慢时变化工过程裕量释放机制分析

化工过程普遍存在慢时变特性,在一个运行周期内慢时变参数的变化造成化工装置性能逐渐下降。为此,过程设计时需要按照慢时变参数可能的“最坏”影响对设计变量留出足够的设计裕量,在一个运行周期内通过操作逐渐释放,补偿慢时变参数的不利影响,且理想操作是保证到运行周期结束时化工装置性能恰好达到过程约束边界。本文对慢时变过程设计裕量的释放机制进行了分析,考虑含慢时变参数的全周期操作优化通用动态模型,通过最优控制的极小值原理求解该优化问题,建立了最优裕量释放轨迹和慢时变参数变化曲线之间的联系,从而证明最优裕量释放只与慢时变化工过程的运行周期有关。以乙炔加氢反应器为例验证了该裕量释放机制,对于慢时变化工过程,设定的运行周期越短,设计裕量释放越快,仅能获得较高的短期经济效益;反之,设定较长的运行周期,设计裕量缓慢释放,能获得更高的长期经济效益。     

化工过程总体裕量与控制性能的权衡优化

化工过程的总体裕量可以用操作优化的经济效益进行评价,根据稳态优化和动态优化的经济效益可进一步划分为服务于操作控制的控制裕量和表征过程可实现经济效益的工艺裕量,二者都与化工过程的控制性能有关。针对具有一定裕量的化工过程进行多目标动态优化,优化目标分别为操作点的经济效益与动态过程中的控制性能指标,采用0-1变量描述控制结构,将控制结构和控制器参数也作为优化变量进行混合整数动态优化,采用Constrained NSGA-Ⅱ算法求解非劣解集,根据非劣解集分析总体工艺裕量、总体控制裕量与控制性能指标的关系。通过催化裂化装置的实例分析发现,对于具有一定裕量的化工过程,控制性能越高,所需的总体控制裕量越多,表征操作优化可实现经济效益的总体工艺裕量越少,只有通过对总体控制裕量和总体工艺裕量进行权衡,才能找到兼顾工艺要求和控制性能的工艺操作点和控制设计方案。     

化工过程总体裕量与控制性能的权衡优化

化工过程的总体裕量可以用操作优化的经济效益进行评价,根据稳态优化和动态优化的经济效益可进一步划分为服务于操作控制的控制裕量和表征过程可实现经济效益的工艺裕量,二者都与化工过程的控制性能有关。针对具有一定裕量的化工过程进行多目标动态优化,优化目标分别为操作点的经济效益与动态过程中的控制性能指标,采用0-1变量描述控制结构,将控制结构和控制器参数也作为优化变量进行混合整数动态优化,采用Constrained NSGA-Ⅱ算法求解非劣解集,根据非劣解集分析总体工艺裕量、总体控制裕量与控制性能指标的关系。通过催化裂化装置的实例分析发现,对于具有一定裕量的化工过程,控制性能越高,所需的总体控制裕量越多,表征操作优化可实现经济效益的总体工艺裕量越少,只有通过对总体控制裕量和总体工艺裕量进行权衡,才能找到兼顾工艺要求和控制性能的工艺操作点和控制设计方案。     

基于优先级的烧结过程协调优化控制系统

烧结过程是一个复杂的物理、化学反应过程,存在大滞后性、强非线性、多目标、多约束条件等控制难点。为了实现铁矿石烧结过程中混合料料槽料位和烧结终点这两个关键参数的综合控制,提出了一种基于优先级的协调优化控制方法。首先,通过综合运用神经网络预测和模糊控制,建立烧结终点的智能控制模型;同时,为了稳定混合料料槽料位,分析影响料槽料位的主要因素,基于专家知识建立了混合料料槽料位专家控制模型;然后,通过构造基于优先级的协调优化控制模型,在优先级控制的基础上采用软切换控制,将两个控制器相结合,获得最适宜的速比以及台车速度增量,实现烧结生产过程的协调优化控制。最后,针对该协调控制策略,设计了其工厂实现方案。     

基于相对增益分析的换热网络旁路设计

提出一种考虑了可控性的换热网络旁路设计法。基于稳态模型增益的定量计算,推导换热网络稳态数学模型的求解过程,从可控性分析的角度逐一求解换热网络的非方相对增益矩阵,从中确定最优的旁路位置,使被控变量具有较高的可控性。突破相对增益矩阵仅用于控制配对的常规范畴,提出一种通过逐次求解换热网络非方相对增益矩阵优化选取最优旁路设置的方法,并给出了设置旁路的若干准则,以简化求算过程。分析稳态工作点变化后的情况,表明工况变化不影响上述得出的旁路设置。该法适用于大型复杂换热网络,满足生产控制要求,并能保证整个换热网络具有较高的可控性。以某常减压蒸馏装置脱盐前换热网络为例,验证方法的可行性和有效性。     

基于动态优化的催化裂化装置再生器裕量分析与控制设计（Ⅰ）动态优化的数学描述

从操作和控制的角度,通过动态优化的方法求解催化裂化装置再生器的工艺裕量与控制设计。该动态优化问题的数学描述包括催化裂化装置反应-再生系统和配套控制系统的动态模型、多回路PID控制器结构模型、过程不确定性模型、稳态起始点约束、生产要求和操作约束及目标函数等。该优化问题是一个带有0-1变量约束的多目标混合整数动态优化问题,具有分别描述控制性能指标和工艺指标的两个不相关目标函数。对两个优化目标进行折中处理,可以使设计结果既能满足工艺要求,又能实现良好的自动控制。     

