Efficient energy management for an elevator system under a constrained optimization framework

This paper addresses the challenging energy management problem of a DC-microgrid elevator system using a coherent combination between port-Hamiltonian approach for physical system modeling, differential flatness for profiles generation and predictive control for taking into account constraints, optimization costs and reference profiles. The microgrid connected to a three-phase utility grid includes a mechanical part, a Salient Permanent Magnet Synchronous Machine (SPMSM), an energy storage unit, a super-capacitor, a solar panel (PV) generation unit as well as the corresponding converters to DC-links. We will concentrate here on the microgrid's mechanical part connected to the synchronous machine. More precisely, a constrained predictive control combined with differential flatness is employed for efficiently manage the dissipative energy. First, optimal profiles of both the stator currents and rotor speed are provided using flat trajectory generation. Next, a constrained Model Predictive Control (MPC) optimization problem is formulated in order to satisfy the a priori given profiles. Comparison and simulation results validate the benefits of the proposed approach.