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Integrated Scheduling and dynamic optimization of Sequential Batch Processes with Online Implementation

AICHE JOURNAL 2013年第7期59卷 2379-2406页

作者： Chu, Yunfei You, Fengqi Northwestern Univ Dept Chem & Biol Engn Evanston IL 60208 USA

An efficient decomposition method to solve the integrated problem of scheduling and dynamic optimization for sequential batch processes is proposed. The integrated problem is formulated as a mixed-integer dynamic optimization problem or a large-scale mixed-integer nonlinear programming (MINLP) problem by discretizing the dynamic models. To reduce the computational complexity, we first decompose all dynamic models from the integrated problem, which is then approximated by a scheduling problem based on the flexible recipe. The recipe candidates are expressed by Pareto frontiers, which are determined offline by using multiobjective dynamic optimization to minimize the processing cost and processing time. The operational recipe is then optimized simultaneously with the scheduling decisions online. Because the dynamic models are encapsulated by the Pareto frontiers, the online problem is a mixed-integer programming problem which is much more computationally efficient than the original MINLP problem, and allows the online implementation to deal with uncertainties. (c) 2013 American Institute of Chemical Engineers AIChE J, 59: 2379-2406, 2013

关键词： integrated scheduling and dynamic optimization decomposition mixed-integer dynamic optimization mixed-integer nonlinear programming multiobjective dynamic optimization

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Simultaneous mixed-integer dynamic scheduling of processes and their energy systems

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AICHE JOURNAL 2022年第8期68卷 e17741-e17741页

作者： Baader, Florian Joseph Bardow, Andre Dahmen, Manuel Forschungszentrum Julich Inst Energy & Climate Res Energy Syst Engn IEK 10 D-52425 Julich Germany Rhein Westfal TH Aachen Fac Mech Engn Aachen Germany Swiss Fed Inst Technol Energy & Proc Syst Engn Zurich Switzerland Rhein Westfal TH Aachen Inst Tech Thermodynam Aachen Germany

Increasingly volatile electricity prices make simultaneous scheduling optimization desirable for production processes and their energy systems. Simultaneous scheduling needs to account for both process dynamics and binary on/off-decisions in the energy system leading to challenging mixed-integer dynamic optimization problems. We propose an efficient scheduling formulation consisting of three parts: a linear scale-bridging model for the closed-loop process output dynamics, a data-driven model for the process energy demand, and a mixed-integer linear model for the energy system. Process dynamics is discretized by collocation yielding a mixed-integer linear programming (MILP) formulation. We apply the scheduling method to three case studies: a multiproduct reactor, a single-product reactor, and a single-product distillation column, demonstrating the applicability to multiple input multiple output processes. For the first two case studies, we can compare our approach to nonlinear optimization and capture 82% and 95% of the improvement. The MILP formulation achieves optimization runtimes sufficiently fast for real-time scheduling.

关键词： demand response integration of scheduling and control mixed-integer dynamic optimization mixed-integer linear programming simultaneous scheduling

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Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes

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COMPUTERS & CHEMICAL ENGINEERING 2012年 37卷 125-135页

作者： Brunet, Robert Guillen-Gosalbez, Gonzalo Ricardo Perez-Correa, J. Antonio Caballero, Jose Jimenez, Laureano Univ Rovira & Virgili Dept Engn Quim Escola Tecn Super Engn Quim Tarragona 43007 Spain Pontificia Univ Catolica Chile Dept Ingn Quim & Bioproc Santiago Chile Univ Alicante Dept Ingn Quim E-03080 Alicante Spain

In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer (R) with an external NLP solver implemented in Matlab (R). The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Hybrid simulation-optimization mixed-integer dynamic optimization Biotechnological processes L-Lysine

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Decentralized Control System Design under Uncertainty Using mixed-integer optimization

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CHEMICAL ENGINEERING & TECHNOLOGY 2012年第2期35卷 261-271页

作者： Paramasivan, Ganesh Kienle, Achim Max Planck Inst Dynam Komplexer Tech Syst D-39106 Magdeburg Germany Univ Magdeburg Lehrstuhl Automatisierungstech Modellbildung D-39106 Magdeburg Germany

