CIESC Journal ›› 2020, Vol. 71 ›› Issue (3): 1189-1201.DOI: 10.11949/0438-1157.20190975

• Process system engineering • Previous Articles     Next Articles

Multi-objective constrained optimization method for heat exchanger network considering comprehensive economy and entransy

Lei WANG1,2(),Yuting CHEN1,2,Yanyan XU1,2,3,Shuang YE1,2(),Weiguang HUANG1,2,3   

  1. 1.Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
    2.University of Chinese Academy of Sciences, Beijing 100049, China
    3.School of Physical Science and Technology, Shanghai Tech University, Shanghai 201210, China
  • Received:2019-08-30 Revised:2019-12-05 Online:2020-03-05 Published:2020-03-05
  • Contact: Shuang YE

综合考虑经济性与效率的换热网络多目标约束优化方法

王磊1,2(),陈玉婷1,2,徐燕燕1,2,3,叶爽1,2(),黄伟光1,2,3   

  1. 1.中国科学院上海高等研究院,上海 201210
    2.中国科学院大学,北京 100049
    3.上海科技大学物质科学与技术学院,上海 201210
  • 通讯作者: 叶爽
  • 作者简介:王磊(1994—),男,硕士研究生,wanglei01@sari.ac.cn
  • 基金资助:
    国家重点研发计划项目(YS2017YFGH001928);上海市科委科研计划项目(19DZ1205700)

Abstract:

For the optimization of the heat exchange network, not only the“quantity”of energy recovery, but also the“quality”dissipation problem in the energy recovery process must be considered. On the premise of the maximum energy recovery(MER) of the heat exchanger network, based on the entransy dissipation theory in the process of irreversible heat transfer, aiming at the highest entransy efficiency which represents the energy recovery quality, we establish a multi-objective mixed integer nonlinear programming (MOMINLP) model, which comprehensively consider the quantity and quality of energy recovery and the economics of the heat exchanger network. According to the characteristics of the model targets, the heat exchanger network is optimized step-by-step based on the ε-constraint algorithm, the maximum energy recovery and minimum total annual cost (TAC) of the heat exchanger network are accurately solved in turn with the BARON software. Then, with the solved results multiplied by the relaxation coefficient εi as the constraint condition for narrowing the search area, the Pareto frontier of the entransy efficiency under the constraints of energy and economy is obtained. Through calculating the classic 10SP1 case, the optimal solution as the minimum ratio of economy to efficiency is obtained when the relaxation coefficient is 1.05, and compared with the results of other literature optimization methods, the multi-objective constrained optimization method in this paper can find the comprehensive optimal solution faster. Finally, the entransy efficiency of different optimization schemes is compared through the heat exchanger networks composite curve in T-Q diagram, which indicates that divide the heat exchanger network into internal part and surplus part firstly, and then optimize the scheme according to the economy and entransy efficiency, this method can reduce the irreversible loss of internal part and increase the temperature of the surplus part.

Key words: heat exchanger network, ε-constrained method, multi-objective, optimal design, integration, process control

摘要:

换热网络优化中不仅要考虑能量回收的“量”,还要考虑能量回收过程中“质”的耗散问题。在换热网络最大能量回收的前提下,基于不可逆传热过程中的耗散理论,以代表能量回收品质的效率最高为目标,建立综合能量回收数量、品质并同时考虑换热网络经济性的多目标混合整数非线性规划(MOMINLP)模型。根据模型目标有主次之分的特点,基于ε约束法对模型进行分步优化并结合BARON软件进行精确求解,依次求解换热网络的最大能量回收量(MER)与最低年均总成本(TAC),再将所得结果乘以松弛系数εi作为缩小搜索区域的约束条件,获得能量与成本约束下效率的Pareto前沿。通过对经典10SP1案例进行计算求解,最终得到最大能量回收量下,费用松弛系数为1.05时费效比最小的优化方案,而且本文的多目标约束优化方法能够更快求得综合的最优解。最后通过T-Q图中的换热网络组合曲线对比不同优化方案的效率,将换热网络划分为内部换热部分与剩余流股部分,多目标约束优化方法能够降低内部换热不可逆损失,提高剩余流股的温度。

关键词: 换热网络, ε-约束法, 多目标, 优化设计, 集成, 过程控制

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