摘要
当前的电动汽车充电站规划模型因考虑的因素过少,导致充电站规划时间增多以及充电功率范围下降,所以考虑路网结构建立一种新的电动汽车充电站双层规划模型。基于双层规划理论建立双层规划模型,利用神经网络算法与遗传算法获取双层规划模型中的运行费用和最佳充电路径,获得电动汽车充电站容量预测结果。以预测结果为基础将路网结构作为第一层规划模型,将充电站作为第二层规划模型,在充电站容量可控的情况下实现充电站双层规划模型的构建。实验结果表明,所设计模型能够有效降低充电站规划时间,提高充电功率范围。
The traditional electric vehicle charging station planning model ignores many factors, resulting in long planning time and low charging power range. In this regard, a new bilevel programming model of electric vehicle charging station was established based on road network structure. The bi-level programming model was founded via bilevel programming theory. Neural network algorithm and genetic algorithm were applied to obtain the operation cost and the best charging path for obtaining the electric vehicle charging station capacity prediction results. Based on the results, the road network structure and charging station were regarded as the first level and second level planning models, respectively. When the capacity of charging station was controllable, the bi-level programming model of charging station was constructed. The results show that the model can effectively reduce the planning time of charging station and improve the charging power range.
作者
张密
张代润
谢超
曾皓冬
ZHANG Mi;ZHANG Dai-run;XIE Chao;ZENG Hao-dong(School of Electrical Information,Sichuan University,Chengdu Sichuan 610065,China;School of Electrical Engineering,Sichuan University,Chengdu Sichuan 610065,China)
出处
《计算机仿真》
北大核心
2022年第10期173-177,共5页
Computer Simulation
关键词
路网结构
电动汽车
充电站
双层规划
规划模型
Road network structure
Electric vehicle
Charging station
Bi-level programming
Programming model