Decentralized control system design comprises the selection of a suitable control structure and controller parameters. In this contribution, the optimal control structure and the optimal controller parameters are determined simultaneously using mixed-integer dynamic optimization (MIDO) under uncertainty, to account for nonlinear process dynamics and various disturbance scenarios. Application of the sigma point method is proposed in order to approximate the expectation and the variance of a chosen performance index with a minimum number of points to solve the MIDO problem under uncertainty. The proposed methodology is demonstrated with a benchmark problem of an inferential control for a reactive distillation column. The results are compared with established heuristic design methods and with previous deterministic approaches.

关键词： Control structure selection Decentralized control system mixed-integer dynamic optimization Process control

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Integrated control and process design during optimal polymer grade transition operations

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COMPUTERS & CHEMICAL ENGINEERING 2008年第11期32卷 2823-2837页

作者： Flores-Tlacuahuac, Antonio Biegler, Lorenz T. Univ Iberoamer Dept Ingn & Ciencias Quim Mexico City 01210 DF Mexico Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

In this work we address the simultaneous process control and design problem of polymerization reactors during dynamic grade transition operation. The problem is cast as a mixed-integer dynamic optimization (MIDO) formulation and, by using the full discretization approach for solving dynamic optimization problems [Kameswaran, S., & Biegler, L. T (2006). Simultaneous dynamic optimization strategies: Recent advances and challenges. Computers & Chemical Engineering, 30 (10-12). 1560-1575], is transformed into a mixed-integer Nonlinear Program (MINLP). The resulting MINLP is solved using a full space nonconvex optimization formulation [Flores-Tlacuahuac. A., & Biegler, L. T. (2007). Simultaneous mixed-integer dynamic optimization for integrated design and control. Computers & Chemical Engineering, 31, 588-600]. The control and design formulation has been applied to two polymerization reactors featuring highly nonlinear behavior. In both cases, the proposed MIDO formulation was capable of finding optimal solutions. This amounts to finding optimal steady states. reactor designs. as well as open-loop and closed-loop dynamic optimal trajectories, control structures and controller parameters by specifying either the polymer molecular weight distribution or monomer conversion. Because CPU solution time tends to increase with system complexity, some strategies for lowering CPU time are discussed. (c) 2008 Elsevier Ltd. All rights reserved.

关键词： Scheduling Control optimization Polymerization reactors Grade transition mixed-integer dynamic optimization

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Continuous reformulations of discrete-continuous optimization problems

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COMPUTERS & CHEMICAL ENGINEERING 2004年第10期28卷 1951-1966页

作者： Stein, O Oldenburg, J Marquardt, W Univ Aachen Rhein Westfal TH Aachen Lehrstuhl Prozesstech D-52056 Aachen Germany Univ Aachen Rhein Westfal TH Aachen Lehrstuhl Math C D-52056 Aachen Germany

This paper treats the solution of nonlinear optimization problems involving discrete decision variables, also known as generalized disjunctive programming (GDP) or mixed-integer nonlinear programming (MINLP) problems, that arise in process engineering. The key idea is to eliminate the discrete decision variables by adding a set of continuous variables and constraints that represent the discrete decision space of the optimization problem. With such a reformulation, we are able to apply solution algorithms for purely continuous nonlinear optimization problems to efficiently calculate local minima of GDP or MINLP problems. In this contribution, we propose different alternatives to reformulate GDP/MINLP problems as continuous optimization problems. We furthermore investigate theoretical properties of the different reformulations with regard to their numerical solution. The proposed formulations are illustrated and analyzed on the basis of optimization problems dealing with process engineering applications involving stationary as well as dynamic process models. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： discrete-continuous nonlinear optimization disjunctive programming complementarity process engineering mixed-integer dynamic optimization

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Moving horizon approach of integrating scheduling and control for sequential batch processes

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AICHE JOURNAL 2014年第5期60卷 1654-1671页

