Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization.

The electric vehicle to grid (V2G) interaction technology can improve the utilization of renewable energy and stabilize its grid connection. At the same time, renewable energy can be used for a microgrid nearby, or incorporated into a large grid, to effectively address the volatility of renewable energy sources. Motivated by the increasing number of electric vehicles (EVs) and the randomness of renewable energy output, this paper proposes an effective strategy to improve the security and economy of the microgrid system. The uncertainty of wind power and EV's state of charge (SOC) is modeled as uncertainty prediction sets. And considering the worst-case scenario, this proposed strategy can increase the absorption ratio of renewable energy while orderly guiding the charging and discharging of EVs in peak-load reduction and valley filling and thus, lower operating costs under various practical constraints. To solve the problem of over-conservatism of the robust optimization, this paper introduces a dispatch interval coefficient to adjust the degree of conservatism, while improving the economy of microgrids system. The robustness and feasibility of the proposed dispatch strategy are demonstrated by numerical case studies. • Electric vehicle is introduced as both load and source (V2G mode) to help the consumption of wind power. • Operation stability and economic performance of microgrid is improved with the adjustable robust optimization (RO). • The robustness and economy of the system has been quantified. • Sensitivity analysis of uncertain variables to system total cost is carried out. [ABSTRACT FROM AUTHOR]