Inferential Control of Reactive Destillation Columns – An Algorithmic Approach

Decentralized control system design comprises the selection of a suitable control structure and controller parameters. Here, mixed integer optimization is used to determine the optimal control structure and the optimal controller parameters simultaneously. The process dynamics is included explicitly into the constraints using a rigorous nonlinear dynamic process model. Depending on the objective function, which is used for the evaluation of competing control systems, two different formulations are proposed which lead to mixed‐integer dynamic optimization (MIDO) problems. A MIDO solution strategy based on the sequential approach is adopted in the present paper. Here, the MIDO problem is decomposed into a series of nonlinear programming (NLP) subproblems (dynamic optimization) where the binary variables are fixed, and mixed‐integer linear programming (MILP) master problems which determine a new binary configuration for the next NLP subproblem. The proposed methodology is applied to inferential control of reactive distillation columns as a challenging benchmark problem for chemical process control.     

Maintenance scheduling and process optimization under uncertainty

In this paper, we describe an optimization framework for (i) deriving optimal maintenance policies in continuous process operations in the presence of parametric uncertainty and (ii) analyzing and quantifying the impact of uncertainty on optimal maintenance schedules. A systems effectiveness measure is introduced which depends on expected process profitability and process and reliability/maintenance characteristics. A mixed integer nonlinear optimization model is proposed which aims at identifying the number of maintenance (preventive or corrective) actions required over a given time horizon of interest, the time instants and sequence of these maintenance actions on the various components of the process system, so that the system effectiveness is maximized. By introducing the concept of availability threshold values, it is shown that an efficient solution strategy can be established which requires the solution of much smaller nonlinear optimization problems. The application of the proposed framework to an example problem highlights the important interactions between process operation and maintenance scheduling in the presence of uncertainty.     

化工过程综合问题MINLP算法中整型变量的连续化

化工过程系统综合问题需要同时考虑设备结构参数和工艺操作参数,一般用整型变量表示设备的取舍,用连续变量表示操作参数,这就构成一个流程的超结构,在数学形式表现为一个混合整型非线性规划（MINLP）问题。混合整型非线性规划问题的求解成为化工过程综合优化的关键。今根据超结构中整型变量的特征,提出整型变量连续化处理的思路,将MINLP问题简化为NLP问题,然后采用罚函数法求解。最后将该算法运用于加氢脱烷基化（HDA）过程综合的实例研究,结果表明该算法克服了传统方法在处理整型变量时出现的麻烦,为有效快速地进行化工过程综合优化问题提供了一种新的途径。     

Optimal model-based aeration control policies in a sequencing batch reactor

We present a non-linear programming formulation for the computation of optimal aeration policies in a sequencing batch reactor for wastewater streams treatment. We assume that organic matter and nitrogen are the main pollutants to be removed to meet water quality targets. The novelty of the work lies in the fact that no binary variables are required to compute the switching time between the aerobic and anoxic stages of the water treatment process leading to a simpler, robust and easier to compute optimization formulation. Moreover, because the control valve, through which air is fed to the reactor, can take either its minimum or maximum bounds as well as any fractional values between such bounds, improved optimal aeration profiles are reported. Such improved profiles mean that shorter processing times are required, compared to previous solutions, leading also to a reduction in the operation cost of the wastewater treatment process. Although the optimal operation policies were computed for a typical home wastewater stream, the optimization formulation can also be extended for the treatment of other polluted streams.     

悬浮填料单元在活性污泥改造中的应用

将悬浮填料装填入格网,制成体积一定的悬浮填料单元。分别投入曝气池的厌氧区和好氧区,形成悬浮填料和活性污泥复合工艺中试系统。然后,考察在复合系统在不同填料填充率、曝气量和水力停留时间的氨氮去除率。我们发现最优条件下,氨氮去除率较高,复合系统最稳定。最优条件为：填充率为35%;好氧段曝气量为5 m3/h,厌氧段曝气量为0.3 m3/h;水力停留时间为8 h。在此条件下,氨氮去除率比活性污泥工艺提高了18%。     

基于微粒群优化算法的不确定性调和调度

Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimization problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization （PSO） algorithm is developed for nonlinear optimization problems with both continuous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.     