作者： Chu, Yunfei You, Fengqi Northwestern Univ Dept Chem & Biol Engn Evanston IL 60208 USA

Online integration of scheduling and control is crucial to cope with process uncertainties. We propose a new online integrated method for sequential batch processes, where the integrated problem is solved to determine controller references rather than process inputs. Under a two-level feedback loop structure, the integrated problem is solved in a frequency lower than that of the control loops. To achieve the goal of computational efficiency and rescheduling stability, a moving horizon approach is developed. A reduced integrated problem in a resolving horizon is formulated, which can be solved efficiently online. Solving the reduced problem only changes a small part of the initial solution, guaranteeing rescheduling stability. The integrated method is demonstrated in a simulated case study. Under uncertainties of the control system disruption and the processing unit breakdown, the integrated method prevents a large loss in the production profit compared with the simple shifted rescheduling solution. (c) 2014 American Institute of Chemical Engineers AIChE J, 60: 1654-1671, 2014

关键词： scheduling advanced manufacturing mixed-integer dynamic optimization model predictive control batch processes

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Simultaneous Design and Control of a Ternary Reactive Distillation Column with Inert Material

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CHEMICAL ENGINEERING & TECHNOLOGY 2018年第11期41卷 2233-2240页

作者： Vasudevan, Aneesh Narayanasamy, Selvaraju Paramasivan, Ganesh Natl Inst Technol Calicut Dept Chem Engn NIT Campus PO Kozhikode 673601 Kerala India Indian Inst Technol Guwahati Dept Biosci & Bioengn Gauhati 781039 Assam India ISRO Prop Complex Mahendragiri 627133 Tamil Nadu India

Process integration means significant challenges in operating a chemical process dynamically due to its complexity. One example is the ternary reactive distillation with inert material. Based on the heuristic approach, chemical process design and process control are performed independently one after another. This may lead to infeasible solutions either in process design and control or in both. The application of simultaneous design and control, formulated as mixed-integer dynamic optimization (MIDO) problems, increased rapidly in the last decade. Simultaneous process design and control, including control structure selection and control parameters, is devised for the challenging benchmark problem of a ternary reactive distillation with inert material. The improved process design and control is obtained by solving the MIDO problem.

关键词： Inert materials mixed-integer dynamic optimization Process integration Ternary reactive distillation columns

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Optimal design and control of a reactive distillation system

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ENGINEERING optimization 2005年第7期37卷 733-753页

作者： Panjwani, P Schenk, M Georgiadis, MC Pistikopoulos, EN Univ London Imperial Coll Sci & Technol Ctr Proc Syst Engn Dept Chem Engn London England

This article presents the design and control of a reactive distillation system utilizing recent advances in mixed integer dynamic optimization. A high fidelity dynamic model is used to predict the behavior of the process under time-varying disturbances. Design and control decisions, involving both discrete and continuous variables, are simultaneously optimized leading to a more economically attractive and better controlled system than that obtained by following a sequential optimization approach. It is shown that the resulting design and control scheme can guarantee feasible operation under bounded uncertainty at a minimum total average cost, representing similar to 17% savings over the original design.

关键词： mixed-integer dynamic optimization reactive distillation process design and control

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Simultaneous design and control optimisation under uncertainty

Simultaneous design and control optimisation under uncertain...

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7th International Symposium on Process Systems Engineering

作者： Bansal, V Perkins, JD Pistikopoulos, EN Ross, R van Schijndel, JMG Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn London SW7 2BY England Proc Syst Enterprise Ltd London W6 9DA England Shell Int Chem BV NL-1030 BN Amsterdam Netherlands

This paper demonstrates how the design and control of processes described by large-scale, complex, mixed-integer dynamic models can be simultaneously optimised in the face of time-varying disturbances and parametric uncertainties. A rigorously modelled distillation example is used for this purpose, where the number of trays, feed location, column diameter, surface areas of the heat exchangers and tuning parameters of the controllers are selected in order to minimise the total annualised cost of the system, while satisfying a large number of feasibility constraints. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： process design process control uncertainty mixed-integer dynamic optimization

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