This paper presents a real time control strategy for dynamically balancing electric demand and supply at local level, in a scenario characterized by a HV/MV substation with the presence of renewable energy sources in the form of photovoltaic generators and an electric energy storage system. The substation is connected to the grid and is powered by an equivalent traditional power plant playing the role of the bulk power system. A Model Predictive Control based approach is proposed, by which the active power setpoints for the traditional power plant and the storage are continually updated over the time, depending on generation costs, storage’s state of charge, foreseen demand and production from renewables. The proposed approach is validated on a simulation basis, showing its effectiveness in managing fluctuations of network demand and photovoltaic generation in test and real conditions.

Electric energy storage systems integration in distribution grids / DI GIORGIO, Alessandro; Liberati, Francesco; Lanna, Andrea. - ELETTRONICO. - (2015), pp. 1279-1284. (Intervento presentato al convegno 15th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2015 tenutosi a Roma; Italy nel 2015) [10.1109/EEEIC.2015.7165354].

Electric energy storage systems integration in distribution grids

DI GIORGIO, ALESSANDRO
;
Liberati, Francesco
;
LANNA, ANDREA
2015

Abstract

This paper presents a real time control strategy for dynamically balancing electric demand and supply at local level, in a scenario characterized by a HV/MV substation with the presence of renewable energy sources in the form of photovoltaic generators and an electric energy storage system. The substation is connected to the grid and is powered by an equivalent traditional power plant playing the role of the bulk power system. A Model Predictive Control based approach is proposed, by which the active power setpoints for the traditional power plant and the storage are continually updated over the time, depending on generation costs, storage’s state of charge, foreseen demand and production from renewables. The proposed approach is validated on a simulation basis, showing its effectiveness in managing fluctuations of network demand and photovoltaic generation in test and real conditions.
2015
15th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2015
Demand Response; Energy Storage System; Model Predictive Control; Renewable Energy Sources; Smart Grid; Electrical and Electronic Engineering; Energy Engineering and Power Technology
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Electric energy storage systems integration in distribution grids / DI GIORGIO, Alessandro; Liberati, Francesco; Lanna, Andrea. - ELETTRONICO. - (2015), pp. 1279-1284. (Intervento presentato al convegno 15th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2015 tenutosi a Roma; Italy nel 2015) [10.1109/EEEIC.2015.7165354].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/856584
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