Advanced management of network overload in areas with Renewable Energies Sources

Thanh-Hung Pham (1) , Alessio Iovine (1) , Sorin Olaru (1) , Jean Maeght (2) , Patrick Panciatici (2) , Manuel Ruiz (2)

1 L2S - Laboratoire des signaux et systèmes
2 RTE - Réseau de Transport d'Electricité [Paris]

This paper proposes an overload management method based on Model Predictive Control principles for electrical power network zones with Renewable Energies Sources (RESs). The danger of sudden line disconnection represents a critical aspect of the operation and the overload can only be tolerated within drastic duration and repetitiveness constraints. The first contribution resides in the employment of temporal and logical variables as a part of the system states to formulate supplementary bounds for the line power flow limits during the overload tolerance. For the second contribution, the control problem is independent from the exogenous overload trigger thanks to the feedback of these variables as the controller parameters. Lastly, according to considered assumptions, a sequence of predicted maximal supplementary bounds is used for the control design. With respect to classical additional temporal variables, these bounds simplify the control design problem. The proposed method is validated through simulations on an industrial study case.

Mots clés: Power transmission network; constrained model predictive control; mixed logical dynamical modeling

Domaines: Optimisation et contrôle [math.OC]; Automatique / Robotique; Energie électrique

Thanh-Hung Pham, Alessio Iovine, Sorin Olaru, Jean Maeght, Patrick Panciatici, et al.. Advanced management of network overload in areas with Renewable Energies Sources. CPES 2022, Jun 2022, Moscow, Russia. ⟨10.1016/j.ifacol.2022.07.015⟩. ⟨hal-03616849⟩