Sensor network design for maximizing process efficiency: An algorithm and its application

Sensor network design (SND) is a constrained optimization problem requiring systematic and effective solution algorithms for determining where best to locate sensors. A SND algorithm is developed for maximizing plant efficiency for an estimator‐based control system while simultaneously satisfying accuracy requirements for the desired process measurements. The SND problem formulation leads to a mixed integer nonlinear programming (MINLP) optimization that is difficult to solve for large‐scale system applications. Therefore, a sequential approach is developed to solve the MINLP problem, where the integer problem for sensor selection is solved using the genetic algorithm while the nonlinear programming problem including convergence of the “tear stream” in the estimator‐based control system is solved using the direct substitution method. The SND algorithm is then successfully applied to a large scale, highly integrated chemical process. © 2014 American Institute of Chemical Engineers AIChE J, 61: 464–476, 2015     

氧化沟不同分区脱氮除磷研究

采用混合反应器模拟氧化沟运行方式,探讨氧化沟不同好氧缺氧分区对脱氮除磷效果的影响。结果表明,在分点曝气氧化沟系统中氧传质推动力大,溶氧效率高,在相同的供氧条件下,其一个循环的好氧区比分段曝气系统好氧区长,但是分点曝气系统有机物耗氧多,DO浪费大,而分段曝气溶氧效率低,但DO的有效利用率(用于脱氮除磷)高,二者硝化能力相当,NH4+-N去除率分别为96.68%和97.03%,硝化菌活性分别为4.65、4.66 mg.g-1.h-1。在好氧区和缺氧区比例相同的条件下,分区越多,有机物被好氧异养菌利用的越多,脱氮除磷效果越差。分区减少,可以有效地增加反硝化菌对碳源的利用,对提高脱氮效果更有利。在同样的供氧条件下,分段曝气单个A/O分区长,反硝化菌和聚磷菌对碳源利用多,脱氮除磷效果优于分点曝气,在满足硝化的前提下,缺氧区和好氧区比例越大,碳源被利用的越完全,对脱氮除磷越有利,DO的有效利用率也越高,此时越接近于前置缺氧-好氧(A/O)工艺。     

污水好氧生物处理工艺中供气系统的优化与节能分析

对于污水好氧生物处理技术而言,供气系统包括曝气方式/装置、气体输送管线、曝气器(气体释放头)、反应器/反应池以及结合运行程序的监控仪表等,以节能降耗作为考察目标,本文全面分析了供气系统中的常见曝气方式的适用范围、影响因素、优化控制与节能途径.以鼓风曝气方式为主要考察对象,分析了空气从风机到曝气池释放的全过程耗能及节能途...     

Short-term scheduling and recipe optimization of blending processes

The main objective of this paper is to develop an integrated approach to coordinate short-term scheduling of multi-product blending facilities with nonlinear recipe optimization. The proposed strategy is based on a hierarchical concept consisting of three business levels: Long-range planning, short-term scheduling and process control. Long-range planning is accomplished by solving a large-scale nonlinear recipe optimization problem (multi-blend problem). Resulting blending recipes and production volumes are provided as goals for the scheduling level. The scheduling problem is formulated as a mixed-integer linear program derived from a resource-task network representation. The scheduling model permits recipe changeovers in order to utilize an additional degree of freedom for optimization. By interpreting the solution of the scheduling problem, new constraints can be imposed on the previous multi-blend problem. Thus bottlenecks arising during scheduling are considered already on the topmost long-range planning level. Based on the outlined approach a commercial software system has been designed to optimize the operation of in-line blending and batch blending processes. The application of the strategy and software is demonstrated by a detailed case study.     

Optimization of cleaning schedulesin heat exchanger networkssubject to fouling

Many heat exchanger networks in continuous processes are subject to fouling, which causes significant losses in efficiency over time. This paper addresses the problem posed in scheduling cleaning operations in order to maintain optimal operation in such networks. A mixed integer nonlinear programming modelis presented and is solved using the Outer Approximation/Extended Relaxation algorithm. The methodology is demonstrated via case studies using fouling rates obtained from plant data studies. Both linear and asymptotic fouling behaviors are considered. The challenges posed by the nonconvexity of the problem in finding a global optimum are discussed.     

