Optimal scheduling of electric vehicles charging in battery swapping station considering wind- photovoltaic accommodation

The disorderly charging of large-scale Electric Vehicles increases the peak-to-valley difference of the grid and new energy absorption is facing difficulties. Considering these problems and difficulties, an aggregate management strategy for orderly scheduling of Electric Vehicles in the battery swapping station is proposed, which considers promoting the wind and photovoltaic power consumption and shaving peak of the grid. A multiobjective optimization model is established with the goal of the minimum variance of the grid load, the least amount of abandoned wind and solar energy, and the maximum revenues of the LAs, which is solved by Genetic Algorithm. The results of the example show that the optimization model can effectively realize the orderly charging of Electric Vehicles, release the peak shaving capacity, absorb the excess wind and photovoltaic power, and reduce costs of LAs and users.

Automated summary

An aggregate management strategy for orderly scheduling of Electric Vehicles in the battery swapping station is proposed in this study to address the issue of peak-to-valley difference in the grid, promoting wind and photovoltaic power consumption while shaving peak of the grid. The optimization model effectively realizes the orderly charging of Electric Vehicles, releases peak shaving capacity, absorbs excess wind and photovoltaic power, and reduces costs for LAs and users.