A new stage-wise superstructure of heat transfer network and its application
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摘要: 换热网络优化是一种有效的能量回收方式。然而，拥有较大换热网络结构寻优空间的模型往往是具有非线性、非凸性的复杂混合整数非线性规划(MINLP)模型，常常难以得到可行解。基于换热网络分级超结构，构建了一个包含流股分流、等温混合、流股回流非等温混合的新型换热网络多级超结构并设置全线性约束条件，可以在增加换热网络寻优空间的同时，大幅提升MINLP模型可求解性。通过两个文献案例验证流股分流、流股回流及非等温混合对换热网络寻优的贡献，证明了该模型的有效性和适用性。Abstract: Optimization of heat exchanger network is an effective way of energy recovery. However, the model with large optimization space of heat exchanger network is often a complex mixed-integer nonlinear programming (MINLP) model with nonlinear and non-convexity constraints, and difficult to get a feasible solution. In this paper, based on the stage-wise superstructure, a new type of heat exchanger network contains flow split, reflux and non-isothermal mixing was built, and while increasing the optimization space of heat exchange network, linear constraints were set to greatly improve the solvability of MINLP model. Two cases in literature were used to verify the contribution of flow split, reflux, isothermal mixing and non-isothermal mixing to the optimization of heat exchanger network, and the effectiveness and applicability of the model.
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Key words:
- heat exchanger network /
- the stage-wise superstructure /
- flow split /
- reflux /
- non-isothermal mixing
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图 2 换热网络进出口的热流股
Figure 2. Heat streams at the inlet and outlet of the heat exchange network
图 4 换热网络进出口的冷流股
Figure 4. Cold streams at the inlet and outlet of the heat exchange network
表 1 案例1流股数据
Table 1. Data for example 1
Stream Tin/℃ Tout/℃ Fcp/(t·h−1) H1 175 45 10 H2 125 65 40 HU 180 179 - C1 20 155 20 C2 40 112 15 CU 15 25 - 
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表 3 案例2流股数据
Table 3. Data for example 2
Steram Tin/K Tout/K Fcp/(kW·K−1) H1 500 320 6 H2 480 380 4 H3 460 360 6 H4 380 360 20 H5 380 320 12 C1 290 660 18 HU 700 700 - CU 300 320 -
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