基于遗传算法的双压氢液化流程性能优化研究

Research on Performance Optimization of Dual-pressure Hydrogen Liquefaction Process Based on Genetic Algorithm

由于液氢具有储氢密度高等显著优势,因此氢液化技术是实现氢大规模化应用的关键技术之一。构建了双压Claude循环的氢膨胀制冷氢液化循环流程,调用Refprop软件物性库确保物性数据的准确性,利用遗传算法以总比功耗为优化目标,开展了氢液化流程热力参数设计与优化。优化后流程氢液化率达到6.5 t/d,液氢产品仲氢含量95%,总比功耗为10.53 kW·h/kg,流程(火用)效率为35.72%。给出了低温各部件(除却压缩机和水冷器部分)的(火用)损失分布和各部件(火用)损失占比;可为大型工业级氢液化装置研制提供参考。

Liquid hydrogen has significant advantages such as high hydrogen storage density,making hydrogen liquefaction technology one of the key technologies for the scaled application of hydrogen.A hydrogen expansion refrigeration and liquefaction cycle process based on the dual-pressure Claude cycle is constructed,and the accuracy of physical property data is ensured by calling the Refprop library.Using genetic algorithms with the specific power consumption as the optimization objective,the thermodynamic parameter design and optimization of the hydrogen liquefaction process are carried out.The hydrogen liquefaction rate of the optimized process is 6.5 t/d,the para-hydrogen content of liquid hydrogen product is 95%,and the total specific power consumption is 10.53 kW·h/kg.The exergy efficiency of the optimized process is 35.72%.The distribution of exergy losses and the proportion of exergy losses in each component of the low-temperature section(excluding the compressor and water cooler) are further provided.The results can provide a reference for the development of large-scale industrial-grade hydrogen liquefaction plants.