The increasing installed capacity of distributed energy resources (DERs) allows prosumers to have a more flexible and proactive role in power system operation. At the same time, it may affect the stability of the power grid. To reduce the DERs penetration in the main grid and maximize the profit of the end-users, a new energy trading paradigm called peer-to-peer (P2P) energy trading emerges in the area of the local community microgrid. However, few of the previous works combine types of energy generation and storage equipment to the microgrid framework and propose a throughout distributed optimization solution to this scalable framework considering the impact of battery degradation cost. In this paper, a novel parallel market clearing mechanism is proposed for P2P energy trading with end-users in a highly scalable residential community microgrid. The proposed mechanism takes into account a variety of realistic factors such as household privacy, user preferences, peak shaving services, community power grid-related usage fees, point-to-point bilateral transaction weights, and battery degradation costs. To make the microgrid more scalable, each household in the community is designed with different household energy generation and storage appliances including photovoltaic panels, wind turbines, plug-in electrical vehicles, and various household batteries with different capacities. A distributed approach based on the alternating direction method of multiplier (ADMM) algorithm is presented to solve the energy pricing problem while guaranteeing the privacy of all participants. The designed comparative case studies take into consideration the types of users, grid transaction methods, the influence of peak shaving fee, the impact of energy storage equipment, and the effect of battery degradation costs. The results show a significant reduction of both the cost of each user and the total cost in the P2P energy market while considering the degradation cost of home energy management systems and plug-in electric vehicles. The case studies also present that prosumers have greater advantages than consumers in P2P energy transactions. Peak shaving service and home energy storage devices can distribute and utilize energy more efficiently. •A residential community microgrid framework with high scalability is designed.•Based on this microgrid framework, an ADMM algorithm is proposed that can be combined with the charging and discharging strategies of PEVs and HESSs.•The proposed algorithm takes into account a variety of realistic factors such as household privacy, user preferences, peak shaving services.•The designed comparative experimental case takes into consideration the types of users, grid transaction methods, the impact of energy storage equipment, and the impact of battery degradation costs.