电力建设2025，Vol.46Issue(12)：57-69,13.DOI:10.12204/j.issn.1000-7229.2025.12.006
基于节假日因素影响的高速服务区充电负荷建模与充电桩优化规划
Charging-Load Modeling and Optimal Charging-Pile Planning in Highway Service Areas Under the Influence of Holiday Factors
摘要
Abstract
[Objective]To achieve carbon-peaking and-neutrality goals,the number of electric vehicles(EVs)in China has grown rapidly.However,the growth of EV-charging infrastructure has lagged behind the rapid increase in demand.The problem of inadequate charging capacity is particularly severe in highway service areas,where challenges such as difficulty in accessing chargers and long waiting queues have become increasingly pronounced.[Methods]First,based on a geographic information system data and actual traffic flow,a travel probability matrix is constructed and a"charging-anxiety coefficient"is introduced to enhance the model's adaptability to real-world scenarios.Second,a"traffic-flow-to-speed impact coefficient"is proposed to improve the accuracy of predicting the state of charge of EVs upon arrival at highway service areas;this coefficient serves as the foundation for forecasting charging loads.Finally,a multi-service-area charging-pile optimization model is developed based on the forecast results.This model incorporates a dynamic weight adjustment mechanism based on traffic flow,allowing for the flexible reallocation of construction,operation and maintenance,and user-waiting-time costs under varied traffic load conditions,thereby enabling adaptive optimization of objective function weights.[Results]Simulation results show that although increasing the number of charging piles significantly reduces user waiting times,it also leads to higher investment costs.Peak charging loads during holidays increase by 26.3%compared with those during normal periods,exhibiting a bimodal pattern,with demand concentrated in service areas located in the last half of travel routes.The proposed dynamic weight adjustment mechanism adapts to traffic flow fluctuations,enabling an adaptive balance between costs and user experience.[Conclusions]Introducing a dynamic weight adjustment mechanism and optimizing charging-pile allocation across multiple service areas significantly enhance the flexibility and responsiveness of highway charging networks in matching supply with demand.Under the combined effects of traffic flow fluctuations and holiday demand peaks,the proposed approach achieves precise coupling between charging resources and user needs.This not only improves pile utilization rates and reduces queuing times but also effectively balances construction and operational costs.关键词
电动汽车/充电负荷预测/高速公路服务区/充电桩优化配置/出行概率矩阵/充电焦虑系数Key words
electric vehicle/charging-load prediction/highway service area/charging-pile optimization allocation/dynamic weight adjustment mechanism/charging-anxiety factor分类
信息技术与安全科学引用本文复制引用
LI Zhenkun,XIAO Tianyu,SONG Zhiru,ZHANG Zhiquan..基于节假日因素影响的高速服务区充电负荷建模与充电桩优化规划[J].电力建设,2025,46(12):57-69,13.基金项目
国家自然科学基金项目(52177098) This work is supported by the National Natural Science Foundation of China(No.52177098). （52177098）
