The increasing penetration of Renewable Energy Resources (RES) is an opportunity to empower citizens to actively participate in energy markets through energy communities. At the local level, the Peer-to-Peer (P2P) trade and exchange of renewable energy represents a valid solution to fulfil the energy demand of the members, increase self-consumption and obtain economic benefits. However, a proper evaluation of the benefits for the community would require new considerations in designing typologies, composition, sharing and pricing mechanisms. Based on these premises, this paper explores the possible influences of different community-based P2P trading systems by examining several categories, ranging from aggregation structures, market mechanisms, sharing policies and pricing mechanisms internal to the local market. Furthermore, a flexible Mixed Integer Linear Programming model was formulated to optimise the day-ahead scheduling of community members participating in the P2P energy market. In this way, different community types, sharing policies, and pricing mechanisms were tested. Finally, the optimisation results were evaluated based on several key parameters.

Modelling and techno-economic analysis of Peer-to-Peer electricity trading systems in the context of Energy Communities / Schiera, Daniele Salvatore; De Vizia, Claudia; Zarri, Andrea; Borchiellini, Romano; Lanzini, Andrea; Patti, Edoardo; Bottaccioli, Lorenzo. - (2022), pp. 1-6. (Intervento presentato al convegno 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) tenutosi a Prague (CZ) nel 28 June 2022 - 01 July 2022) [10.1109/EEEIC/ICPSEurope54979.2022.9854537].

Modelling and techno-economic analysis of Peer-to-Peer electricity trading systems in the context of Energy Communities

Schiera, Daniele Salvatore;De Vizia, Claudia;Borchiellini, Romano;Lanzini, Andrea;Patti, Edoardo;Bottaccioli, Lorenzo
2022

Abstract

The increasing penetration of Renewable Energy Resources (RES) is an opportunity to empower citizens to actively participate in energy markets through energy communities. At the local level, the Peer-to-Peer (P2P) trade and exchange of renewable energy represents a valid solution to fulfil the energy demand of the members, increase self-consumption and obtain economic benefits. However, a proper evaluation of the benefits for the community would require new considerations in designing typologies, composition, sharing and pricing mechanisms. Based on these premises, this paper explores the possible influences of different community-based P2P trading systems by examining several categories, ranging from aggregation structures, market mechanisms, sharing policies and pricing mechanisms internal to the local market. Furthermore, a flexible Mixed Integer Linear Programming model was formulated to optimise the day-ahead scheduling of community members participating in the P2P energy market. In this way, different community types, sharing policies, and pricing mechanisms were tested. Finally, the optimisation results were evaluated based on several key parameters.
2022
978-1-6654-8537-1
File in questo prodotto:
File Dimensione Formato  
EEEIC_2022_Zarri - camera ready.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 411.15 kB
Formato Adobe PDF
411.15 kB Adobe PDF Visualizza/Apri
Modelling_and_techno-economic_analysis_of_Peer-to-Peer_electricity_trading_systems_in_the_context_of_Energy_Communities.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 462.21 kB
Formato Adobe PDF
462.21 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

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/11583/2970889