采用醇胺法脱除沼气中的CO₂，使之达到可液化制取LNG的标准。通过Aspen Hysys模拟该工艺流程，利用Matlab进行遗传算法和序贯法优化。优化后的结果表明，原料气中含30%、40%、50% CO₂时，生产单位CH₄的电耗分别为0.163、0.191、0.235 kWh/m³，降低了0.85%、1.59%、0.91%；再生热耗分别为2.29、3.02、4.34 GJ/m³，降低了5.68%、7.69%、8.49%。将优化结果与现有工厂、实验、模拟数据对比，可为高碳含量天然气脱除CO₂提供参考。

Biogas is a typical biomass energy source that can be purified into compressed natural gas (CNG) or liquefied natural gas (LNG). CO₂ removal technology is the key to purify biogas. The technology using aqueous amine solvent is a popular and feasible one at present, but it consumes high energy. Aspen Hysys is utilized to simulate this technology to achieve the CO₂ removal targets and make the biomass meet the critical requirement for LNG production. To reduce energy consumption, genetic algorithm method and sequential method are developed by Matlab to optimize the ratio of amine solution and main operating parameters. As the mole fraction of CO₂ in feed gas is 30%, 40% and 50%, respectively, the optimized power consumption is 0.163, 0.191 and 0.235 kWh·m^-3, which decrease by 0.85%, 1.59% and 0.91% respectively than before optimization; the optimized regeneration heat consumption is 2.29, 3.02, and 4.34 GJ·m^-3, which decrease by 5.68%, 7.69% and 8.49%, respectively. The optimization results are compared with the existing data of factory, experiment and simulation. It provides a reference for the parameter optimization and energy consumption of CO₂ removal from natural gas with a high concentration of CO₂.

曾金繁(1995-),女,硕士生