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CRYOGREEN - Innovative advance control of large cryogenics system to save energy and reduce carbon emission

Coordonnateur du projet : CEA-SBT
Responsable du projet à GIPSA-lab : Mazen ALAMIR

Projet réalisé grace au soutien de : ANR Thématique (Ingénierie, Procédés et Sécurité)

Date du projet : 16/12/2013

Durée : 48 mois

Large cryogenic systems (for example refrigerators like those installed at CERN to cool the Large Hadron Collider, and like those which will be installed in the coming years for ITER), extract large heat loads at low temperature. This process requires much power at room temperature and cryogenic users and manufacturers have for a long time aware of the importance of the energy efficiency of these devices.  Indeed, these large cryoplants are optimized for a certain design point, and it has been possible in the past years to reach an efficiency of 20% of the Carnot efficiency in the LHC cryoplant. However, such large cryoplants are tricky to control, and subjected to some instabilities as soon as the heat loads change significantly above a certain time scale. Moreover, when heat loads change, the optimum efficiency, reached at the design point, is no longer guaranteed, as the optimum efficiency is the result of a complex compromise between the operations of different components (cold compressors, turbines, warn compressors…). It would be of major interest for cryogenic users  to have at their disposal a tool ensuring that the electrical consumption of the cryoplant will always be minimum.  This is the objective of this project. In this project, we propose to develop a totally new control system for large refrigerators, which amazingly still use so far very simple PIDs, in spite of their complexity.
In this project, we plan to use a  “Parametrized Distributed in Time Model Predictive Control” scheme, which seems the most promising local multivariable controller, and the most suited to our constrained environment.  This new approach is a generalization of the MPC scheme, which is likely to enable an optimized control within a real time system such as a cryogenic refrigerator. The different subsystems will need to exchange information between each other, and some decisions will be needed, in order to solve possible conflicts.

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