 1978;Umeda et al, 1979), problem table algorithm (Linnhoff and Flower, 1978b;Linnhoff and Flower, 1978a), pinch design method (Linnhoff and Hindmarsh, 1983;Ahmad et al, 1990;Linnhoff and Ahmad, 1990;Linnhoff, 1993), dual temperature (Trivedi et al, 1989a) and pseudo-pinch methods (Rev and Fonyo, 1986b;Rev and Fonyo, 1986a;Trivedi et al, 1989b;Wood et al, 1991) and (ii) mathematical programming techniques (Cerda et al, 1983;Papoulias and Grossmann, 1983;Floudas et al, 1986;Suaysompol and Wood, 1991;Ježowski and Friedler, 1992;Galli and Cerda, 1998a;Galli and Cerda, 1998b;Galli and Cerda, 1998c). The following section mainly focuses on reviewing the minimum utility targeting problem with sequential synthesis approach.…”