Collaborative and optimal operation of V2G for electric vehicles to promote renewable energy consumption

Promoting renewable energy sources such as wind power (WP) and photovoltaic power (PP) on the grid and the development of the electric vehicle (EV) industry are ways to achieve global goal of carbon neutrality and carbon peaking. For this purpose, we propose an optimal operating strategy for a microgrid with electric vehicle. We incorporate the condition of EV scheduling capability in conjunction with time-of-use price (TOU) to control the charging and discharging behavior of EV to utilize controllable loads in the microgrid, and finally to collaboratively dispatch energy storage system (ESS) to decrease the negative impact of renewable energy. In this way, the charging and discharging costs of EV (CDCE) and the equivalent load fluctuations between the microgrid and the main power grid are reduced. A two-layer function is established for this reason. The goal of the inner layer is to minimize the charging and discharging cost for the user, and the goal of the outer layer is to minimize the difference in power fluctuations on the tie line between the microgrid and the main power grid (TLBMM). A multi-objective particle swarm algorithm was adopted to address the function. The findings prove that it can obtain the best EV charging and discharging scheduling scheme and ESS power scheme. It can effectively, decrease the EV charging and discharging cost, as well as smoothing the power curve of the TLBMM and promoting the renewable energy consumption.