This paper addresses decentralized energy trading among virtual power plants (VPPs) and proposes a peer-to-peer (P2P) mechanism, including two interactive layers: on the bottom layer, each VPP schedules/reschedules its internal distributed energy resources (DERs); and on the top layer, VPPs negotiate with each other on the trade price and quantity. The bottom-layer scheduling provides initial conditions for the top-layer negotiation, and the feedback of top-layer negotiation affects the

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... ayer rescheduling. The local scheduling/rescheduling of a VPP is formulated as a stochastic optimization problem, which takes into account the uncertainties of wind and photovoltaic power by using the scenarios-based method. In order to describe the capability of a seller VPP to generate more energy than the scheduled result, the concept of power generation potential is introduced and then considered during order initialization. The multidimensional willingness bidding strategy (MWBS) is modified and applied to the price bidding process of P2P negotiation. A 14-VPP case is studied by performing numerous computational experiments. The optimal scheduling model is effective and flexible to deal with VPPs with various configurations of DERs. The parallel price bidding with MWBS is adaptive to market situations and efficient due to its rapid convergence. It is revealed that VPPs can obtain higher profit by participating in P2P energy trading than from traditional centralized trading, and the proposed mechanism of two-layer "interactivity" can further increase VPPs' benefits compared to its "forward" counterpart. The impacts of VPP configuration and VPP number are also studied. It is demonstrated that the proposed mechanism is applicable to most cases where VPPs manage some controllable DERs.