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Gestion des congestions et prise de décision dans les réseaux électriques maillés en utilisant des batteries électriques

Abstract : Power generation has been undergoing a radical change due to the expansion of renewable energies. The part of the generation which can be characterised as intermittent and scarce is increasing in importance and is creating new overload constraints on electrical grids called congestions. In this context, batteries are gaining a growing attention for their potential in congestion management. The thesis work contained in this manuscript deals with the conception of new algorithms relying on batteries to solve congestions on meshed electrical grid. The presented control strategy mingle batteries actions and renewable curtailment. The control is based on two levels. The upper level relates to planification and the lower level is dedicated to real-time congestion management. The lower level is developped using Model Predictive Control and provides a framework to take into account delays on control actions. The upper level covers the batteries trajectories planning, supports the lower level and defines batteries capacity used for real-time congestion management and the residual capacities of these batteries. This level can thus be used to define a multi-service framework for batteries. The residual capacities can be offered to other actors or services of the electrical market.The developped algorithms are implemented on a project conducted by the french Transmission System Operator (RTE) : the RINGO Project. This project is a demonstrator program whose aim is to validate large capacity storage as a solution to congestions.
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Submitted on : Tuesday, May 4, 2021 - 1:52:07 PM
Last modification on : Thursday, May 6, 2021 - 3:33:25 AM
Long-term archiving on: : Thursday, August 5, 2021 - 7:36:01 PM


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  • HAL Id : tel-03216850, version 1


Clémentine Straub. Gestion des congestions et prise de décision dans les réseaux électriques maillés en utilisant des batteries électriques. Energie électrique. Université Paris-Saclay, 2021. Français. ⟨NNT : 2021UPASG013⟩. ⟨tel-03216850⟩



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