Integrated Electric Vehicle Charging Path Planning Considering Traffic Network and Power Grid

In order to improve the current situation of urban traffic congestion and interference of EVs with the safe operation of the power grid, we propose a charging path planning that considers the traffic network and power grid demand. This planning uses the power grid to obtain the load curve information of each electric vehicle charging station (EVCS) in the region and suggests a reasonable EVCS for the user. On this basis, it uses the improved ant colony algorithm (IAC) to plan the path for the user by combining the location and driving energy consumption of the user vehicle and the traffic information in the urban traffic network. The information is then updated for the next user to plan the path. The effectiveness of the path planning is reflected using the user comprehensive satisfaction and the variance of the regional EVCS load. The results show that the charging path planning proposed in this paper can not only improve the overall satisfaction of users and optimize their experience, but also reduces the variability of regional EV system loads and makes the spatial and temporal distribution of each EV system load more reasonable.