The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station pe...The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency,station utilization rates,no-power session occurrences,and CO_(2)reduction metrics.A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization.Results indicate a strong correlation between station utilization and energy efficiency,highlighting the importance of strategic station placement.The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring.CO_(2)reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals.Based on these insights,this study recommends the implementation of predictive maintenance strategies,real-time user notifications,and diversified provider networks to improve station availability and efficiency.The proposed data-driven framework offers actionable solutions for policymakers,charging network operators,and urban planners to enhance EV infrastructure reliability and sustainability.展开更多
Electric vehicle is a kind of new energy vehicle which uses batteries as energy supply unit.A huge gap in charging infrastructures will be created by the expansion of electric vehicles.The effectiveness and rationalit...Electric vehicle is a kind of new energy vehicle which uses batteries as energy supply unit.A huge gap in charging infrastructures will be created by the expansion of electric vehicles.The effectiveness and rationality of charging facilities will directly affect the convenience and economy of the users,as well as the safe operation of the power grid.Three types of charging facilities:charging pile,charging station and battery swap station are introduced in this paper.According to the different methods of charging infrastructure planning,the research status of the method of determining charging demand points is expounded.And the spatial distribution of charging demand points extracted by the current site selection method has a certain deviation.Then the models and algorithms of charging infrastructure optimized layout are reviewed.Currently,many researches focus on three categories optimization objectives:benefit of power company side,investment cost of charging facility and user side cost,and the genetic algorithm and particle swarm optimization are the main solving algorithms.Finally,the relative methods and development trend of the charging infrastructures optimized layout are summarized,and some suggestions on the optimized layout of electric vehicle charging infrastructures are given forward.展开更多
With the new round of scientific and technological revolution and industrial transformation,China has posited the direction of“new infrastructure”in 2020.As one of the seven major industries of the“new infrastruct...With the new round of scientific and technological revolution and industrial transformation,China has posited the direction of“new infrastructure”in 2020.As one of the seven major industries of the“new infrastructure”,the charging infrastructure(CI)industry not only supports the upgrade of the new energy vehicle industry but also provides developing platforms for emerging industries,such as wireless charging,energy storage,smart microgrid,and new energy consumption.Therefore,the government’s supporting role is crucial for the CI industry.To effectively explore the effectiveness of government’s subsidy policy in the CI industry and promote its healthy development,we employed a game model and discussed the government's evolution process of different game strategies between CI and battery-swapping station(BSS)operators in this study.First,China's government subsidies for the electric vehicle(EV)industry were classified into CIs and BSSs.The subsidies obtained by the CI operators were operating subsidies,whereas those obtained by BSSs were investment subsidies.Second,a game model was constructed,involving the government,operators,and users.The model used backward induction to seek the refined Nash equilibrium solution for CIs and BSS operators.The Nash equilibrium solution indicated that the optimal investment amount and BSS quantity of the operator were positively correlated with the government subsidy intensity.When the profitability of the operators increased and the amount of the subsidies increased,consumers’willingness to use EVs increased and the policy effects were closely related to the benefits of government management.The decisions made by either the users or the operators were inversely related to the operators’management efficiency.Besides,the subsidy policy was affected by the government management.Therefore,in the implementation stage of the government’s future subsidy policies,the government needs to innovate and improve management effectiveness.The government could use subsidy policies as a driving force for developing the CI industry to build a comprehensive ecosystem of the industry,which is also the next key point for the government to promote the development of the CI industry in the future.展开更多
The construction of charging infrastructure is an important prerequisite for the development of electric vehicles （EVs）. In this paper, the classification of charging vehicle models and charging infrastructure was f...The construction of charging infrastructure is an important prerequisite for the development of electric vehicles （EVs）. In this paper, the classification of charging vehicle models and charging infrastructure was firstly summarized, and the optimal charging mode of each type of EV model and the total electicity demand of charging were then analyzed. Combined with the general principle of the development and application of new energy vehicles in the city H, the model of electric vehicle charging infrastructure planning was designed. The case we proposed fully proved the effectiveness of the model.展开更多
The challenge to deal with environmental contamination along with national goals such as energy security,reliability,and self-dependency due to depleting fossil fuel resources has motivated researchers to find an alte...The challenge to deal with environmental contamination along with national goals such as energy security,reliability,and self-dependency due to depleting fossil fuel resources has motivated researchers to find an alternate solution in the transport sector.Due to this,electrification of the transport sector has become an achievable solution that has caught attention with increasing penetration in the market share.India is a participant in the Paris Agreement which aims to curtail the production of greenhouse gases and limit the escalating temperature.Public intervention and changes in policy and regulations are the key aspects of technological transition.Compared to internal combustion engine(ICE)-based vehicles,the consumers’frame of mind concerns about adapting to e-mobility is anxiety over charging times and driving range.Thus,the development of charging stations plays a crucial role in promoting electric vehicles(EVs).This study investigates to identify different barriers that exist in the Indian context related to the adoption of e-mobility.Furthermore,this work emphasizes the recent developments in charging infrastructure planning in India.Also,the status of installed charging stations is examined.Developing appropriate charging stations are associated with several challenges,which are also highlighted to provide guidance to public and private entities that can be adopted in their respective business model.As India has the second largest population and is the seventh largest country in the world,the EV adoption rate of India is considerably low compared to other countries;for India,there is a long way to match the growth rate of EV adoption.Hence it becomes essential to develop a robust and suitable charging infrastructure to promote the sale and use of EVs in India.展开更多
