基于被控变量在线建模的化工过程实时优化方法

选择合适的被控变量可对过程进行实时优化(RTO),但现有方法在设计阶段确定被控变量后,不允许对其进行在线调整,导致了RTO效果的局限性。针对这一问题,提出了一种基于被控变量在线建模的方法,使用局部建模技术在线寻找相似样本并建立一阶最优性必要条件(NCO)的估计模型,将其作为被控变量更新控制回路,在反馈控制作用下达到更好的RTO效果。对一个蒸发过程的研究表明,此方法能够通过对NCO的在线准确建模,增加生产过程的经济效益。     

Robust dynamic optimization for nonlinear chemical processes under measurable and unmeasurable uncertainties

We formulate an integrated framework for the robust dynamic optimization of nonlinear chemical processes under measurable and unmeasurable uncertainties. An affine decision rule is proposed to approximate the causal dependence of the wait-and-see decision variables on the gradually revealed measurable uncertainties. To overcome the computational intractability of the proposed model, a linearization technique based on the first-order Taylor expansion is introduced around the nominal values of uncertainties to derive the robust dynamic counterpart, which can be discretized to a large-scale nonlinear programming (NLP) formulation. Effects of first discretizing the dynamic models or introducing the affine decision rule are investigated. The proposed framework is also compared with the state-of-the-art re-optimization and traditional robust optimization approaches. An illustrative example and an industrial semi-batch 2-mercaptobenzothiazole production case are involved to demonstrate the advantages and applicability of the proposed framework.     

化工流程模拟技术研究进展

化工流程模拟技术结合了化工和信息技术,在计算机上通过严格的数学模型模拟出化工工艺过程。从而得到关于操作、经济、环境等多种条件的最优解,为实际的工艺工程操作提供理论支撑。比起传统的实验室的小试与中试,它节省了大量的人力和物力,受到许多的化工工作者的青睐。然而,市面上关于化工流程模拟的模拟软件多种多样,功能与侧重点各相不同。本文选取了Aspen Plus、Hysys、Pro/Ⅱ、ChemCAD、gPROMS共5种常用的流程模拟软件。针对它们不同的功能与特点进行了较为详细的介绍,并总结了各个软件在各种工艺流程中的应用成果,提出了今后的流程模拟技术应能整合多种串联工艺,在工厂级、企业级甚至地区级的层面上进行模拟优化,为化工行业的全面清洁生产提供理论与技术支持。     

Conceptual design and optimization of chemical processes under uncertainty by two-stage programming

This contribution presents a method and a tool for modelling and optimizing process superstructures in the early phase of process design where the models of the processing units and other data are inaccurate. To adequately deal with this uncertainty, we employ a two-stage formulation where the operational parameters can be adapted to the realization of the uncertainty while the design parameters are the first-stage decisions. The uncertainty is represented by a set of discrete scenarios and the optimization problem is solved by stage decomposition. The approach is implemented in the computer tool FSOpt (Flow sheet Superstructure Optimization) FSOpt provides a flexible environment for the modelling of the unit operations and the generation of superstructures and algorithms for the translation of the superstructure into non-linear programming models.The approach is applied to two case studies, the hydroformylation of dodec-1-ene and the separation of an azeotropic mixture of water and formic acid.     

Enterprise-wide optimization in an integrated chemical complex

An integrated chemical production complex provides a rich environment for the application of enterprise-wide optimization techniques. A world scale site can be composed of dozens of production plants manufacturing hundreds of products. This paper discusses the nature of an integrated chemical production site to identify the opportunities for enterprise-wide optimization. It shows how the site is composed of sub-systems, called envelopes, which involve the production of a basic chemical and its downstream derivatives or comprise a network of units that provide an important utility. Several planning and operational challenges in these envelopes are shown to be excellent optimization opportunities. The challenge of waste disposal scheduling is presented in detail along with a solution using a resource task network.     

化工过程本质安全评估方法研究进展与展望

可持续性发展已经成为社会、生态和经济发展的关键。可持续制造的发展道路需要平衡环境、社会和经济各方面。本质安全设计是减少风险、实现化学工业可持续发展的最有效的方法之一,本质安全设计可以永久性地消除或减少化工过程中涉及的危害。本文综述了本质安全的历史发展、本质安全四大原则的概念、本质安全四大原则应用的使用潜力、本质安全设计评估工具,并系统介绍了本质安全设计评估方法的研究进展和存在的问题,包括基于参数的得分索引本质安全方法、基于参数的数值索引本质安全方法、基于图示的本质安全方法、基于风险分析的本质安全方法和基于多目标评价的本质安全方法,分析比较了各种方法的优缺点,并对本质安全评估方法的未来发展和完善提出了一些见解。     

