Common vulnerabilities of RTO implementations in real chemical processes

Quelhas, André Domingues; Jesus, Normando José Castro de; Pinto, José Carlos

doi:10.1002/cjce.21738

Cited by 35 publications

(39 citation statements)

References 45 publications

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“…Quelhas et al [66], however, brought attention to the fact that the estimation problem must be carefully designed. Dealing with a two-step RTO applied to an industrial ethylene production plant, it is shown that the typical trajectories of the estimated heat transfer coefficients indicate that some of the model parameters are not estimable when the parameter estimation is performed independently and simultaneously with the data reconciliation procedure, which might be due to correlation with other parameters and process data or because they do not affect the objection function significantly.…”

Section: Solution Strategiesmentioning

confidence: 99%

“…Nevertheless, they should be analyzed during the design of a DR application trying to answer whether the optimization problem is being satisfactory solved. Although DR generates benefits, it can have strong negative effects when some hypothesis is violated or the procedure does not find a feasible solution, and using reconciled data could yield worse results than using the measurements directly [65][66][67].…”

Section: Introductionmentioning

confidence: 99%

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Numerical Aspects of Data Reconciliation in Industrial Applications

et al. 2017

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Abstract:Data reconciliation is a model-based technique that reduces measurement errors by making use of redundancies in process data. It is largely applied in modern process industries, being commercially available in software tools. Based on industrial applications reported in the literature, we have identified and tested different configuration settings providing a numerical assessment on the performance of several important aspects involved in the solution of nonlinear steady-state data reconciliation that are generally overlooked. The discussed items are comprised of problem formulation, regarding the presence of estimated parameters in the objective function; solution approach when applying nonlinear programming solvers; methods for estimating objective function gradients; initial guess; and optimization algorithm. The study is based on simulations of a rigorous and validated model of a real offshore oil production system. The assessment includes evaluations of solution robustness, constraint violation at convergence, and computational cost. In addition, we propose the use of a global test to detect inconsistencies in the formulation and in the solution of the problem. Results show that different settings have a great impact on the performance of reconciliation procedures, often leading to local solutions. The question of how to satisfactorily solve the data reconciliation problem is discussed so as to obtain improved estimates.

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Section: Solution Strategiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical Aspects of Data Reconciliation in Industrial Applications

et al. 2017

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“…• The success rate of modern convex solvers is much higher than that of SQP solvers and can virtually reach 100%, 32 which is a very nice feature for industrial RTO applications 8 .…”

Section: Advantages Of Convex Modelsmentioning

confidence: 99%

“…There are still a significant number of difficulties that limit the wide application of RTO in industry 8,9 . The main limitation is without any doubt the inability of the RTO schemes to find the plant optimum in the presence of structural plant-model mismatch 5,10 .…”

Section: Introductionmentioning

confidence: 99%

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

François

Bonvin

2013

Ind. Eng. Chem. Res.

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Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements are used to iteratively adapt the model via input-affine additive terms. The modifier terms correspond to the deviations between the measured and predicted constraints on the one hand, and the measured and predicted cost and constraint gradients on the other. If the iterative scheme converges, these modifier terms guarantee that the converged point satisfies the KKT conditions for the plant. Furthermore, if upon convergence the plant model predicts the correct curvature of the cost function, convergence to a (local) plant optimum is guaranteed.The main advantage of modifier adaptation lies in the fact that these properties do not rely on specific assumptions regarding the nature of the uncertainty. In other words, in addition to rejecting the effect of parametric uncertainty like most RTO methods, modifier adaptation can also handle process disturbances and structural plant-model mismatch. This paper shows that the use of a convex model approximation in the modifier-adaptation framework implicitly enforces model adequacy. The approach is illustrated through both a simple numerical example and a simulated continuous stirred-tank reactor.

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“…In fact, plant-model mismatch is not the only vulnerability of RTO systems, whose performance can also be jeopardized by incomplete and corrupted process information, absence of knowledge regarding measurement errors and performance issues related to numerical optimization techniques [31]. In addition, the use of continuous system diagnostic tools is not common, neither in the literature, nor in commercial RTO systems.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Real Industrial RTO Systems

2016

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Abstract:The proper design of RTO systems' structure and critical diagnosis tools is neglected in commercial RTO software and poorly discussed in the literature. In a previous article, Quelhas et al. (Can J Chem Eng., 2013, 91, 652-668) have reviewed the concepts behind the two-step RTO approach and discussed the vulnerabilities of intuitive, experience-based RTO design choices. This work evaluates and analyzes the performance of industrial RTO implementations in the face of real settings regarding the choice of steady-state detection methods and parameters, the choice of adjustable model parameters and selected variables in the model adaptation problem, the convergence determination of optimization techniques, among other aspects, in the presence of real noisy data. Results clearly show the importance of a robust and careful consideration of all aspects of a two-step RTO structure, as well as of the performance evaluation, in order to have a real and undoubted improvement of process operation.

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Common vulnerabilities of RTO implementations in real chemical processes

Cited by 35 publications

References 45 publications

Numerical Aspects of Data Reconciliation in Industrial Applications

Numerical Aspects of Data Reconciliation in Industrial Applications

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

Performance Evaluation of Real Industrial RTO Systems

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