考虑出行路径决策的电动汽车充电负荷时空预测方法  

Spatial⁃temporal Forecast Method of Electric Vehicles Charging Load Considering Decision⁃making of Trip Path

作　　者：李娇 杨伟[1] LI Jiao;YANG Wei(School of Automation,University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学自动化学院,南京210094

出　　处：《电力电容器与无功补偿》2023年第4期62-71,共10页Power Capacitor & Reactive Power Compensation

基　　金：国家电网公司科技项目(JSDL-XLFW-SQ-2016-10-092)。

摘　　要：为了构建准确的电动汽车充电负荷模型,本文提出一种考虑出行路径决策的充电负荷时空预测方法。首先,采用拉丁超立方采样抽取用户的起始出行时刻和起始荷电状态。其次,考虑用户的不确定性充电需求,利用模糊综合评价法以剩余荷电状态、停驶时长以及充电时长3种评价指标构建用户的充电行为模型。最后,考虑道路交通状况对用户出行路径的影响,根据Logit模型构建路阻函数模型,利用动态Floyd算法获取用户的出行路径,通过蒙特卡罗模拟得到电动汽车充电需求的时空分布。通过算例分析以及路径规划实验,表明本文方法能够更好地模拟用户的实际出行轨迹,在路径规划、载客量的影响以及模型精度上均具有优势。In order to construct an accurate charging load model of electric vehicles,a kind of spatial⁃temporal forecast method considering trip path decision is proposed in this paper.Firstly,Latin hypercube sampling is used to extract the user's initial trip time and initial state of charge.Secondly,considering the uncertain charging demand of users,the fuzzy comprehensive evaluation method is used to construct the user’s charging behavior model with three evaluation indexes:residual state of charge,parking time and charging time.Finally,considering the impact of road traffic conditions on the user’s travel path,the road re⁃sistance function model is constructed in accordance with the logit model,the user’s travel path is obtained by using the dynamic Floyd algorithm,and the temporal and spatial distribution of electric vehicle charging demand is obtained by Monte Carlo simulation.It is shown through example analysis and path planning experimentsthat this method can better simulate the actual travel trajectory of users,and has advantages in path planning,impact of passenger capacity and model accuracy.

关 键 词：充电负荷 时空分布模型 拉丁超立方抽样 交通路网 路径规划 

分 类 号：U491.8[交通运输工程—交通运输规划与管理] TM715[交通运输工程—道路与铁道工程]