Energy integration in petrochemical and refining industries is an effective concept to minimize dependence on heating and cooling utilities through networks of exchanger equipment. Pinch Analysis is very popular and successful technique to optimize heat recovery between heat sources and sinks. Yet, design of networks of exchangers is challenging and requires careful attention to energy consumption and exchanger areas. This work presents a graphical methodology to design exchanger networks taking into account both heat loads and transfer areas of exchanger units in one single information. A new parameter is introduced for design that is the ratio between the heat load and the exchanger area, and is determined in kW/m. It is defined as an energy-area parameter expressing how much heat the exchanger would transfer per every meter square of area. Such parameter will be valuable key in design to screen matches of exchangers providing that both the heat and area are considered. The higher the value of the parameter, the better the performance of the exchanger, i.e. maximum heat transfer rate for minimum exchanger area. The design methodology embedding the energy-area parameter guarantees HEN designs with energy targets and minimum areas. A case is studied for the production of 100,000 t/y of dimethyl ether. An optimum network is generated by applying the new parameter with less exchanger areas and hot utility of 25% and 30%, respectively compared with an automated design by Aspen Energy Analyzer®. Also, substantial savings of about 47% in the total cost of the network are earned.

中文翻译：

---

使用新能源领域关键参数的能源回收系统概念有效设计

石化和炼油行业的能源整合是一个有效的概念，可以通过交换设备网络最大限度地减少对加热和冷却设施的依赖。夹点分析是一种非常流行且成功的技术，用于优化热源和散热器之间的热回收。然而，交换器网络的设计具有挑战性，需要仔细关注能源消耗和交换器区域。这项工作提出了一种设计交换器网络的图形方法，在一个信息中考虑了交换器单元的热负荷和传输面积。设计中引入了一个新参数，即热负荷与换热器面积之比，单位为 kW/m。它被定义为能量面积参数，表示换热器每平方米面积可传递多少热量。如果同时考虑热量和面积，这样的参数将是设计中筛选交换器匹配的有价值的关键。该参数值越高，换热器的性能越好，即最小换热器面积下的最大传热速率。嵌入能量面积参数的设计方法保证了 HEN 设计具有能量目标和最小面积。以年产10万吨二甲醚为例。通过应用新参数，可以生成最佳网络，与 Aspen Energy Analyzer® 的自动化设计相比，交换器面积更小，热利用率分别为 25% 和 30%。此外，网络总成本还可大幅节省约 47%。