Bidding Strategy for Virtual Power Plant Considering the Large-Scale Integrations of Electric Vehicles

Abstract

In order to alleviate the energy crisis and environmental pollution, electric vehicles (EVs) have been developed on a large-scale throughout the world in the exceptional period. On the other hand, virtual power plant (VPP), an aggregator involved in various renewable energies and diversified loads, is considered as the crucial measure to coordinate with the EVs to participate in the power market. Obviously, the equivalent model of EV in the VPP is difficult to fulfill the need for large-scale development of EVs in the future. Therefore, it is of great significance to establish the detailed charging models of EVs and explore the influences on the operation of the VPP. First, the basic structure and operation feature of VPP considering four different kinds of EVs is introduced briefly. Moreover, in order to describe the bidding processing of VPP, the three stages of power market are introduced from the trading aspects. Then, the charging characteristics of four types of EVs are analyzed in terms of charging time, charging power, and access probability. In addition, the bidding strategy models of VPP at three different stages are built and the improved Artificial Bee Colony algorithm is utilized to solve the optimal bidding strategies of the VPP. Finally, the performances of the bidding model of VPP are validated by the different scenarios that considered the multitype EVs integrations, and the influences of the different scales of EVs on the bidding strategy of VPP are also analyzed.