摘要
文章应用有限时间热力学理论,首先建立了逆水气变换(RWGS)化工流程模型,并分析了反应器入口压力和入口摩尔流率对整个化工流程性能的影响,接着以总熵产率最小和CO产率最大为优化目标,采用第2代非支配排序遗传算法(NSGA-II)对RWGS化工流程进行了多目标优化。结果表明:化工流程的最小总熵产率与最大CO产率两个目标无法同时达到最优;Pareto最优前沿包含了2个目标在不同权重下的最优解;与参考点相比,利用LINMAP决策的方法确定的最优解使总熵产率减小了3.5%,CO产率增加了3.5%。文中研究结果对实际RWGS化工流程的设计与优化有一定的理论指导意义。
A model of reverse water-gas shift(RWGS)chemical process is established based on the theory of finite-time thermodynamics,and then effects of the inlet pressure and the inlet molar flow rate of the reactor on the process performances are analyzed.The minimum total entropy generation rate and the maximum CO yield are taken as the optimization objectives,and the method of the second-generation non-dominated sorting genetic algorithm(NSGA-II)is used to obtain the Pareto optimal front of the multi-objective optimization of the RWGS chemical process.The results show that the two objectives of the minimum total entropy generation rate and the maximum CO yield of the chemical process cannot achieve the corresponding optimal values at the same time;the Pareto optimal front contains the optimal solutions of the two objectives under different weights;compared with the reference operation point of the process,the optimal solution determined by the LINMAP decision method reduces the total entropy generation rate by 3.5%and increases the CO yield by 3.5%.The obtained results in this paper have certain theoretical guiding significance for the design and optimization of the actual RWGS chemical process.
作者
赵明
夏少军
于亚杰
Zhao Ming;Xia Shaojun;Yu Yajie(College of Power Engineering,Naval University of Engineering,Wuhan 430033,China)
出处
《可再生能源》
CAS
CSCD
北大核心
2022年第5期598-603,共6页
Renewable Energy Resources
基金
国家自然科学基金项目(51976235,51606218,51576207)
湖北省自然科学基金项目(2018CFB708)。
关键词
有限时间热力学
逆水气变换
流程
熵产率
CO产率
多目标优化
finite time thermodynamics
reverse water-gas shift
process
entropy generation rate
CO yield
multi-objective optimization
