dc.contributor.author | Krishnamoorthy, Dinesh | |
dc.contributor.author | Foss, Bjarne Anton | |
dc.contributor.author | Skogestad, Sigurd | |
dc.date.accessioned | 2019-04-04T10:33:35Z | |
dc.date.available | 2019-04-04T10:33:35Z | |
dc.date.created | 2018-06-02T15:00:42Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Computers and Chemical Engineering. 2018, 115 34-45. | nb_NO |
dc.identifier.issn | 0098-1354 | |
dc.identifier.uri | http://hdl.handle.net/11250/2593276 | |
dc.description.abstract | Real-time optimization (RTO) is an established technology, where the process economics are optimized using rigourous steady-state models. However, a fundamental limiting factor of current static RTO implementation is the steady-state wait time. We propose a “hybrid” approach where the model adaptation is done using dynamic models and transient measurements and the optimization is performed using static models. Using an oil production network optimization as case study, we show that the Hybrid RTO can provide similar performance to dynamic optimization in terms of convergence rate to the optimal point, at computation times similar to static RTO. The paper also provides some discussions on static versus dynamic optimization problem formulations. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Elsevier | nb_NO |
dc.relation.uri | https://www.sciencedirect.com/science/article/pii/S0098135418302096 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Steady-State Real-time Optimization using Transient Measurements | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 34-45 | nb_NO |
dc.source.volume | 115 | nb_NO |
dc.source.journal | Computers and Chemical Engineering | nb_NO |
dc.identifier.doi | 10.1016/j.compchemeng.2018.03.021 | |
dc.identifier.cristin | 1588493 | |
dc.relation.project | Norges forskningsråd: 237893 | nb_NO |
dc.description.localcode | © 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 29.3.2020 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | nb_NO |
cristin.unitcode | 194,66,30,0 | |
cristin.unitcode | 194,63,25,0 | |
cristin.unitname | Institutt for kjemisk prosessteknologi | |
cristin.unitname | Institutt for teknisk kybernetikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 2 | |