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Integrated design and control of semicontinuous distillation systems utilizing mixed integer dynamic optimization

COMPUTERS & CHEMICAL ENGINEERING 2016年 89卷 172-183页

作者： Meidanshahi, Vida Adams, Thomas A., II McMaster Univ Dept Chem Engn 1280 Main St West Hamilton ON L8S 4L8 Canada

Semicontinuous distillation systems are notoriously difficult to design and optimize because the structural parameters, operational parameters, and control system must all be determined simultaneously. In the past 15 years of research into semicontinuous systems, studies of the optimal design of these systems have all been limited in scope to small subsets of the parameters, which yields suboptimal and often unsatisfactory results. In this work, for the first time, the problem of integrated design and control of semicontinuous distillation processes is studied by using a mixed integer dynamic optimization (MIDO) problem formulation to optimize both the structural and control tuning parameters of the system. The public model library (PML) of gPROMS is used to simulate the process and the built-in optimization package of gPROMS is used to solve the MIDO via the deterministic outer approximation method. The optimization results are then compared to the heuristic particle swarm optimization (PSO) method. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Semicontinuous system Integrated design and control mixed integer dynamic optimization Outer approximation method Particle swarm optimization gPROMS

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Optimal Allocation of dynamic VAR Support Using mixed integer dynamic optimization

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IEEE TRANSACTIONS ON POWER SYSTEMS 2011年第1期26卷 305-314页

作者： Tiwari, Ashutosh Ajjarapu, Venkataramana Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

dynamic security of power systems is a major concern during contingencies, especially in present environment when there is inadequate transmission line capacity and dynamic reactive power support. This paper addresses dynamic VAR allocation to ensure acceptable transient voltage performance and short-term stability against severe contingency. To filter out severe contingency, severity indices are proposed. An algorithm based upon trajectory sensitivity analysis is used to select candidate VAR locations. The overall problem is formulated (in dynamic framework) as mixed integer dynamic optimization (MIDO). To solve MIDO problem, it is converted into mixed integer nonlinear problem (MINLP) by complete discretization using simultaneous discretization approach. The effectiveness of proposed approach is illustrated using New England 39-bus system.

关键词： Branch and bound collocation method mixed integer dynamic optimization mixed integer nonlinear problem Radau points scatter search sensitivity analysis severity index simultaneous discretization

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Control vector optimization and genetic algorithms for mixed-integer dynamic optimization in the synthesis of rice drying processes

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2011年第7期348卷 1318-1338页

作者： Wongrat, Wongphaka Younes, Abdunnaser Elkamel, Ali Douglas, Peter L. Lohi, Ali Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada

Rice drying synthesis is an essential operation that has to be done carefully and cost-effectively. Rice is harvested at high moisture content and hence must be dried within 24h for safe storage. However, improper drying can cause fissuring in the rice grain, and thus greatly reduce its market value. Multi-pass drying systems are therefore used to gradually bring moisture content to desired level. The problem of rice synthesis, considered in this study, seeks the configuration of units and their corresponding operating conditions that maximize rice quality. This problem is formulated as a mixed-integer dynamic optimization problem. The integer part of the problem reflects process alternatives while the dynamic part originates from nonlinear differential-algebraic equations describing the drying behavior of a rice grain. Clearly such a formidable problem is not easy to solve. Hence, we propose an approach that makes use of two algorithms: a genetic algorithm to search for the best configuration of units and a control vector parameterization approach that optimizes the operating conditions for each configuration. We demonstrate the effectiveness of the approach on a case study. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： Combinatorial problems Control vector parameterization Genetic algorithms mixed integer dynamic optimization Process optimization Rice drying processes

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Control vector optimization and genetic algorithms for mixed-integer dynamic optimization in the synthesis of rice drying processes

Control vector optimization and genetic algorithms for mixed...

