This paper proposes a novel fully distributed flexible framework for the optimal control and energy management of energy community considering different types of distributed sources such as photovoltaic panels, wind turbines, fuel cell, micro-turbine and battery storage. The proposed framework makes use of the alternating direction method of multipliers (ADMM) to provide a highly secured peer-2-peer (P2P) energy trading among the neighboring agents. The total operation cost of the energy community consisting of the individual cost of agents would be optimized using a new modified bacterial foraging algorithm (MBFA). MBFA is equipped by a new powerful local search formulation which can help to optimize the agents' costs, effectively. Through a recursive phenomenon, the optimal power scheduling of distributed energy resources (DERs) and storage units is determined. The proposed P2P framework within energy community is examined using the IEEE microgrid test system. The results advocate the high efficiency and optimality of the proposed model.