Voltage Regulation With Electric Taxi Based on Dynamic Game Strategy

In this paper, a battery charging and swapping optimization model is established for electric vehicles (EVs) and battery charging/swapping stations (BCSS). The EVs are categorized into private electric vehicles (PrEVs) and electric taxis (ETs), where the charging behaviors of PrEVs are modeled based on the Monte Carlo (MC) method, and the battery swapping (BS) strategies of ETs are optimized by bi-level dynamic game. Moreover, the voltage deviation of the power grid is considered in the load regulation process of ETs. A path-location model is established combining with the Floyd algorithm in the simulation and the IEEE 14-Bus system is used to derive the node voltage. Numerical results show that the proposed strategy can simultaneously increase the revenue of BCSS and ETs and reduce the voltage deviation.

Automated summary

This study establishes an optimization model for electric vehicles and battery charging/swapping stations, analyzing the charging behaviors and swapping strategies of different types of EVs, as well as considering voltage deviation in the power grid. The proposed strategy increases revenue for BCSS and ETs while reducing voltage deviation.