A Distributed Consensus Control Under Disturbances for Wind Farm Power Maximization

Nicolo Gionfra 1 Guillaume Sandou 1, 2 Houria Siguerdidjane 1 Damien Faille 3 Philippe Loevenbruck 4
1 L2S - Laboratoire des signaux et systèmes
2 DISCO - Dynamical Interconnected Systems in COmplex Environments
L2S - Laboratoire des signaux et systèmes, Inria Saclay - Ile de France, SUPELEC, CNRS - Centre National de la Recherche Scientifique : UMR8506
3 EDF R&D STEP - Simulation et Traitement de l'information pour l'Exploitation des systèmes de Production
4 EDF - EDF
Abstract : — In this paper we address the problem of power sharing among the wind turbines (WTs) belonging to a wind farm. The objective is to maximize the power extraction under the wake effect, and in the presence of wind disturbances. Because of the latter, WTs may fail in respecting the optimal power sharing gains. These are restored by employing a consensus control among the WTs. In particular, under the assumption of discrete-time communication among the WTs, we propose a distributed PID-like consensus approach that enhances the rejection of the wind disturbances by providing the power references to the local WT controllers. The latter are designed by employing a novel feedback linearization control that, acting simultaneously on the WT rotor speed and the pitch angle, guarantees the tracking of general deloaded power references. The obtained results are validated on a 6-WT wind farm example.
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Communication dans un congrès
56th IEEE Conference on Decision and Control (CDC 2017), Dec 2017, Melbourne, Australia. 2017, Proceedings of the 56th IEEE Conference on Decision and Control. 〈10.1109/cdc.2017.8263944 〉
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Soumis le : mardi 19 décembre 2017 - 16:14:47
Dernière modification le : jeudi 26 avril 2018 - 17:11:36

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CENTRALESUPELEC | SUP_LSS | SUP_SYSTEMES | TDS-MACS | L2S | UNIV-PARIS-SACLAY | INRIA | INRIA2017

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Nicolo Gionfra, Guillaume Sandou, Houria Siguerdidjane, Damien Faille, Philippe Loevenbruck. A Distributed Consensus Control Under Disturbances for Wind Farm Power Maximization. 56th IEEE Conference on Decision and Control (CDC 2017), Dec 2017, Melbourne, Australia. 2017, Proceedings of the 56th IEEE Conference on Decision and Control. 〈10.1109/cdc.2017.8263944 〉. 〈hal-01667884〉

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