De BENEDETTI MASSIMILIANO MAURIZIO | Cycle: XXXIII |
Section: Systems and Control
Advisor: BASCETTA LUCA
Tutor: GARATTI SIMONE
Major Research topic:
Autonomous Agents fleets management and optimization through Artificial Intelligence and Reinforcement ; Learning techniques
Abstract:
The proliferation of Distributed Energy Resources (DERs) among the energy distribution network (DSO) has introduced several coordination and optimization problems related to the maximization of renewable energy production and grid stability.
The growing number of DERs and the electric vehicle connected to the DSO grid allow the participation of this new “agents” to the grid services (eg. Demand Response, Secondary Frequency regulation) but the lack of optimization, control and coordination strategy has introduced high risks of low performance and related IT platform scalability issues.One of the most recent research area on this filed consists in the application of classical or novel multi-agent systems approach on the DERs Aggregation. Furthermore, the lack of formalization of the standard scenario introduce an additional grade of freedom that prevent the development and the comparison of standard approach.The main goal of this research project is to investigate local and global control and coordination strategy for DERs (this may include small PV plus energy storage, electric vehicle or a mix of these resources) that participate to grid services in specific market scenarios using multi-agent systems technique.
The growing number of DERs and the electric vehicle connected to the DSO grid allow the participation of this new “agents” to the grid services (eg. Demand Response, Secondary Frequency regulation) but the lack of optimization, control and coordination strategy has introduced high risks of low performance and related IT platform scalability issues.One of the most recent research area on this filed consists in the application of classical or novel multi-agent systems approach on the DERs Aggregation. Furthermore, the lack of formalization of the standard scenario introduce an additional grade of freedom that prevent the development and the comparison of standard approach.The main goal of this research project is to investigate local and global control and coordination strategy for DERs (this may include small PV plus energy storage, electric vehicle or a mix of these resources) that participate to grid services in specific market scenarios using multi-agent systems technique.
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