This paper focuses on the development of electric vehicle(EV)charging infrastructure in the UK,which is a vital part of the delivering ultra-low-emission vehicle(ULEV)and will transition into low emission energy syste...This paper focuses on the development of electric vehicle(EV)charging infrastructure in the UK,which is a vital part of the delivering ultra-low-emission vehicle(ULEV)and will transition into low emission energy systems in the near future.Following a brief introduction to global landscape of EV and its infrastructure,this paper presents the EV development in the UK.It then unveils the government policy in recent years,charging equipment protocols or standards,and existing EV charging facilities.Circuit topologies of charging infrastructure are reviewed.Next,three important factors to be considered in a typical site,i.e.,design,location and cost,are discussed in detail.Furthermore,the management and operation of charging infrastructure including different types of business models are summarized.Last but not least,challenges and future trends are discussed.展开更多
Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector.Deployment of charging infrastructure is needed to accelerate technology ad...Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector.Deployment of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across regions.In this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including Chinese.We investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously available.We find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of interest.This evidence contrasts with predictions in the U.S.and European markets,where the performance is closer to parity.We also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.展开更多
The current increase in the number of electric vehicles in Germany requires an adequately developed charging infrastructure.Large numbers of public and semi-public charging stations are necessary to ensure sufficient ...The current increase in the number of electric vehicles in Germany requires an adequately developed charging infrastructure.Large numbers of public and semi-public charging stations are necessary to ensure sufficient coverage of charging options.In order to make the installation worthwhile for the mostly private operators as well as public ones,a sufficient utilization is decisive.This paper gives an overview of the differences in the utilization across the public charging infrastructure in Germany.To this end,a dataset on the utilization of 21164 public and semi-public charging stations in Germany is evaluated.The installation and operating costs of various charging stations are modeled and economically evaluated in combination with the utilization data.It is shown that in 2019-2020,the average utilization in Germany was rather low,albeit with striking regional differences.We consider future scenarios allowing the regional development forecasting of economic viability.It is demonstrated that a growth in electric mobility of 20%-30%per year leads to a large number of economically feasible charging parks in urban agglomeration areas.展开更多
In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including i...In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including increased peak power demand and the need for substantial upgrades to power infrastruc-ture.Here,we introduce an integrated model to assess fast and ultrafast charging impacts for represen-tative charging stations in China,combining real-world charging patterns and detailed station optimization models.We find that larger stations with 12 or more chargers experience modest peak power increases of less than 30%when fast-charging power is doubled,primarily because shorter charg-ing sessions are less likely to overlap.For more typical stations(e.g.,8-9 chargers and 120 kW·charger^(−1)),upgrading chargers to 350-550 kW while allowing managed dynamic waiting strategies(of∼1 minute)can reduce overall charging times to∼9 minutes.At stations,deploying battery storage and/or expanding transformers can help manage future increases in station loads,yet the primary device cost of the former is∼4 times higher than that of the latter.Our results offer insights for charging infrastructure planning,EV-grid interactions,and associated policymaking.展开更多
Driven by the dual carbon goals and the national strategy for the high-quality development of the advanced manufacturing industry,along with the trend of economic transformation,China’s new energy vehicle market has ...Driven by the dual carbon goals and the national strategy for the high-quality development of the advanced manufacturing industry,along with the trend of economic transformation,China’s new energy vehicle market has experienced explosive growth,which has spurred a surge in the construction of domestic charging infrastructure.Charging infrastructure not only supports achieving dual carbon goals and the development of the new energy vehicle industry but also undertakes the new historical mission of infrastructure in China’s new development stage,becoming a crucial infrastructure connecting energy decarbonization and transportation electrification[1].In recent years,central and local governments have placed great emphasis on this field.They have introduced policies from various angles,including comprehensive macro-level measures,government planning,financial subsidies,charging rates,industry management,and scientific and technological innovation,to promote the moderately advanced development of charging facilities.展开更多
