化工企业氯碱生产多目标优化应急救援研究

随着现代化建设的不断深入,氯碱生产的需求量也就越来越大,而在氯碱生产过程中也伴随着很多的安全问题,建立及时有效的应急救援对于安全生产有着十分重要的作用,然而在应急救援中将数学模型有效的融人是一个十分关键的。本研究将多目标遗传算法与应急救援相结合,通过目标优化建立最具针对性的应急救援,保证人民的生命与财产安全,企业生产健康有序的进行。     

煤化工废水脱酸脱氨流程的多目标优化

对某气化厂85 t/h煤化工废水单塔脱酸脱氨流程进行模拟,在此基础上建立以塔釜再沸器热负荷最小化和产物收率(氨气+酸性气)最大化为优化目标的多目标优化模型。由于化工流程的特殊性,对现有的多目标粒子群算法进行改进,加入边界检验以提升运算速度。运用改进后的算法对模型进行求解,得到一组Pareto解集。以目前工况为基准,选定2个Pareto解进行分析。结果表明,在维持当前塔釜再沸器热负荷基本不变的情况下,产物收率增加10.21%;在维持当前产物收率基本不变的情况下,塔釜再沸器热负荷降低16.98%。     

催化重整过程的多目标优化

In this article, a multiobjective optimization strategy for an industrial naphtha continuous catalytic reforming process that aims to obtain aromatic products is proposed. The process model is based on a 20-lumped kinetics reaction network and has been proved to be quite effective in terms of industrial application. The primary objectives include maximization of yield of the aromatics and minimization of the yield of heavy aromatics. Four reactor inlet temperatures, reaction pressure, and hydrogen-to-oil molar ratio are selected as the decision variables. A genetic algorithm, which is proposed by the authors and named as the neighborhood and archived genetic algorithm （NAGA）, is applied to solve this multiobjective optimization problem. The relations between each decision variable and the two objectives are also proposed and used for choosing a suitable solution from the obtained Pareto set.     

芳烃抽提过程多目标优化

芳烃抽提是芳烃生产过程的重要环节,其生产调优对提高整个芳烃联合装置的效益具有重要意义。基于流程模拟及响应面分析方法,得到了芳烃抽提过程的产品纯度模型及能耗模型。建立了以产品纯度最大化及过程能耗最小化的多目标优化模型。提出了一种改进的自适应加权求和算法,并用于多目标优化模型的求解。求解结果表明新算法在Pareto最优解分布的均匀性上与原算法相当,但求解效率要高于原算法。给出了不同产品等级下的最佳操作参数,采用优化后的操作参数可有效地提高产品纯度并降低过程能耗。提出的多目标优化模型及求解算法用于芳烃抽提过程的操作调优,可有效地提高决策的准确性。     

基于全流程模拟的催化裂化装置多目标优化

应用流程模拟软件Petro SIM对催化裂化装置进行了全流程模拟,采用平均影响因子法从15个独立可调的变量中筛选出7个影响产品分布的主要优化变量,以各产品质量指标为约束,建立了液化石油气和汽油产量最大化的双目标优化模型,应用多目标列队竞争算法对该优化模型求解,所得Pareto最优解集揭示了液化石油气、汽油和柴油产量的分布规律. 根据市场对不同产品需求的变化,确定了5种优化操作方案,调整催化裂化装置的多产品方案.     

进化多智能体技术在多目标优化中的应用

针对多目标优化研究中传统遗传算法存在的一些问题,引入人工智能领域新兴发展起来的多智能体技术,结合遗传算法形成进化多智能体系统来求解多目标优化问题.主要对进化多智能体系统框架、进化遗传算法进行了论述.     

电-气互联系统的多目标优化

针对电-气互联系统的运行成本(包括电力系统成本和天然气系统成本)和污染排放成本综合优化问题,在粒子群优化算法的基础上利用Pareto优势原理挑选最优解,获得Pareto非劣解集.以IEEE5-NGS10构成的电-气互联系统为例进行多目标优化计算,求解Pareto曲线,并根据所得Pareto曲线找出了多目标优化的最优解,...     

废物最小化的过程集成方法及多目标优化

By avoiding or reducing the production of waste, waste minimization is an effective approach to solve the pollution problem in chemical industry. Process integration supported by multi-objective optimization provides a framework for process design or process retrofit by simultaneously optimizing on the aspects of environment and economics. Multi-objective genetic algorithm is applied in this area as the solution approach for the multi-objective optimization problem.     

