Dynamic participation in local energy communities with peer-to-peer trading

Background: Energy communities and local electricity markets (e.g., as peer-to-peer trading) are on the rise due to increasingly decentralized generation favorable adjustment of legal framework in many European countries. Methods: This work applies a bi-level optimization model for dynamic participation trading determine optimal parameters new participants who want join an energy community, based preferences members original community environmental, economic, or mixed preference). The upper-level problem chooses by minimizing objective function that includes prosumers' cost-saving emission-saving preferences, while lower level maximizes welfare optimally allocating locally generated photovoltaic (PV) between according their willingness-to-pay. is solved transforming its corresponding Karush-Kuhn-Tucker (KKT) conditions. Results: The results demonstrate environment-oriented prosumers opt prosumer with high PV capacities installed low demand, whereas profit-oriented prefer member demand but no system capacity, presenting source income. Sensitivity analyses indicate willingness-to-pay has important influence when must decide two members. Conclusions: added value this proposed method can be seen basis selection process large number potential members. Most future will include over horizon several years.