In this paper we consider the optimal operation of an energy community receiving incentives for energy virtually shared among the community members. A similar incentive scheme for renewable energy communities is adopted in Italy since 2020. The operational problem is formulated as the maxi-mization of the profit of the community over a given time horizon. The profit includes the incentive for the virtual self-consumption. The optimization exploits all available sources of flexibility, such as controllable loads and generators, and battery energy storage systems. Compared to previous work of the authors, the mixed-integer formulation proposed in this paper requires a smaller number of continuous variables. Still, the number of binary variables may be prohibitive when the size of the community grows. For this reason, an equivalent formulation in the form of convex maximization is derived, involving only continuous variables. We show examples where the latter problem can be solved in reasonable time, while the solution process of the mixed integer problem gets stuck. Moreover, a simple strategy to fairly redistribute the community benefits among its members is discussed.

Stentati, M., Paoletti, S., Vicino, A. (2023). Optimization and Redistribution Strategies for Italian Renewable Energy Communities. In IEEE EUROCON 2023 - 20th International Conference on Smart Technologies (pp.263-268). IEEE [10.1109/eurocon56442.2023.10199011].

Optimization and Redistribution Strategies for Italian Renewable Energy Communities

Paoletti, Simone
;
2023-01-01

Abstract

In this paper we consider the optimal operation of an energy community receiving incentives for energy virtually shared among the community members. A similar incentive scheme for renewable energy communities is adopted in Italy since 2020. The operational problem is formulated as the maxi-mization of the profit of the community over a given time horizon. The profit includes the incentive for the virtual self-consumption. The optimization exploits all available sources of flexibility, such as controllable loads and generators, and battery energy storage systems. Compared to previous work of the authors, the mixed-integer formulation proposed in this paper requires a smaller number of continuous variables. Still, the number of binary variables may be prohibitive when the size of the community grows. For this reason, an equivalent formulation in the form of convex maximization is derived, involving only continuous variables. We show examples where the latter problem can be solved in reasonable time, while the solution process of the mixed integer problem gets stuck. Moreover, a simple strategy to fairly redistribute the community benefits among its members is discussed.
2023
978-1-6654-6397-3
Stentati, M., Paoletti, S., Vicino, A. (2023). Optimization and Redistribution Strategies for Italian Renewable Energy Communities. In IEEE EUROCON 2023 - 20th International Conference on Smart Technologies (pp.263-268). IEEE [10.1109/eurocon56442.2023.10199011].
File in questo prodotto:
File Dimensione Formato  
Optimization_and_Redistribution_Strategies_for_Italian_Renewable_Energy_Communities.pdf

non disponibili

Tipologia: PDF editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 597.9 kB
Formato Adobe PDF
597.9 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1277490