To adress the problems of insufficient consideration of charging pile resource limitations,discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response cap...To adress the problems of insufficient consideration of charging pile resource limitations,discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response capability in current electric vehicle(EV)opti-mization scheduling,edge intelligence-oriented electric vehicle optimization scheduling and charging station peak-shaving response capability assessment methods are proposed on the basis of the consideration of electric vehicle and charging pile matching.First,an edge-intelligence-oriented electric vehicle regulation frame for charging stations is proposed.Second,continuous time variables are used to represent the available charging periods,establish the charging station controllable EV load model and the future available charging pile mathematical model,and establish the EV and charging pile matching matrix and constraints.Then,with the goal of maximizing the user charging demand and reducing the charging cost,the charging station EV optimal scheduling model is established,and the EV peak response capacity assessment model is further established by considering the EV load shifting constraints under different peak response capacities.Finally,a typical scenario of a real charging station is taken as an example for the analysis of optimal EV scheduling and peak shaving response capacity,and the proposed method is compared with the traditional method to verify the effectiveness and practicality of the proposed method.展开更多
Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive ...Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive construction spending,maintenance costs,and urban space occupation.However,recent developments in technology may significantly reduce the necessary charging capacity required by the system.This paper develops a linear programming model to characterize the effects of likely scenarios where vehicle-to-vehicle(V2V)charging is available via vehicle modularization or wireless charging.Specifically,we consider scenarios in which vehicles can transmit energy to each other(coordinated by a central platform)while traveling closely on the same road.We first estimate the number of charging piles needed for completing the travel plan of 73 cars from data,assuming a battery capacity of 400 km’s range and no V2V charging.Our results show that once V2V charging technologies with an efficiency of 50%are available,more than 2/3 of the charging piles investment would be wasted.Additionally,if the efficiency of V2V charging increases to 75%,we can easily reduce the battery capacity of vehicles to 200 km,which will reduce production costs and improve energy efficiency.These results may reveal us an alternative pathway towards transportation electrification.展开更多
新能源汽车的充电基础设施是新能源汽车产业的重要组成部分,是新能源汽车最重要的配套基础设施。针对现有充电桩无法进行远程管理控制和数据采集的问题,基于现有充电桩和国家标准设计一款电动汽车有序充电智能管控装置。该装置主要由数...新能源汽车的充电基础设施是新能源汽车产业的重要组成部分,是新能源汽车最重要的配套基础设施。针对现有充电桩无法进行远程管理控制和数据采集的问题,基于现有充电桩和国家标准设计一款电动汽车有序充电智能管控装置。该装置主要由数据转换单元(Data Transfer Unit,DTU)和充电管理控制器组成。DTU与每台充电中的充电管理控制器及小区基础负荷总电度量表进行通信,同时通过以太网接口与服务器进行通信,实现数据的远程传输与中转。同时解决充电桩与服务器之间的连接问题。充电管理控制器作为核心部件,具备控制充电桩的通断和采集充电状态信息的功能。通过接收来自服务器的指令,可以实现对充电桩的远程控制。同时充电管理控制器还可以实时采集充电桩的充电状态信息,并将这些信息传输给服务器,以便用户和管理员进行查看和监控。展开更多
基金supported by the Science and Technology Project of State Grid Jiangsu Electric Power Company(J2023114).
文摘To adress the problems of insufficient consideration of charging pile resource limitations,discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response capability in current electric vehicle(EV)opti-mization scheduling,edge intelligence-oriented electric vehicle optimization scheduling and charging station peak-shaving response capability assessment methods are proposed on the basis of the consideration of electric vehicle and charging pile matching.First,an edge-intelligence-oriented electric vehicle regulation frame for charging stations is proposed.Second,continuous time variables are used to represent the available charging periods,establish the charging station controllable EV load model and the future available charging pile mathematical model,and establish the EV and charging pile matching matrix and constraints.Then,with the goal of maximizing the user charging demand and reducing the charging cost,the charging station EV optimal scheduling model is established,and the EV peak response capacity assessment model is further established by considering the EV load shifting constraints under different peak response capacities.Finally,a typical scenario of a real charging station is taken as an example for the analysis of optimal EV scheduling and peak shaving response capacity,and the proposed method is compared with the traditional method to verify the effectiveness and practicality of the proposed method.
基金support from the Ministry of Education China and NSFC through the CJJX scheme(20221710034).
文摘Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive construction spending,maintenance costs,and urban space occupation.However,recent developments in technology may significantly reduce the necessary charging capacity required by the system.This paper develops a linear programming model to characterize the effects of likely scenarios where vehicle-to-vehicle(V2V)charging is available via vehicle modularization or wireless charging.Specifically,we consider scenarios in which vehicles can transmit energy to each other(coordinated by a central platform)while traveling closely on the same road.We first estimate the number of charging piles needed for completing the travel plan of 73 cars from data,assuming a battery capacity of 400 km’s range and no V2V charging.Our results show that once V2V charging technologies with an efficiency of 50%are available,more than 2/3 of the charging piles investment would be wasted.Additionally,if the efficiency of V2V charging increases to 75%,we can easily reduce the battery capacity of vehicles to 200 km,which will reduce production costs and improve energy efficiency.These results may reveal us an alternative pathway towards transportation electrification.
文摘新能源汽车的充电基础设施是新能源汽车产业的重要组成部分,是新能源汽车最重要的配套基础设施。针对现有充电桩无法进行远程管理控制和数据采集的问题,基于现有充电桩和国家标准设计一款电动汽车有序充电智能管控装置。该装置主要由数据转换单元(Data Transfer Unit,DTU)和充电管理控制器组成。DTU与每台充电中的充电管理控制器及小区基础负荷总电度量表进行通信,同时通过以太网接口与服务器进行通信,实现数据的远程传输与中转。同时解决充电桩与服务器之间的连接问题。充电管理控制器作为核心部件,具备控制充电桩的通断和采集充电状态信息的功能。通过接收来自服务器的指令,可以实现对充电桩的远程控制。同时充电管理控制器还可以实时采集充电桩的充电状态信息,并将这些信息传输给服务器,以便用户和管理员进行查看和监控。
