Online Data Reconciliation with Poor Redundancy Systems
The paper deals with the integrated solution of different model-based optimization levels to face the problem of inferring and reconciling online plant measurements practically, under the condition of poor measure redundancy, because of a lack of instrumentation installed in the field. The novelty o...
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| Published in | Industrial & engineering chemistry research Vol. 50; no. 24; pp. 14105 - 14114 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Washington, DC
American Chemical Society
21.12.2011
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0888-5885 1520-5045 |
| DOI | 10.1021/ie202259b |
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| Abstract | The paper deals with the integrated solution of different model-based optimization levels to face the problem of inferring and reconciling online plant measurements practically, under the condition of poor measure redundancy, because of a lack of instrumentation installed in the field. The novelty of the proposed computer-aided process engineering (CAPE) solution is in the simultaneous integration of different optimization levels: (i) the data reconciliation based on a detailed process simulation; (ii) the introduction and estimation of certain adaptive parameters, to match the current process conditions as well as to confer a certain generality on it; and (iii) the use of a set of efficient optimizers to improve plant operations. The online feasibility of the proposed CAPE solution is validated on a large-scale sulfur recovery unit (SRU) of an oil refinery. |
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| AbstractList | The paper deals with the integrated solution of different model-based optimization levels to face the problem of inferring and reconciling online plant measurements practically, under the condition of poor measure redundancy, because of a lack of instrumentation installed in the field. The novelty of the proposed computer-aided process engineering (CAPE) solution is in the simultaneous integration of different optimization levels: (i) the data reconciliation based on a detailed process simulation; (ii) the introduction and estimation of certain adaptive parameters, to match the current process conditions as well as to confer a certain generality on it; and (iii) the use of a set of efficient optimizers to improve plant operations. The online feasibility of the proposed CAPE solution is validated on a large-scale sulfur recovery unit (SRU) of an oil refinery. |
| Author | Grottoli, Maria Grazia Manenti, Flavio Pierucci, Sauro |
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| Cites_doi | 10.1002/(SICI)1097-4601(1996)28:10<773::AID-KIN8>3.0.CO;2-K 10.1016/j.compchemeng.2010.11.004 10.1021/ie070355s 10.1016/0098-1354(94)00107-Y 10.1002/aic.690320410 10.1016/j.compchemeng.2006.11.007 10.1021/ie901749t 10.1002/9781118186435 10.1080/01621459.1984.10477105 10.1016/j.compchemeng.2007.04.003 10.1021/ie970852g 10.1016/j.compchemeng.2011.04.009 10.1002/aic.690430414 10.1109/37.845037 10.1016/j.ces.2008.10.062 10.1016/S1570-7946(09)70152-X 10.1016/0098-1354(92)80064-G 10.1002/aic.690290602 10.1016/S0010-2180(01)00325-X 10.1016/j.compchemeng.2004.07.016 10.1016/S0959-1524(01)00021-X 10.1002/aic.690280615 10.1016/j.compchemeng.2006.08.009 10.1016/S0098-1354(98)00248-8 10.1016/S0098-1354(98)00217-8 10.1002/0471725382 10.1016/S1570-7946(10)28057-4 10.1016/0098-1354(85)85016-X 10.1016/S0098-1354(98)00301-9 |
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| Title | Online Data Reconciliation with Poor Redundancy Systems |
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