摘要
提出一种基于Pareto蚁群算法的电动汽车充电站智能规划方法:首先,综合各种因素建立多目标充电站规划的数学模型;然后利用Pareto蚁群算法建立相应的电动汽车充电站的选址规划模型;最后,构建基于反向传播神经网络的充电站负荷预测模型,依据负荷预测数据利用Pareto蚁群算法扩展电动汽车充电站。以某高速路网为例,对19个候选站点进行规划,验证了该方法的正确性。
The method of intellgent planning is proposed for electric vehicle charging station.This method is based on Pareto ant colony algorithm.Firstly,the mathematical model of multi-target charging station planning is established by combining various factors,and then the Pareto ant colony algorithm is used to establish the corresponding location planning model of electric vehicle charging station.Finally,the charging station load forecast based on back propagation neural network is constructed.The model uses the Pareto ant colony algorithm to extend the distribution of electric vehicle charging stations based on load forecasting data.Taking the high-speed road network structure as an example,19 candidate sites are planned to verify the correctness of the planning model.
作者
樊文婷
马竞楠
李莹
赵冉
曹娜
FAN Wenting;MA Jingnan;LI Ying;ZHAO Ran;CAO Na(Inner Mongolia Electric Power Group Mengdian Information & Telecommunication Co.,Ltd.,Hohhot 010020,China)
出处
《内蒙古电力技术》
2019年第3期12-17,共6页
Inner Mongolia Electric Power
