LAPSE:2018.0195
Published Article
LAPSE:2018.0195
Performance Evaluation of Real Industrial RTO Systems
Maurício M. Câmara, André D. Quelhas, José Carlos Pinto
July 30, 2018
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.
Keywords
industrial RTO systems, Numerical Methods, on-line optimization, optimizing control, repeated identification and optimization, static real-time optimization (RTO)
Subject
Suggested Citation
Câmara MM, Quelhas AD, Pinto JC. Performance Evaluation of Real Industrial RTO Systems. (2018). LAPSE:2018.0195
Author Affiliations
Câmara MM: Chemical Engineering Program, COPPE, Federal University of Rio de Janeiro, Cidade Universitária, Rio de Janeiro, RJ 21945-970, Brazil
Quelhas AD: Petrobras—Petróleo Brasileiro SA, Corporate University, Rio de Janeiro, RJ 20211-230, Brazil
Pinto JC: Chemical Engineering Program, COPPE, Federal University of Rio de Janeiro, Cidade Universitária, Rio de Janeiro, RJ 21945-970, Brazil
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Journal Name
Processes
Volume
4
Issue
4
Article Number
E44
Year
2016
Publication Date
2016-11-22
Published Version
ISSN
2227-9717
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PII: pr4040044, Publication Type: Journal Article
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LAPSE:2018.0195
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doi:10.3390/pr4040044
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Jul 30, 2018
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