This paper presents the design of a high level Model Predictive Control (MPC) for efficient management and consumption of energy resources in microgrids locally controlled via Sliding Mode Control (SMC). The proposed MPC relies on a new model of the so-called Energy Management System (EMS), which takes into account the involved powers as new inputs. In the paper, the microgrid includes a Distributed Generation unit (DGu), based on a renewable energy source, and two Energy Storage units (ESus), working both in grid-connected and islanded operation mode and controlled by SMC. The MPC module generates the references of power for the energy storage systems, taking into account input and state constraints. The proposed approach is theoretically analyzed and the asymptotical stability of the controlled systems is proved. Simulation assessment confirms the efficacy of the proposal.

MPC with sliding mode control for the energy management system of microgrids

Incremona, Gian Paolo;
2017-01-01

Abstract

This paper presents the design of a high level Model Predictive Control (MPC) for efficient management and consumption of energy resources in microgrids locally controlled via Sliding Mode Control (SMC). The proposed MPC relies on a new model of the so-called Energy Management System (EMS), which takes into account the involved powers as new inputs. In the paper, the microgrid includes a Distributed Generation unit (DGu), based on a renewable energy source, and two Energy Storage units (ESus), working both in grid-connected and islanded operation mode and controlled by SMC. The MPC module generates the references of power for the energy storage systems, taking into account input and state constraints. The proposed approach is theoretically analyzed and the asymptotical stability of the controlled systems is proved. Simulation assessment confirms the efficacy of the proposal.
2017
IFAC-PapersOnLine
electric power systems; Predictive control; sliding mode control; uncertain dynamic systems; Control and Systems Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1047638
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