In the process of load impact analysis of electric vehicle charging power, the dynamic adjustment effect is poor due to the influence of load calculation method. Therefore, a dynamic adjustment algorithm of orderly charging power of electric vehicle cluster under the dual constraints of variable capacity and user demand is proposed. Under the double constraints of variable capacity and user demand, the orderly charging power of electric vehicle cluster is calculated, the dynamic regulation model of orderly charging power of electric vehicle cluster is constructed, the objective function is obtained, the energy constraint and power constraint conditions are set, and the dynamic regulation algorithm is designed according to the solution of the regulation model. The experimental results show that this algorithm has better stability and adaptability in regulating the orderly charging power of electric vehicle clusters, and can effectively cope with the load changes under different charging requirements, showing excellent accuracy and consistency.
Aiming at the problem of “1 hour to charge and 4 hours just to queue” during the National Day holiday in 2021, in order to reduce the problems of poor charging experience and reduced confidence in high-speed travel caused by too long charging queuing time, this paper proposes a charging path planning. Based on the state model of electric vehicles (EV), charging stations, traffic network and distribution network, this paper fully considers the charging resources around the expressway network when planning the charging path for users on the expressway network, and proposes a new method considering the “EV-pile-road-grid” state electric vehicle charging path planning. By calling the Baidu map API interface and the data of the charging piles of the Internet of Vehicles Platform, the optimized selection of charging stations is completed, and a feasible navigation path with the shortest travel (time) is finally formed.
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