The model consists of two parts:

• A linear optimization model that perfectly allocates prosumers’ renewable electricity generation from PV systems supported by battery energy storage systems (BESSs) among the actors of the community, considering each actor’s willingness-to-pay for avoiding emissions and for purchasing PV electricity generated by the community. (see Perger et al. [1])
• A bi-level optimization model for dynamic participation in peer-to-peer electricity trading to determine the optimal parameters of new participants who want to join an energy community, based on the preferences of the members of the original community (e.g., environmental, economic, or mixed preference). The upper-level problem chooses optimal parameters by minimizing an objective function that includes the prosumers’ cost-saving and emission-saving preferences, while the lower-level problem maximizes community welfare by optimally allocating locally generated photovoltaic (PV) electricity between members according to their willingness-to-pay. The bi-level problem is solved by transforming the lower-level problem by its corresponding Karush-Kuhn-Tucker (KKT) conditions. (see Perger T and Auer H [2])