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3rd International Conference on Modeling, Simulation, and Applied optimization (ICMSAO-09)

作者： Wongrat, Wongphaka Younes, Abdunnaser Elkamel, Ali Douglas, Peter L. Lohi, Ali Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada

关键词： Combinatorial problems Control vector parameterization Genetic algorithms mixed integer dynamic optimization Process optimization Rice drying processes

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A Rolling Horizon Framework with Social Spider Algorithm for Solving the Energy Management Problem of Utility Microgrids 19

A Rolling Horizon Framework with Social Spider Algorithm for...

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19th International Middle East Power Systems Conference (MEPCON)

作者： Elsayed, W. T. Bendary, F. M. El-bages, M. S. Hegazy, Y. G. Benha Univ Fac Engn Shoubra Cairo Egypt German Univ Cairo Cairo Egypt

ISBN: (纸本)9781538609903

This paper presents a new approach for solving the energy management problem of utility microgrids. In this approach, the rolling horizon concept is utilized to constitute a framework, in which an efficient metaheuristic technique known as the social spider algorithm is used for solving the problem. Before presenting the proposed approach, the mathematical formulation of the problem has been introduced, and the problem is formulated as a mixed-integer dynamic optimization problem. The proposed approach has been applied for solving the energy management problem of a utility microgrid with specifications obtained from the previous literature. The results obtained from using the social spider algorithm are promising.

关键词： Energy management problem (EMP) mixed integer dynamic optimization rolling horizon approach social spider algorithm (SSA) utility microgrids

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Addressing Short Term Voltage Stability Problem - Part I: Challenges and Plausible Solution Directions

Addressing Short Term Voltage Stability Problem - Part I: Ch...

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IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

作者： Tiwari, Ashutosh Ajjarapu, Venkataramana Iowa State Univ Dept ECPE Ames IA USA

ISBN: (纸本)9781509021574

This paper is the first of a two-part paper presenting issues related to short term voltage stability problem and then providing possible solution options that can ensure the security of the system. Lately power system planners are frequently encountering voltage problems in short term. Placement of dynamic VAR device in the system is one preferred option. However, there is little research done in the field of dynamic VAR allocation to ensure short term voltage stability and no industry grade tool exists. Part I explores the challenges faced while solving dynamic VAR allocation problem. The problem is complex as it requires proper selection of dynamic model;and consideration of contingencies and system dynamics in the optimization problem which leads to large problem size. Hence, this paper explores different solution methodologies;and finally proposes a novel approach to solve the optimization problem. Part II of this paper provides numerical results that demonstrate the application of the proposed approach.

关键词： Branch and Bound mixed integer dynamic optimization multiple contingency simultaneous discretization

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Addressing Short Term Voltage Stability Problem - Part II: A Case Study

Addressing Short Term Voltage Stability Problem - Part II: A...

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IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

作者： Tiwari, Ashutosh Ajjarapu, Venkataramana Iowa State Univ Dept ECPE Ames IA USA

ISBN: (纸本)9781509021574

This paper is second of a two-part paper and proposes a framework for optimal allocation of dynamic VAR device and demonstrates its application. This paper presents a complete framework to solve this complex problem. First, to filter out severe contingencies out of all credible ones severity indices are proposed. Second, a method based upon trajectory sensitivity analysis is used to determine the best candidate dynamic VAR locations. Third, the overall optimization problem is formulated as mixed integer dynamic optimization (MIDO). To reduce the complexity of optimization problem due to consideration of system dynamics and multiple contingencies, a novel methodology is proposed, where the overall problem is solved in two phases. Further, the MIDO problem is solved by the state of art solvers. The effectiveness of the proposed approach is illustrated using the 75 bus system.

