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

Abstract

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.