初探芳烃抽提过程多目标优化策略

芳烃抽提是芳烃生产过程中的重要环节,对于提高整个芳烃联合装置的效益意义重大。建议以产品纯度最大化的流程方案,降低能耗损失,是芳烃抽提过程多目标优化的最优策略。本文就芳烃抽提过程多目标优化策略进行分析,提出优化模型及算法,以此提高决策的准确性。     

工业PTA氧化过程的多目标优化

Multi-objective optimization of a purified terephthalic acid (PTA) oxidation unit is carried out in this paper by using a process model that has been proved to describe industrial process quite well. The model is a semiempirical structured into two series ideal continuously stirred tank reactor (CSTR) models. The optimal objectives include maximizing the yield or inlet rate and minimizing the concentration of 4-carboxy-benzaldhyde, which is the main undesirable intermediate product in the reaction process. The multi-objective optimization algorithm applied in this study is non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The performance of NSGA-II is further illustrated by application to the title process.     

基于软件集成的常减压蒸馏装置的全流程模拟与优化

根据炼油厂提供的数据,利用Aspen Plus Pinch和B-JAC等软件分别实现了常减压蒸馏车间的主装置模拟、换热网络优化和旧换热器的校核及新换热器的设计。并最终实现了整个车间的全流程模拟,为常减压蒸馏装置的改造奠定了基础。     

多目标质量压气机实验叶片注射成型工艺参数优化

为获得综合质量较高的发动机低速实验台所用树脂叶片,提出并研究了叶片多目标质量优化方法。以叶片翘曲量、收缩率、残余应力为优化目标,模具温度、熔体温度、注射时间、保压时间、保压压力、冷却时间为优化变量,模拟叶片成型过程,获得不同参数组合下的翘曲量、收缩率以及残余应力数据,并基于回归分析建立工艺参数与各质量目标间的映射关系;然后通过层次分析法计算各质量目标的权重,进而建立叶片注射成型多目标质量优化数学模型,最后基于遗传算法对叶片注塑工艺参数进行优化。实验验证表明,优化的工艺参数可显著提高叶片成型质量。     

化工过程分离循环系统的多目标模糊优化研究

Separation-recycle system is an important part in chemical process, and its optimization is a multiobjective problem. In this paper the process optimization procedure is proposed. The fuzzy optimization algorithm with the concept of relative importance degree (RID) is utilized to transfer multi-objective optimization (MO-O) model into a single-objective optimization (SO-O) framework. The treatment of process condensate in synthesisa mmonia plant is taken as example to illustrate the optimization procedure, and the satisfactory result demonstrates feasibility and effectiveness of the suggested method.     

过程系统的能量综合和优化

本文论述了从能量变化的角度分析过程系统以及按照Ｙｏｎｇ经济学关系建立系统优化的目标函数和约束条件的必要性，概述了按照过程系统能量结构特点所建立的三环节Ｙｏｎｇ经济分析模型，及其在四类子系统－单元过程设备两级能量综合优化中的应用。然后讨论了全局综合优化问题，介绍了以Ｙｏｎｇ经济学为基础提出的３个全局综合优化策略：子系统分解协调优化、复合措施和全局改进方案的Ｙｏｎｇ经济评价调优，及这一系统方法的研究、     

甲醛生产过程能量综合优化

通过对甲醇氧化、甲醛吸收等工艺改进及过程能量优化,实现甲醛生产装置的高产低耗。介绍了传统银催化法甲醛生产工艺流程和过程用能特点,对甲醛生产各个环节进行了用能分析,找出过程用能的薄弱环节,从全局角度进行综合优化,提出甲醛生产工艺优化流程和相应的用能优化措施。     

多目标过程系统优化的粒子群算法求解

化工领域的过程设计、生产控制、配方和计划等众多问题的数学模型,在考虑产品性能、单位成本、环境影响等诸多因素下,都是多目标优化问题;而求解多目标优化问题,目前还没有有效的方法;现今的做法是把多目标优化通过加权转化为单目标优化,再求解单目标优化问题,但这存在权数不易确定;还忽视了有效解集中存在一个其各目标的值与各目标的最优值距离最近的有效解的问题,称为理想有效解.理想有效解的求法一般分为两步,先求各目标的最优值、再求理想有效解,这将影响求解的速度;为此提出在PSO(粒子群优化)算法中加入惩罚项,同时对PSO算法中的个体极值与全局极值作调整,使PSO算法适用于求多目标优化问题理想有效解,该算法对多目标问题起到边优化边求理想有效解的功效;这使得在求解速度上加快.通过性能测试表明了算法的有效性,最后将算法用于求解多亚甲基多苯基多胺生产过程系统优化取得良好效果.     

炼油厂氢气网络建模与多目标优化(英文)

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming (MINLP). A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.