Abstract
With the rise of electric vehicles, the key of electric vehicle charging is how to charge them in residential areas and other closed environments. Addressing this problem is extremely important for avoiding adverse effects on the load and stability of the neighboring grids where multi-user centralized charging takes place. Therefore, we propose a charging dynamic scheduling algorithm based on user bidding. First, we determine the user charging priority according to bidding. Then, we design a resource allocation policy based on game theory, which could assign charge slots for users. Due to users leaving and urgent user needs, we found an alternate principle that can improve the flexibility slot utilization of charging. Simulation results show that the algorithm could meet the priority needs of users with higher charging prices and timely responses to requests. Meanwhile, this algorithm can ensure orderly electric vehicle charging, improve power utilization efficiency, and ease pressure on grid loads.
Highlights
In the future, the use of electric vehicles (EVs) in closed areas such as residential areas will be widespread; it is very important to have an effective charging management method for EVs in the neighborhood [1]
EVs and the travel law, which can reduce the adverse impact of the load of electric power on the stability of power grids caused by the concentrated disorder changing [2,3], but it can improve the utilization efficiency of the peak power quality [4]
The research shows that the price guidance is an effective method to achieve orderly charge scheduling; the charging demand of the users can be met on the basis of minimizing the energy consumption through price adjustment [5,6,7]
Summary
The use of electric vehicles (EVs) in closed areas such as residential areas will be widespread; it is very important to have an effective charging management method for EVs in the neighborhood [1]. Reference [10] presents a multi-objective optimization algorithm-based coordinated EVs charging strategy, which considers both user-level and system-level benefits simultaneously. Reference [14] presents a heuristic algorithm for time-sharing tariffs to solve the problem of electric vehicle access. The drawback of this approach is that the formulation of electricity prices lacks flexibility, and the algorithm is limited by the degree of user response. Reference [16] presents a method for competing charging station resources based on user bids, which can delay the charging demand of the peak period of the grid to the off-peak time.
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