Predictive Control for Zonal Congestion Management of a Transmission Network

Duc-Trung Hoang (1) , Sorin Olaru (1) , Alessio Iovine (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]

Nowadays power transmission networks need to face congestion problems casted on the form of control problems in the presence of uncertainty. Transmission system operators (TSOs) as the French one (RTE) want to avoid power overloads on the lines by focusing on optimal management of battery systems and, if necessary, renewable production curtailments. Target of the present paper is to use a model-based optimal control approach for managing the power flow in a sub-area of a transmission network by the utilisation of storage devices and partial curtailment of the renewable power. Model Predictive Control (MPC) framework is used to include power constraints validation from the design stage. A series of hypothesis are analysed and the principles of congestions management functioning are illustrated through simulations.

Mots clés: Power transmission network; MPC; energy storage; partial power curtailment

Domaines: Automatique / Robotique; Energie électrique

Duc-Trung Hoang, Sorin Olaru, Alessio Iovine, Jean Maeght, Patrick Panciatici, et al.. Predictive Control for Zonal Congestion Management of a Transmission Network. 29th Mediterranean Conference on Control and Automation (MED 2021), Jun 2021, PUGLIA (virtual), Italy. pp.220-225, ⟨10.1109/MED51440.2021.9480270⟩. ⟨hal-03414267⟩