Charging infrastructure supports the rapid development of China's new energy vehicle industry.It not only plays a decisive role in providing accessible and convenient services for electric vehicle(EV)users but als...Charging infrastructure supports the rapid development of China's new energy vehicle industry.It not only plays a decisive role in providing accessible and convenient services for electric vehicle(EV)users but also,in one of the seven new infrastructure areas,plays an important role in stabilizing growth and unleashing economic potential during the new coronavirus(COVID-19)pandemic,impacting China's economy.In this study,the system dynamics model was used to predict the development of the EV industry and the demand for charging infrastructure,while considering the influence of policy,increase in EV mileage,and consumer purchase intention index.Furthermore,using the matching of EVs and charging infrastructure in Beijing and policy oriented sensitivity analysis,a simulation of the construction of battery swap taxis and power stations under three policy scenarios was conducted.This research shows that with policies implemented to support charging infrastructure and swapping compatible taxis,Beijing can achieve its goal of replacing all EVs with fast-swap batteries and fast-charging functions within three years.展开更多
For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sida...For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sidak, Spulber, put forward M-ECPR （Market Efficient Component Pricing Rule） method for bottleneck infrastructures. In this article, we bring the M-ECPR principles into the study of Chinese railways pricing of its network infrastructures. Combined with our Engineer Model and Opportunity Cost Model, we analyzed the special conditions faced by Chinese railways, and developed a model for sharing infrastructure fees among freight and passenger transportations. Engineer Model split Variable Cost （VC） and Fixed Cost （FC） into freight and passenger activities, and Opportunity Cost Model take the insufficient supply of infrastructure capacity into consideration. Of course, the subsidy from the government greatly affected the price standard for bottleneck facilities, or so-called network infrastructures.展开更多
This paper presents a data-driven joint model designed to simultaneously deploy and operate infrastructure for shared electric vehicles(SEVs).The model takes into account two prevalent smart charging strategies:the Ti...This paper presents a data-driven joint model designed to simultaneously deploy and operate infrastructure for shared electric vehicles(SEVs).The model takes into account two prevalent smart charging strategies:the Time-of-Use(TOU)tariff and Vehicle-to-Grid(V2G)technology.We specifically quantify infrastructural demand and simulate the travel and charging behaviors of SEV users,utilizing spatiotemporal and behavioral data extracted from a SEV trajectory dataset.Our findings indicate that the most cost-effective strategy is to deploy slow chargers exclusively at rental stations.For SEV operators,the use of TOU and V2G strategies could potentially reduce charging costs by 17.93%and 34.97%respectively.In the scenarios with V2G applied,the average discharging demand is 2.15kWh per day per SEV,which accounts for 42.02%of the actual average charging demand of SEVs.These findings are anticipated to provide valuable insights for SEV operators and electricity companies in their infrastructure investment decisions and policy formulation.展开更多
To accurately simulate electric vehicle DC fast chargers'(DCFCs')harmonic emission,a small time step,i.e.,typically smaller than 10μs,is required owing to switching dynamics.However,in practice,harmonics shou...To accurately simulate electric vehicle DC fast chargers'(DCFCs')harmonic emission,a small time step,i.e.,typically smaller than 10μs,is required owing to switching dynamics.However,in practice,harmonics should be continuously assessed with a long duration,e.g.,a day.A trade-off between accuracy and time efficiency thus exists.To address this issue,a multi-time scale modeling framework of fast-charging stations(FCSs)is proposed.In the presented framework,the DCFCs'input impedance and harmonic current emission in the ideal grid condition,that is,zero grid impedance and no background harmonic voltage,are obtained based on a converter switching model with a small timescale simulation.Since a DCFC's input impedance and harmonic current source are functions of the DCFC's load,the input impedance and harmonic emission at different loads are obtained.Thereafter,they are used in the fast-charging charging station modeling,where the DCFCs are simplified as Norton equivalent circuits.In the station level simulation,a large time step,i.e.,one minute,is used because the DCFCs'operating power can be assumed as a constant over a minute.With this co-simulation,the FCSs'long-term power quality performance can be assessed time-efficiently,without losing much accuracy.展开更多
Electric vehicles(EVs)have received significant attention because of the potential energy savings and emission reductions they enable.However,current studies and demonstrations have focused mainly on specific technolo...Electric vehicles(EVs)have received significant attention because of the potential energy savings and emission reductions they enable.However,current studies and demonstrations have focused mainly on specific technologies and equipment types,which cannot in themselves solve the predicaments facing EVs.This study points out that EVs will form a large,complex system that needs to be optimized over different aspects to compete with traditional vehicles.Therefore,wholesystem thinking is needed to support the development control of EVs,with a broader scope than operational control,and the core issue is the interaction between EVs and power grid,including their coordinated development and operational management.For development control of EVs,a target system and a step-wise optimization method are presented,as well as the basic principles for designing the target system.There are two key barriers in EVs’development:the research and mass production of highperformance power batteries,and the formulation of a favorable mechanism to capture benefits and encourage development.To address the problems of EV development,a promotion method that combines franchising with moderate competition is proposed.The concepts and methods developed in this study can facilitate the research and development of EVs.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
文摘The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency,station utilization rates,no-power session occurrences,and CO_(2)reduction metrics.A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization.Results indicate a strong correlation between station utilization and energy efficiency,highlighting the importance of strategic station placement.The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring.CO_(2)reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals.Based on these insights,this study recommends the implementation of predictive maintenance strategies,real-time user notifications,and diversified provider networks to improve station availability and efficiency.The proposed data-driven framework offers actionable solutions for policymakers,charging network operators,and urban planners to enhance EV infrastructure reliability and sustainability.
