In this paper we address the optimal operation of an energy community, which receives an incentive for the self-consumption realized at the community level in each time period. This incentive scheme mimics the one adopted for renewable energy communities in Italy since 2020. The operational problem is formulated as the maximization of the social welfare of the community over a given time horizon. The social welfare includes the incentive. Each entity of the community can encompass loads, generators, and battery energy storage systems. The optimization problem computes the battery charging/discharging policies, and the set points of flexible loads and controllable generators. The resulting problem formulation is non-convex, due to the presence of complementarity constraints. This issue is tackled by deriving an equivalent mixed integer linear programming formulation. A toy example and an application with real consumption, generation, and price data, are reported to illustrate the proposed approach.
Stentati, M., Paoletti, S., Vicino, A. (2022). Optimization of energy communities in the Italian incentive system. In 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) (pp.1-5). New York : IEEE [10.1109/isgt-europe54678.2022.9960513].
Optimization of energy communities in the Italian incentive system
Paoletti, Simone;
2022-01-01
Abstract
In this paper we address the optimal operation of an energy community, which receives an incentive for the self-consumption realized at the community level in each time period. This incentive scheme mimics the one adopted for renewable energy communities in Italy since 2020. The operational problem is formulated as the maximization of the social welfare of the community over a given time horizon. The social welfare includes the incentive. Each entity of the community can encompass loads, generators, and battery energy storage systems. The optimization problem computes the battery charging/discharging policies, and the set points of flexible loads and controllable generators. The resulting problem formulation is non-convex, due to the presence of complementarity constraints. This issue is tackled by deriving an equivalent mixed integer linear programming formulation. A toy example and an application with real consumption, generation, and price data, are reported to illustrate the proposed approach.File | Dimensione | Formato | |
---|---|---|---|
Optimization_of_energy_communities_in_the_Italian_incentive_system.pdf
non disponibili
Tipologia:
PDF editoriale
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
916.3 kB
Formato
Adobe PDF
|
916.3 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.
https://hdl.handle.net/11365/1277491