基于动态优化的催化裂化装置再生器裕量分析与控制设计(Ⅱ) 求解方法与结果分析

用动态优化的方法求解催化裂化装置再生器的工艺裕量与控制设计。对于该多目标混合整数动态优化问题,通过ε-约束法处理多目标优化问题,将控制性能目标函数转化为控制性能约束;通过将0-1变量松弛化、引入附加等式约束求解混合整数动态优化问题。求解得到非劣解集,绘制关于控制性能指标和工艺指标的关系曲线,发现系统对控制器性能的要求愈高,所需要的裕量应愈大。由此进行折中处理,从而找到兼顾工艺要求和控制性能的催化裂化装置再生器优化设计方案。     

先进控制条件下化工过程操作裕量与控制性能分析

引言化工过程的设计裕量可以定义为考虑过程不确定参数(包括工艺条件、设备条件、外来扰动)发生变化时为满足生产和操作要求需要在正常操作的标称设计值上增加的量。设计裕量根据其属性可以     

过程模拟优化在化工工艺设计中的应用研究

化工工艺设计是保证企业各方面效益的基础,运用过程模拟优化的方式,可以保证工艺设计的科学性。在本文中,首先阐述化工过程模拟优化的技术。然后结合具体的应用案例,分析过程模拟优化在化工工艺设计中的应用方式、效果。基于此,可以为相关人员提供参考,同时彰显过程模拟优化的价值,为提高化工工艺设计的效果提供保障。     

化工过程模拟优化的演变优化方法

研究了化工过程模拟优化的一类新方法——过程演变优化方法,提出基于ＤＮＮ（动态人工神经网络）的动态算法的统一框架,阐明其并行分布计算特性,并给出一些基于过程规划的计算动力学模型。     

Release mechanism analysis of design margin for slowly-time-varying chemical processes

Slowly-time-varying characteristics are common in chemical processes, and the changes of slowly-time-varying parameters in an operating cycle gradually decrease the performance of chemical process. So, enough margins must be added for design variables during the phase of process design according to the possible worst-case influence of slowly-time-varying parameters. The design margins will be released gradually compensating the worse influence of slowly-time-varying parameters in an operating cycle. It can be called as a perfect operation that the operating point is on the boundary of process constraints when an operating cycle is ending. In this paper, the margin release mechanism of slowly-time-varying chemical processes is analyzed. Based on the universal dynamic model containing slowly-time-varying parameters, the full cycle operation optimization is solved by minimum principle of optimal control. It is found that the optimal margin release trajectory is related to the curve of slowly-time-varying parameter, ensuring that the optimal margin release is only dependent on the operating cycle. This mechanism is verified by the example of acetylene hydrogenation reactor. For slowly-time-varying chemical processes, the shorter the operating cycle is set, the faster the design margin is released, the higher temporary economic benefit is obtained; otherwise, the longer the operating cycle is set, the more integrated economic benefit is accomplished.     

Optimal experimental design for optimal process design: A trilevel optimization formulation

Typical optimal experimental design (OED) methods aim at minimizing the covariance matrix of the estimated parameters regardless of the intended application of the model that is being estimated. This can unnecessarily increase the experimental costs. Herein, we propose a new OED method, which tailors the designed experiments to the model application. The method is demonstrated for model-based process design and aims at mitigating a worst-case realization of the process design. The proposed formulation results in a min–max–min problem and is based on bounded-error OED. The method is illustrated via an ad hoc solution method using two examples, a simple illustrative example and the van de Vusse reaction, that show the differences between typical and the new tailored OED method: experimental designs can be considered good using the latter method, while the same design would be considered bad with the former methods.     

化工过程设计的多目标不确定优化研究

In many circumstances, chemical process design can be formulated as a multi-objective optimization （MOO） problem. Examples include bi-objective optimization problems, where the economic objective is maximized and environmental impact is minimized simultaneously. Moreover, the random behavior in the process,property, market fluctuation, errors in model prediction and so on would affect the performance of a process. Therefore, it is essential to develop a MOO methodology under uncertainty. In this article, the authors propose a generic and systematic optimization methodology for chemical process design under uncertainty. It aims at identifying the optimal design from a number of candidates. The utility of this methodology is demonstrated by a case study based on the design of a condensate treatment unit in an ammonia plant.     

A survey on applications of optimization-based integrating process design and control for chemical processes

Process design and control are closely related to each other in chemical engineering activities. Traditionally, process design and control system design are carried out in sequence. However, the integration of process design and control (IPDC) can bring greater economic benefits and process dynamic performance than traditional sequential design methods. This is true, particularly for modern chemical processes, in which various process units become more interacting and compact owing to the widespread use of heat integration and recycled streams, and the resulted impacts between process design and control begin to significantly influence both the capital and operational costs. Recently, considerable studies about the IPDC for chemical processes have been reported in published literature. The purpose of the paper is to survey the applications of optimization-based integrating process design and control for chemical processes. Firstly, attention has been focused on the applications of IPDC to different process units, for example, chemical reactors and separation columns. Then, the survey is extended to the applications of IPDC to plant-wide chemical processes. Finally, the future research challenges in the application of IPDC to chemical processes have been briefly discussed.     

Optimization‐based support for process design under uncertainty: A case study

The use of two‐stage stochastic optimization for the support of the solution of process design problems in the early phase of process development where the different potential elements of the production process can only be described with significant uncertainty is discussed. The first stage variables are the design decisions which are fixed after the process has been built, while the second stage variables are the operational parameters which can be adapted to the realization of the uncertainties. The application of the approach to the design of a hydroformylation process in a thermomorphic solvent system is demonstrated. The proposed designs which are computed using the software framework FSOpt are analyzed and compared using different graphic representations which provide insight into what the most important design decisions are. Finally, the experience with the proposed formulation and solution techniques and point out where further advances are needed is reviewed. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3404–3419, 2016