关键词： Branch and Bound dynamic VAR allocation mixed integer dynamic optimization mixed integer Non Linear Programming multiple contingency

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An evolutionary approach for multi-objective dynamic optimization applied to middle vessel batch distillation

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COMPUTERS & CHEMICAL ENGINEERING 2009年第4期33卷 857-870页

作者： Leipold, Matthias Gruetzmann, Sven Fieg, Georg Tech Univ Hamburg Inst Proc & Plant Engn D-21073 Hamburg Germany

In this paper, a new approach is presented to perform multi-objective dynamic optimizations of novel batch distillation utilizing an evolutionary algorithm. The contribution is divided into two major parts. First, the development of an efficient hybrid evolutionary algorithm covering multi-objective mixed integer dynamic optimization problems is presented. The efficiency of the optimization solver is proven by several complex test problems. Second, the application of the algorithm is shown by the optimization of a middle vessel batch distillation. The challenging non-linear dynamic model, which takes the start-up phase into account, is solved in Aspen Custom Modeler. It could be proven that the proposed evolutionary algorithm can be applied to complex mathematical problems. Likewise the algorithm was found to successfully handle the optimization of middle a vessel batch distillation. The results show the feasibility of the proposed methodology and a significant increase in profitability of the process. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Modified differential evolution mixed integer dynamic optimization Pareto optimal design and operation Middle vessel batch distillation Total reflux operation

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Optimal delivery of chemotherapeutic agents in cancer

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COMPUTERS & CHEMICAL ENGINEERING 2008年第1-2期32卷 99-107页

作者： Dua, Pinky Dua, Vivek Pistikopoulos, Efstratios N. Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn London SW7 2AZ England UCL Ctr Proc Syst Engn Dept Chem Engn London WC1E 7JE England

Cancer refers to a set of diseases where normal cells of the body lose mechanisms which are responsible for controlling their growth and motility. Chemotherapy aims to kill these abnormal or cancer cells, however normal cells and healthy tissues are also adversely affected. Systematic modelling and optimization approaches can be employed to obtain effective chemotherapeutic protocol that minimizes the tumour cell population while limiting the damage to the normal cells. In this paper, two models for cancer chemotherapy are considered and the effect of the time of drug administration on the final tumour size is analyzed. The first model is cell cycle non-specific and considers all the cancer cells as belonging to one compartment whereas the second model is cell cycle specific and takes into account the effect of the drugs that act on cells at certain specific stages of the cell cycle. An optimal control problem is also formulated and solved for both the models so as to obtain the chemotherapeutic schedule which minimizes the final tumour size while taking into account the constraints on drug resistance and toxicity. For the first model a mixed integer dynamic optimization problem and for the second model a dynamic optimization problem are solved. The optimal chemotherapeutic drug administration profiles and the variation of number of cells with time are obtained and analyzed in detail. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： drug delivery systems cancer chemotherapy optimal control mixed integer dynamic optimization

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Optimal grade transition and selection of closed-loop controllers in a gas-phase olefin polymerization fluidized bed reactor

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CHEMICAL ENGINEERING SCIENCE 2003年第16期58卷 3643-3658页

作者： Chatzidoukas, C Perkins, JD Pistikopoulos, EN Kiparissides, C Aristotle Univ Thessaloniki Chem Proc Engn Res Inst Dept Chem Engn Thessaloniki 54006 Greece Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn London SW7 2BY England

To satisfy the diverse product quality specifications required by the broad range of polyolefin applications, polymerization plants are forced to operate under frequent grade transition policies. Commonly, the optimal solution to this problem is based on the minimization of a suitable objective function defined in terms of the changeover time, product quality specifications, process safety constraints and the amount of off-spec polymer, using dynamic optimization methods. However, considering the great impact that a given control structure configuration can have on the process operability and product quality optimization, the time optimal grade transition problem needs to be solved in parallel with the optimal selection of the closed-loop control pairings between the controlled and manipulated variables. In the present study, a mixed integer dynamic optimization approach is applied to a catalytic gas-phase ethylene-1-butene copolymerization fluidized bed reactor (FBR) to calculate both the "best" closed-loop control configuration and the time optimal grade transition policies. The gPROMS/gOPT computational tools for modelling and dynamic optimization, and the GAMS/CPLEX MILP solver are employed for the solution of the combined optimization problem. Simulation results are presented showing the significant quality and economic benefits that can be achieved through the application of the proposed integrated approach to the optimal grade transition problem for a gas-phase polyolefin FBR. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： gas-phase olefin polymerization optimal grade transition optimal control structure selection mixed integer dynamic optimization gPROMS((R)) simulator

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