大规模复杂换热网络联动进化障碍分析及策略改进

Analysis of linkage evolutionary barrier and optimization strategy improvements for large-scale complex heat exchanger networks

针对启发式算法在优化大规模换热网络时出现优化精细度不足的问题,提出一种以小负荷公用工程为导向的换热单元耦合联动强制进化策略。该策略以小负荷公用工程作为导向,构建具有耦合关系的换热单元环路,并对环路内的换热单元热负荷进行联动调整,同时保持环路外换热单元的热负荷和流股匹配不变。该策略旨在最大程度回收流股的能量,以减少小负荷公用工程使用带来的费用增加。将策略应用于强制进化随机游走算法并对两个算例进行测试,算例H8C7和H10C10的优化结果分别为1495292$/a和1713637$/a。与改进前相比,分别降低了7466$/a和7533$/a;与文献中最优解相比,分别减少了2033$/a和1450$/a,证明了该策略的有效性。

A heat exchanger unit coupling and linkage forced evolution strategy,guided by low-load hot utility,was proposed to address the issue of insufficient optimization accuracy in heuristic algorithms for optimizing large-scale heat exchanger networks.This strategy focused on constructing a linked heat exchanger unit loops under the guidance of low-load hot utility,adjusting heat exchanger unit loads within the loops while ensuring consistency with units outside the loops.The goal was to maximize stream energy recovery and reduce costs associated with low-load hot utility usage.When applied to the random walk algorithm with compulsive evolution on two cases,the total annual costs(TACs)for cases H8C7 and H10C10 were 1495292$/a and 1713637$/a,respectively.Compared to previous results,TACs achieved a savings of 7466$/a and 7533$/a.In comparison to the best literature solutions,TACs observed reductions of 2033$/a and 1450$/a,demonstrating the efficacy of this strategy.