一种改进的知识进化算法及其在化工动态优化中的应用

智能优化算法在动态优化问题的求解中,一方面可以一定的概率收敛到全局最优,避免局部极值而得到了广泛应用;但另一方面,基于随机机制的仿生智能算法也面临收敛速度慢、寻优效率较低的瓶颈,限制了其工业实时应用的场合。为此,从提高智能优化算法在动态优化问题的求解效率出发,提出了一种改进的基于知识引导的进化算法结构,主要包括候选控制策略-时域与控制域的离散策略、知识库空间的进化、知识引导的种群进化。该算法分别在批式反应器等4个典型化工动态优化问题上进行了仿真验证,计算结果表明,该方法能够以较小的种群规模通过知识的引导,以较少的计算代价找到较好的全局解,有效提高了算法的收敛效率。     

微粒群算法优化化工建模训练集

提出两种均以微粒群(PSO)算法对原始训练集随机抽样优化,再结合机器学习算法建立预测模型的PSO算法优化化工建模训练集的思路。思路1首先以模型交叉验证的均方误差函数mse最小为目标优化训练集,再通过对验证集预测,从平行运行得到的多个优化训练集中确定最优训练集用于建模。思路2借鉴提高BP神经网络泛化能力的初期终止(early stop)法,以对验证集预测的mse最小为目标优化训练集,再通过对测试集预测,从平行运行得到的多个优化训练集中确定最优训练集用于建模。通过仿真实验研究和对某炼油厂调和汽油生产数据的具体分析应用,表明本文思路可以较大幅度提高模型的预测准确性,在化工建模中具有推广应用价值。     

An improved intelligent early warning method based on MWSPCA and its application in complex chemical processes

With the development of industrial automation, the requirement of abnormal early warning in the industrial production process is getting higher and higher. Facing complex chemical processes, traditional fault detection and abnormal early warning methods have low detection efficiency and poor real-time performance. Therefore, this paper analyzes and studies fault detection and abnormal early warning methods, and puts forward an improved intelligent early warning method based on the moving window sparse principal component analysis (MWSPCA) suitable for complex chemical processes. The sparse principal component analysis algorithm is used to establish the initial early warning model, and then the moving window is used to update the early warning model, which makes the early warning model more suitable for the characteristics of time-varying data. Furthermore, the proposed method reduces the false alarm rate and missed alarm rate of the early warning, and improves the real-time performance of the early warning model. Finally, the feasibility and the validity of the proposed method are verified by the TE process and the oil drilling process. The experiment results show that the proposed method can reduce the risk of complex chemical processes.     

Study on dynamic behavior adjustment of nonlinear chemical processes

In nonlinear chemical processes, many economically desirable operating conditions are located in unstable regions, leading to product quality degradation and safety problems. Therefore, determining how to adjust the dynamic behavior to make the process stable within its desired operational range is a topic of common interest within industrial and academic communities. This article presents a dynamic behavior adjustment method based on a washout filter‐aided controller with an improved parameter‐tuning algorithm to stabilize parts of the equilibrium manifold of chemical processes. In addition, applying this method to industrial toluene liquid‐phase catalytic oxidation shows that, by combining a conventional proportional‐integral (PI) controller with the proposed improved washout filter‐aided controller, the performance of set‐point tracking is improved for cases with parameter uncertainty. In general, the proposed dynamic behavior adjustment method will be effective for most chemical processes. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3189–3198, 2016     

Optimal design of chemical processes with chance constraints

Generally, chemical processes (CP) are designed with the use of inaccurate mathematical models. Therefore, it is important to create a chemical process that guarantees satisfaction of all design specifications either exactly or with some probability. The paper considers the issue of chemical process optimization when at the operation stage the design specification should be met with some probability and the control variables can be changed. We have developed a common approach for solving the broad class of optimization problems with normally distributed uncertain parameters. This class includes the one-stage and two-stage optimization problems with chance constraints. This approach is based on approximate transformation of chance constraints into deterministic ones.     

化工过程大范围工况变化的工况迁移控制策略判定

化工过程出现大范围的工况变化时，复杂的迁移控制策略会带来一定的操作不确定性，因此需要对控制策略进行选择判定。考虑到直接估计工况变化过程生产指标变化量带来的判定误差，引入了中间变量，提出了基于中间变量的控制策略选择判定方法，并分析给出了构建中间变量的基本准则。进而通过对某实际乙烯精馏塔工况变化过程的仿真研究，说明了中间变量的引入能够很大程度地降低对生产指标的估计误差，验证了基于中间变量的控制策略选择判定方法的可用性。     

The impact of surface science on the commercialization of chemical processes

Surface science developed instruments for atomic- and molecular-scale studies of catalyst surfaces, their composition and structure, both in a vacuum and at high pressures, under reaction conditions (bridging the pressure gap). Surfaces ranging from single crystals, nanoparticles and thin films to porous high surface area catalytic materials have been studied. Classes of surface structure sensitive and insensitive reactions have been identified by surface science studies, including ammonia synthesis, hydrodesulfurization, reforming, combustion and hydrogenation. Rates of reactions often vary by orders of magnitude between using the right and the wrong surface structures. The roles of many promoters that modify the catalyst surface structures and bonding of adsorbates have been verified. Surface reaction intermediates could be identified and the mobility of adsorbates and the adsorbate induced reconstruction of the catalysts attest to the dynamic nature of the catalytic systems during the reaction turnover. The important active sites for catalysis include the low coordination surface step, kink, oxygen and chloride ion vacancies sites and sites at oxide-metal interfaces. Uncovering the molecular ingredients of heterogeneous catalysts will have a major impact on the understanding of reaction selectivity to help the evolution of green chemistry and selective reaction of many types.     

