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Processes 2017, 5(1), 3;

Integration of RTO and MPC in the Hydrogen Network of a Petrol Refinery

Department of Systems Engineering and Automatic Control, University of Valladolid, Valladolid 47011, Spain
Department of Electromechanical Engineering, University of Burgos, Burgos 09006, Spain
Petroleos del Norte, S.A, Petronor, Muskiz 48550, Spain
Author to whom correspondence should be addressed.
Academic Editor: Dominique Bonvin
Received: 13 November 2016 / Revised: 28 December 2016 / Accepted: 29 December 2016 / Published: 7 January 2017
(This article belongs to the Special Issue Real-Time Optimization)
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This paper discusses the problems associated with the implementation of Real Time Optimization/Model Predictive Control (RTO/MPC) systems, taking as reference the hydrogen distribution network of an oil refinery involving eighteen plants. This paper addresses the main problems related to the operation of the network, combining data reconciliation and a RTO system, designed for the optimal generation and redistribution of hydrogen, with a predictive controller for the on-line implementation of the optimal policies. This paper describes the architecture of the implementation, showing how RTO and MPC can be integrated, as well as the benefits obtained in terms of improved information about the process, increased hydrocarbon load to the treatment plants and reduction of the hydrogen required for performing the operations. View Full-Text
Keywords: real-time optimization; model predictive control; petrol refineries; hydrogen networks real-time optimization; model predictive control; petrol refineries; hydrogen networks

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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de Prada, C.; Sarabia, D.; Gutierrez, G.; Gomez, E.; Marmol, S.; Sola, M.; Pascual, C.; Gonzalez, R. Integration of RTO and MPC in the Hydrogen Network of a Petrol Refinery. Processes 2017, 5, 3.

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