Double layer scheduling mechanism in Virtual power plant

Abstract

Aiming at the problems of operation economy and stability of power systems with a high proportion of renewable energy, this paper proposes a two-layer optimal scheduling model based on internal trading of the VPP (Virtual power plant) energy layer. Firstly, the users participating in the smart contract and the VPP within the region are regarded as different interest subjects. And the maximum opportunity benefit of users is taken as the internal optimization goal. Secondly, taking the overall benefit maximization of the VPP as the overall optimization objective,. Thus, a two-layer optimal scheduling model including energy storage is established, and the multi-objective particle swarm optimization algorithm was applied to solve the problem. The local consumption of new energy is taken as the criterion, and the price of some local consumption energy is determined by the bidding mechanism of producers and sellers. Finally, the thermal power units are used as auxiliary units. In the two scenarios with or without energy storage, comparative tests are made on the internal trading of the energy layer of VPPs. The optimal scheduling results show that the internal trading of the energy layer of VPP contributes to the local consumption of new energy and improves the overall internal income level of VPP.