高级氧化技术降解吲哚的研究进展

吲哚散发粪便恶臭气味,广泛存在于焦化、染料、化工、制药和农药等工业废水中。由于其特殊的双环稠合结构,靠传统的生物水解断环提高吲哚的降解效果难以为继。本文全面介绍了吲哚的来源、毒性、危害及传统生物降解技术的缺陷,特别论述了高级氧化法（AOPs）中·OH的形成反应及降解吲哚的作用机理。传统AOPs能够高效降解吲哚,但价格昂贵,操作复杂,且使用剂量常受到其他物质的干扰,易引入新的污染物,难以在大规模的水处理工程中应用。因此,认为将AOPs预氧化与生物处理技术进行高效耦合是降解吲哚经济有效的办法。本文最后介绍了硫酸根自由基的高级氧化技术（SR-AOPs）耦合厌氧生物技术降解吲哚的研究及其优点。这些研究对丰富AOPs耦合生物处理技术理论、含氮杂环污染物高效降解及资源化利用有一定的参考价值。     

复杂化工过程失配子模型深度诊断与修正算法

针对复杂化工生产过程中多变量预测控制系统发生模型失配导致控制性能下降造成的产品质量波动的问题，研究了过程失配子模型深度诊断与模型修正方法。考虑到复杂化工生产过程中被控变量为控制通道和扰动通道的综合响应，通过逐次移动操作变量到扰动通道的方法，评价移动后对模型质量指标的影响，从而判断出所移出子模型的性能，进而对失配子模型进行定位。进一步地，利用现场采集的历史数据用自回归滑动平均模型辨识法辨识出失配部分的模型，用于对原有子模型进行修正。实验采用Wood-Berry精馏过程对其进行动态仿真验证，结果证明了该算法的有效性。     

SIMOP: Application to global MINLP stochastic optimization

SIMOP (SIMulation for OPtimization) is an application that automatically creates FORTRAN simulation models for the stochastic optimizers MSGA and MSIMPSA. This paper presents the next step in SIMOP's development timeline, namely its expansion to cope with mixer-integer nonlinear problems (MINLP). From the perspective of MINLP formulations' relevance to the Chemical Engineering field, an introduction to SIMOP's MINLP modeling features is given. Its application is addressed by three case studies. The best results match those previously obtained with MSGA and MSIMPSA when non-automatically coded MINLP simulations where employed, thus validating the present approach. The introduction of discrete variables benefits the performance of both stochastic optimizers, contrary to what should a priori be expected, since a MINLP formulation promotes an accurate search on lower and upper bounds for several continuous variables.     

Practical optimization of complex chemical processes with tight constraints

Stochastic optimization algorithms are introduced for complex chemical processes—using semicontinuous distillation with reaction in a middle vessel as a case study. The processes are dynamic, consisting of several operating modes, and have tight operating constraints to prevent weeping or flooding in the distillation column of the case study. Often intensification leads to fewer processing units, operated in many modes over a cyclic campaign, introducing tight operating constraints. The optimization algorithms examined include a modified univariate technique for N-dimensions, the particle swarm method, the simplex method, and others. These methods are used jointly in a bi-level algorithm, and are tested for speed and quality of result.     

微波强化化工过程技术进展

化工过程强化是企业节能减排的主要途径,化工过程强化手段有多种,简要介绍了微波在催化、合成、萃取、降解及破乳过程的强化作用机理,并介绍了微波在这些过程中的强化效果与应用进展。     

Framework of dynamic simulation for complex chemical processes

The current state of the art of a modelling and dynamic simulation system for complex chemical and biochemical processes is discussed. Process modelling activity involves modelling a physical plant and external tasks imposed on the plant, and details of both aspects are discussed. Typical software structure is concerned with a model builder, result analyser, translator, solution methods, model library and external software interface. Some of them are explained in moderate depth. Recent progress of functionality and numerical methods is presented. Numerical methods incorporating symbolic and structural techniques improve accuracy and efficiency. In order to illustrate benefits of employing dynamic simulation tools, one typical chemical process consisting of a mixing tank, tubular reactor and gas absorber is chosen and dynamic simulation is carried out. Taking into account the work in this paper, some suggestions for future development of a unified framework of a modelling package are made.