Smooth penalty function method for rigorous optimization of distillation processes

Integer decisions on stage numbers and feed locations, and global optimality are still challenging for rigorous optimization of distillation processes. In the present article, we propose a smooth penalty function method to address both these problems. The proposed method is based on the relaxation of the integer decision problem into continuous nonlinear programming (NLP) problem by adopting the bypass efficiency model developed by Dowling and Biegler. A smooth penalty term (SPT) is proposed and added to the total annual cost (TAC) function to form a new objective function, namely, the smooth penalty function. Using the new objective function, the problem is initially solved with negative weight coefficients for the SPTs regarding each column section to get an optimum near the global optimum of the SPT. Then, starting from this solution, the problem is solved again iteratively by increasing the values of the weight coefficients until all the stage numbers become integers. The performance of the method is validated by an illustrating problem and in three case studies, including a reactive distillation optimization problem.     

A hybrid optimization strategy for simultaneous synthesis of heat exchanger network

The heat exchanger network synthesis problem often leads to large-scale non-convex mixed integer nonlinear programming formulations that contain many discrete and continuous variables, as well as nonlinear objective function or nonlinear constraints. In this paper, a novel method consisting of genetic algorithm and particle swarm optimization algorithm is proposed for simultaneous synthesis problem of heat exchanger networks. The simultaneous synthesis problem is solved in the following two levels: in the upper level, the network structures are generated randomly and reproduced using genetic algorithm; and in the lower level, heat load of units and stream-split heat flows are optimized through particle swarm optimization algorithm. The proposed approach is tested on four benchmark problems, and the obtained solutions are compared with those published in previous literature. The results of this study prove that the presented method is effective in obtaining the approximate optimal network with minimum total annual cost as performance index.     

基于全局正交配置的非线性预测控制算法

针对非线性预测控制(NMPC)在线优化计算量大这一关键问题,提出一种基于全局正交配置的非线性预测控制算法。该算法以高阶插值正交多项式为基函数同时配置优化时域内的状态变量和控制变量,将连续动态优化问题转化为非线性规划问题(NLP)求解。全局正交配置可以使用较少的配置点而获得较高的逼近精度,这样即使NMPC使用很长的优化时域,离散化后得到的NLP问题的规模也比较小,能够有效地降低在线优化计算量。最后,以连续聚合反应过程为例验证了算法的有效性。     

混合粒子群算法用于共沸精馏塔的最优设计

提出了一种适于求解混合整数非线性规划问题的混合粒子群优化算法,并将其与化工过程模拟软件相结合,用于共沸精馏塔的最优设计。优化模型以年度总费用最小为目标,以精馏段板数、提馏段板数和回流比为优化变量,并引入流体力学约束使得优化结果更具实际价值,并以效率更高的"轮盘赌"式策略处理整数变量,约束处理采用Deb方法。最终以C++实现优化算法,C#编制界面,通过商业模拟软件Aspen Plus计算粒子适应度,将本方法用于一个醋酸甲酯/甲醇/水三元共沸组成的分离案例,所获最优年度总费用优于文献结果。     

Optimization of large‐scale water transfer networks: Conic integer programming model and distributed parallel algorithms

The optimization of a multi‐echelon water transfer network (WTN) and the associate transportation and inventory systems with demand uncertainty is addressed in article. Optimal network structure, facility locations, operation capacities, as well as the inventory and transportation decisions can be simultaneously determined by the mixed integer nonlinear programming (MINLP) model which includes bilinear, square root and nonlinear fractional terms. By exploiting the properties of this model, we reformulate the MINLP problem as a conic integer optimization model. To overcome the memory and computing bandwidth limitations caused by the huge number of active nodes in the branch‐and‐bound search tree, novel distributed parallel optimization algorithms based on Lagrangean relaxation and message passing interface as well as their serial versions are proposed to solve the resulting conic integer programming model. A regional WTN in China is studied to demonstrate the applicability of the proposed model and the performance of the algorithms. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1566–1581, 2017     

