The manuscript proposes a multi-layer distributed intelligence architecture for energy management in electrical grids for the green transition. The work addresses the challenges posed by the massive integration of intermittent renewable sources, active prosumers, and bidirectional power flows in distribution networks, developing scalable and adaptive Energy Management Systems (EMS). The architecture spans multiple levels, integrating load forecasting, optimization, and coordination among heterogeneous actors, with a particular focus on grid resilience. Funded by the PNRR/NextGenerationEU program, the project also addresses technological accessibility for non-expert users, making participation in Renewable Energy Communities (RECs) concretely viable.

Shaping a more Resilient Grid: Multi-Layer Distributed Intelligence for the Green Transition / Lorenzo Becchi. - (2026).

Shaping a more Resilient Grid: Multi-Layer Distributed Intelligence for the Green Transition

Lorenzo Becchi
2026

Abstract

The manuscript proposes a multi-layer distributed intelligence architecture for energy management in electrical grids for the green transition. The work addresses the challenges posed by the massive integration of intermittent renewable sources, active prosumers, and bidirectional power flows in distribution networks, developing scalable and adaptive Energy Management Systems (EMS). The architecture spans multiple levels, integrating load forecasting, optimization, and coordination among heterogeneous actors, with a particular focus on grid resilience. Funded by the PNRR/NextGenerationEU program, the project also addresses technological accessibility for non-expert users, making participation in Renewable Energy Communities (RECs) concretely viable.
2026
Francesco Grasso, Gabriele Maria Lozito
ITALIA
Goal 12: Responsible consumption and production
Goal 11: Sustainable cities and communities
Goal 7: Affordable and clean energy
Goal 13: Climate action
Lorenzo Becchi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1469197
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