Abstract
Electric vehicles, as a new generation of road transport, are primarily used for transportation. For this reason, the topological characteristics of traffic network may make great influence on the macroscopic characteristics of electric vehicle group. However, little attention is drawn to the study in this field. Therefore, typical approach to studying the impact of traffic network topological characteristics on the charging characteristics of large-scale electric vehicle group is presented by adopting the charging power distribution as analysis indicator. In this paper, a model of complex adaptive system is constructed including the electric vehicle group, traffic network and charging stations, where the tempo-spatial distribution of charging power can be obtained via the simulation with the multi-agent technique. The charging power of regional electric vehicles is found obedient to logarithmic normal distribution after analysis, while the mathematical expectation of probability density shows obvious cyclicity. Finally, the traffic networks of various cities in comparison testify to that improving the connectivity of traffic network and increasing the average clustering coefficient can effectively reduce the effect on power system brought by the charging load of large-scale electric vehicle group.
Highlights
Travel revolutions such as electric vehicle (EV), shared mobility and automatic driving are increasingly affecting the energy demand of road traffic [1], playing an important role in modern transportation [2], [3]
In this paper, multi-agent technique is introduced to study on the charging characteristics of large-scale EV group
We first carry out multi-agent simulation based on the platform of Java agent development framework (JADE)/Multi-Agent
Summary
Travel revolutions such as electric vehicle (EV), shared mobility and automatic driving are increasingly affecting the energy demand of road traffic [1], playing an important role in modern transportation [2], [3]. Many papers forecast the tempo-spatial distribution of EV charging load, it remains a problem to reflect the macroscopic characteristics of the charging behavior in large-scale EV group, since those studies are always with only a small quantity of vehicles and a small scale of map in modeling It is worth going further into the influence of traffic topological characteristics on EV charging characteristics and scaling up the EV group for research. For the problem discussed above, we will extract the actual traffic network data of Guangzhou and several other cities in China, combine the future driving pattern of shared mobility and automatic driving, and study the charging characteristics of large-scale EV group by simulation. A comparison between traffic networks of various cities is made to draw a conclusion on the impact of traffic topological characteristics on charging power distribution characteristics
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