SCHEDULING OF CONTINUOUS PARALLEL LINES IN THE EVAPORATION SECTION OF SUGAR PLANTS

Cost reduction in sugar industries can be achieved just by adjusting and optimizing structures and/or key process variables to assure maximum use of the sugar formed in the field. The evaporation section is the critical stage for efficient management of water and energy resources. Thus, the selected case study addresses the optimization of the operation of continuous evaporation units working in parallel and presenting a decrease of in efficiency with time. The problem was solved through mathematical programming that obtained optimum values for the operating variables. Therefore, it was necessary to mathematically formulate the optimization problem and to model the operations under study. A mixed integer nonlinear programming model (MINLP) was used in order to meet the targets. Also, a technical objective function with economical background was developed. The industrial implementation required as well the conception and development of a user-friendly decision-making tool to facilitate the routine work and to allow plant managers to check, accept, and put into practice the solution proposed. The application of the presented strategies to an industrial case study demonstrates the efficiency and potential of the approach adopted.     

A2O工艺缺氧生物磷去除

A lab-scale anaerobic-anoxic-oxic (A2O) process used to treat a synthetic brewage wastewater was investigated. The objectives of the study were to identify the existence of denitrifying phosphorus removing bacteria (DPB), evaluate the contribution of DPB to biological nutrient removal and enhance the denitrifying phosphorus removal in A2O bioreactors. Sludge analysis confirmed that the average anoxic P uptake accounted for approximately 70% the total amount of P uptake, and the ratio of anoxic P uptake rate to aerobic P uptake rate was 69%. In addition, nitrate concentration in the anoxic phase and different organic substrate introduced into the anaerobic phase had significant effect on the anoxic P uptake. Compared with conventional A2O processes, good removal efficiencies of COD, phosphorus, ammonia and total nitrogen (92.3%, 95.5%, 96% and 79.5%, respectively) could be achieved in the anoxic P uptake system, and aeration energy consumption was saved 25%. By controlling the nitrate recirculation flow in the anoxic zone, anoxic P uptake could be enhanced, which solved the competition for organic substrates among poly-P organisms and denitrifiers successfully under the COD limiting conditions. Therefore, in wastewater treatment plants the control system should be applied according to the practical situation to optimize the operation.     

A2O工艺缺氧生物磷去除

A lab-scale anaerobic-anoxic-oxic （A^2O） process used to treat a synthetic brewage wastewater was investigated. The objectives of the study were to identify the existence of denitrifying phosphorus removing bacteria （DPB）, evaluate the contribution of DPB to biological nutrient removal and enhance the denitrifying phosphorus removal in A^2O bioreactors. Sludge analysis confirmed that the average anoxic P uptake accounted for approximately 70% the total amount of P uptake, and the ratio of anoxic P uptake rate to aerobic P uptake rate was 69%. In addition, nitrate concentration in the anoxic phase and different organic substrate introduced into the anaerobic phase had significant effect on the anoxic P uptake. Compared with conventional A^2O processes, good removal efficiencies of COD, phosphorus, ammonia and total nitrogen （92.3%, 95.5%, 96% and 79.5%, respectively） could be achieved in the anoxic P uptake system, and aeration energy consumption was saved 25%. By controlling the nitrate recirculation flow in the anoxic zone, anoxic P uptake could be enhanced, which solved the competition for organic substrates among poly-P organisms and denitrifiers successfully under the COD limiting conditions. Therefore, in wastewater treatment plants the control system should be applied according to the practical situation to optimize the operation.     

A reactive optimization strategy for the simultaneous planning,scheduling and control of short-period continuous reactors

The efficient and economic operation of processing systems ideally requires a simultaneous planning, scheduling and control framework. Even when the optimal simultaneous solution of this problem can result in large scale optimization problems, such a solution can represent economic advantages making feasible its computation using optimization decomposition and/or few operating scenarios. After reducing the complexity of the optimal simultaneous deterministic solution, it becomes feasible to take into account the effect of model and process uncertainties on the quality of the solution. In this work we consider those changes in product demands that take place once the process is already under continuous operation. Therefore, a reactive strategy is proposed to meet the new product demands. Based on an optimization formulation for handling the simultaneous planning, scheduling, and control problem of continuous reactors, we propose a heuristic strategy for dealing with unexpected events that may appear during operation of a plant. Such a strategy consists of the rescheduling of the products that remain to be manufactured after the given disturbance hits the process. Such reactive strategy for dealing with planning, scheduling and control problems under unforeseen events is tested using two continuous chemical reaction systems.