An empirical analysis framework to evaluate the impact of residential electric vehicles on power grid

This paper proposes an empirical analysis framework to model the charging behavior of electric vehicles (EVs) and estimate the impact on power grid. This method relies solely on residential charging data and is universally applicable to power grids in different regions. Moreover, the approach enables the simulation of the charging demand under varying EV ownership rate levels and the calculation of the maximum number of EVs that a given area can support without overloading the power grid. As a case study, we collect data on residential charging behavior from a city in Central China to estimate model parameters. Combining with load data, we find that even with a 5 % ownership rate, EVs will not significantly burden the grid load on most days throughout the year or during off-peak hours of the day. However, attention must be given to peak months and peak hours of the day. Additionally, we analyze the ownership rate of EVs that the city can sustain and determine that, with 6 % of the available capacity of distribution transformers, the city can accommodate EVs for 8.12 % of its population. This paper contributes to the engineering management of EVs charging, EVs promotion strategies, and the stability of power grid.