A hierarchical approach for P2P energy trading considering community energy storage and PV-enriched system operator

The requirements to reduce dependence on fossil fuels and minimize harmful emissions necessitate using renewable energy more effectively. In this regard, a Peer-to-Peer (P2P) energy trading market in which excess power is sold to neighbors is emerging in place of the typical market where excess power is sold back to the grid. In this study, a bi-level optimal bidding strategy is proposed in which community energy storage systems (CES) and community photovoltaic (CPV) generation are considered. Moreover, individual PV and CES are taken into account for each household. While optimal scheduling of prosumers is carried out at the lower level, the local clearing price considering the profit of Energy Sharing Provider (ESP) is obtained at the upper level. Furthermore, various case studies consisting of Peer-to-Grid (P2G), P2P, and CES-supported P2P are created under different storage capacities. The devised mixed-integer linear programming (MILP) based model is tested using each case study, validating the proposed model and proving its effectiveness.