This study combines feed splitting, internal heat integration, and heat integration between Pervaporation (PV) retentate streams and internal streams of reactive distillation (RD) column employed in TAME production in an attempt to optimize energy consumption in the process. All process parameters in the RD column, PV membrane process, and process energy consumption were optimized simultaneously. Further, the possibility of heat exchange between hot and cold streams was investigated by the optimization algorithm in internal heat integration in the RD column (R-HIDiC) as well as heat integration between retentate streams in PV modules and internal streams in the RD column. Accordingly, the number of heat exchangers and the heat exchange ratio of the streams was determined by the optimization algorithm. The Total Annual Cost (TAC) was adopted as the objective function to be optimized by a combination of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. Twelve different processes were optimized and compared. Optimization results suggest that the hybrid R-HIDiC–PV process with feed splitting and heat integration reduced the energy consumption by 42 % and TAC by 45 % compared to the hybrid PV–RD process and by 47 % and 48 %, respectively, compared to the hybrid RD–Pressure swing distillation process.

这项研究结合了进料分离，内部热集成以及TAME生产中使用的全蒸发（PV）滞留物流和反应精馏（RD）塔内部物流之间的热集成，以尝试优化过程中的能耗。同时优化了RD塔，PV膜工艺和工艺能耗中的所有工艺参数。此外，通过优化算法对RD塔中的内部热集成（R-HIDiC）以及PV模块中滞留物流与RD塔中的内部流之间的热集成进行了优化算法，研究了冷物流之间进行热交换的可能性。因此，通过优化算法确定热交换器的数量和流的热交换率。采用年度总费用（TAC）作为目标函数，并结合遗传算法（GA）和粒子群优化（PSO）算法进行优化。优化和比较了十二个不同的过程。优化结果表明，与混合PV-RD工艺相比，具有进料分裂和热整合功能的混合R-HIDiC-PV工艺可将能耗降低42％，将TAC降低45％，与之相比，分别可降低47％和48％混合RD –变压蒸馏工艺。