A two-layer control scheme based on Model Predictive Control (MPC) operating at two different timescales is proposed for the energy management of a micro-grid (MG), including a battery, a gas-turbine generator, a photovoltaic (PV) generator and the input from the electrical network. The highlevel optimizer, which acts at a slow timescale and relies on a simplified model of the system, is in charge of computing the nominal operating conditions for each MG component so as to optimize an economic performance index on the basis of available predictions for the PV generation and load request. The low-level controller acts at higher frequency, adjusts the MG operation, and relies on a stochastic MPC algorithm that ensures probabilistic constraints satisfaction. Detailed models and simulations of the overall control system are presented.

Two-layer predictive control of a micro-grid including stochastic energy sources

RAIMONDI COMINESI, STEFANO;FARINA, MARCELLO;GIULIONI, LUCA;PICASSO, BRUNO;SCATTOLINI, RICCARDO
2015

Abstract

A two-layer control scheme based on Model Predictive Control (MPC) operating at two different timescales is proposed for the energy management of a micro-grid (MG), including a battery, a gas-turbine generator, a photovoltaic (PV) generator and the input from the electrical network. The highlevel optimizer, which acts at a slow timescale and relies on a simplified model of the system, is in charge of computing the nominal operating conditions for each MG component so as to optimize an economic performance index on the basis of available predictions for the PV generation and load request. The low-level controller acts at higher frequency, adjusts the MG operation, and relies on a stochastic MPC algorithm that ensures probabilistic constraints satisfaction. Detailed models and simulations of the overall control system are presented.
Proceedings of the 2015 American Control Conference
AUT
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/961204
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