Abstract:

Work and heat exchange network (WHEN) problems refer to the problem of synthesizing the networks considering the work integration and heat integration in the process design, which aims to increase the energy efficiency of the overall system and reduce the costs. In the previous works, the mathematical programming methods are generally used to model and optimize WHENs. However, due to the nonlinear constraints of the pressure transformation process and heat exchanger area calculation, as well as the binary variables of heat transfer matching, the overall model is often a highly nonconvex mixed integer nonlinear programming model, which is difficult to solve. This work proposed an efficient WHEN design method. In the model, turbo expanders and heat exchangers are used to exchange shaft work and heat, respectively. A decomposition algorithm is used in the solving procedure, which uses the genetic algorithm to optimize the key variables in the main problem and uses deterministic algorithms to solve the two sub-network design problems. Multi-objective optimization that minimizes economic and environmental impact is considered in the WHEN model. In the case study, we show the difference between the networks obtained with different optimization goals and the Pareto curve considering the multi-objective optimization, which verifies the efficiency of the proposed method.

Key words: work and heat exchange network, integration, multi-objective optimization, genetic algorithm, optimal design

摘要：

功热网络设计问题指在流程设计中对变压和换热过程进行耦合优化设计的问题，以此来提高整体系统的能效并降低成本。前人工作中一般采用数学规划法对功热网络建模优化。然而，由于存在变压过程和换热器面积计算的非线性约束，以及换热匹配的二元变量，整体模型往往是一个高度非凸的混合整数非线性规划模型，难以求解。本文提出一种高效的功热网络优化方法。模型中分别用透平压缩机和换热器实现功热网络中轴功和热的交换。求解过程采用分解算法，主问题中用随机算法对关键变量优化，功和热两个子网络问题中用确定性算法求解。目标函数考虑了经济和环境影响。案例测试对比了不同优化目标得到的结果以及多目标Pareto曲线，验证了所提出方法的高效性。

关键词: 功热交换网络, 集成, 多目标优化, 遗传算法, 优化设计