Analysis of Urban Electric Vehicle Charging Power Demand under Extreme Weather

With the implementation and promotion of the national “double carbon” policy, the electric vehicle industry is developing rapidly. The energy consumption, battery capacity fluctuation and charging power characteristics of electric vehicles (EVs) influence not only the development of the electric vehicle industry, but also the safe operation of the power grid. Ambient temperature and road traffic congestion influence the energy consumption of EVs, which leads to different charging power. In this paper, based on statistical methods, we analyze a large number of traffic data samples to dig out the function relationship between the average speed of electric vehicle driving and road congestion coefficient, and propose a general calculation model based on energy consumption, battery capacity and charging power of EVs accordingly. Taking a large city in China as an example, a Monte Carlo method is used to simulate the charging load of each type of EV under different ambient temperatures and different EV penetration rates to analyze the impact of EVs on the grid and provide a reference for the grid to cope with the sudden increase of EV penetration in the future.

I. Introduction

Recently, in the context of the national vigorous implementation of carbon peak and neutrality targets, electric vehicles have been vigorously promoted by the government because of its advantages of energy saving and environmental protection. Moreover, the “New Energy Vehicle Industry Development Plan (2021-2035)” [1] released by the General Office of the State Council also requires to increase the construction of basic charging facilities and improve the service level of charging infrastructure. The promotion and popularization of electric energy replenishment facilities and the improvement of charging conditions will greatly enhance the car experience of EV owners and will be more accepted by people. With the increase of electric vehicle ownership, when large-scale EVs are connected to the power grid in the future, their charging and discharging behavior may bring pressure to the power grid. Therefore, accurate prediction of urban electric vehicle driving energy consumption and charging load can enable grid planning to better adapt to the large-scale growth of electric vehicles in the future.