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Communication Dans Un Congrès Année : 2022

Nonlinearity handling in MPC for Power Congestion management in sub-transmission areas

Thanh-Hung Pham
  • Fonction : Auteur
  • PersonId : 1130820
Alessio Iovine
Sorin Olaru
Jean Maeght
  • Fonction : Auteur
  • PersonId : 948644
Manuel Ruiz
  • Fonction : Auteur
  • PersonId : 1129099

Résumé

This paper proposes congestion management solutions based on Model Predictive Control (MPC) principles for transmission network zones. The contribution resides in the use of logical variables for describing the nonlinearities related to the modelling of the physical aspects in power curtailment, or some desired control goals. This allows for the representation of the nonlinear model of a sub-transmission zone with a storage device in a linear Mixed Logical Dynamical (MLD) formulation, then paving the way to the utilisation of linear mixed integer programming for the optimization problem. Moreover, part of the contribution considers supplementary temporal specifications for the energy storage device utilisation. This is modelled using additional temporal and logical variables as part of the system state and control signal. Consequently, the extended model of the power network zone is formulated as a linear MLD system and integrated to the MPC design. The proposed controllers are validated through simulations on an industrial case-study.
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Dates et versions

hal-03767398 , version 1 (01-09-2022)

Identifiants

Citer

Thanh-Hung Pham, Alessio Iovine, Sorin Olaru, Jean Maeght, Patrick Panciatici, et al.. Nonlinearity handling in MPC for Power Congestion management in sub-transmission areas. 18th IFAC Workshop on Control Applications of Optimization (CAO 2022), Jul 2022, Gif-sur-Yvette, France. ⟨10.1016/j.ifacol.2022.09.003⟩. ⟨hal-03767398⟩
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