基金Project(21805217)supported by the National Natural Science Foundation of ChinaProject(2015BAG08B02)supported by the National Key Technologies Research and Development Program of ChinaProject(2019IVB014)supported by the Fundamental Research Funds for the Central Universities,China。
文摘Electric vehicle is a kind of new energy vehicle which uses batteries as energy supply unit.A huge gap in charging infrastructures will be created by the expansion of electric vehicles.The effectiveness and rationality of charging facilities will directly affect the convenience and economy of the users,as well as the safe operation of the power grid.Three types of charging facilities:charging pile,charging station and battery swap station are introduced in this paper.According to the different methods of charging infrastructure planning,the research status of the method of determining charging demand points is expounded.And the spatial distribution of charging demand points extracted by the current site selection method has a certain deviation.Then the models and algorithms of charging infrastructure optimized layout are reviewed.Currently,many researches focus on three categories optimization objectives:benefit of power company side,investment cost of charging facility and user side cost,and the genetic algorithm and particle swarm optimization are the main solving algorithms.Finally,the relative methods and development trend of the charging infrastructures optimized layout are summarized,and some suggestions on the optimized layout of electric vehicle charging infrastructures are given forward.
基金National Social Science Foundation of China Key Project“Technologydriven New Energy Vehicle Industry Business Model Innovation Research”[Grant Number.16AGL004].
文摘With the new round of scientific and technological revolution and industrial transformation,China has posited the direction of“new infrastructure”in 2020.As one of the seven major industries of the“new infrastructure”,the charging infrastructure(CI)industry not only supports the upgrade of the new energy vehicle industry but also provides developing platforms for emerging industries,such as wireless charging,energy storage,smart microgrid,and new energy consumption.Therefore,the government’s supporting role is crucial for the CI industry.To effectively explore the effectiveness of government’s subsidy policy in the CI industry and promote its healthy development,we employed a game model and discussed the government's evolution process of different game strategies between CI and battery-swapping station(BSS)operators in this study.First,China's government subsidies for the electric vehicle(EV)industry were classified into CIs and BSSs.The subsidies obtained by the CI operators were operating subsidies,whereas those obtained by BSSs were investment subsidies.Second,a game model was constructed,involving the government,operators,and users.The model used backward induction to seek the refined Nash equilibrium solution for CIs and BSS operators.The Nash equilibrium solution indicated that the optimal investment amount and BSS quantity of the operator were positively correlated with the government subsidy intensity.When the profitability of the operators increased and the amount of the subsidies increased,consumers’willingness to use EVs increased and the policy effects were closely related to the benefits of government management.The decisions made by either the users or the operators were inversely related to the operators’management efficiency.Besides,the subsidy policy was affected by the government management.Therefore,in the implementation stage of the government’s future subsidy policies,the government needs to innovate and improve management effectiveness.The government could use subsidy policies as a driving force for developing the CI industry to build a comprehensive ecosystem of the industry,which is also the next key point for the government to promote the development of the CI industry in the future.
基金Supported by the 2016 Science and Technology Project of Zhejiang Electric Power Corporation(5211HZ15018V)
文摘The construction of charging infrastructure is an important prerequisite for the development of electric vehicles （EVs）. In this paper, the classification of charging vehicle models and charging infrastructure was firstly summarized, and the optimal charging mode of each type of EV model and the total electicity demand of charging were then analyzed. Combined with the general principle of the development and application of new energy vehicles in the city H, the model of electric vehicle charging infrastructure planning was designed. The case we proposed fully proved the effectiveness of the model.
文摘The challenge to deal with environmental contamination along with national goals such as energy security,reliability,and self-dependency due to depleting fossil fuel resources has motivated researchers to find an alternate solution in the transport sector.Due to this,electrification of the transport sector has become an achievable solution that has caught attention with increasing penetration in the market share.India is a participant in the Paris Agreement which aims to curtail the production of greenhouse gases and limit the escalating temperature.Public intervention and changes in policy and regulations are the key aspects of technological transition.Compared to internal combustion engine(ICE)-based vehicles,the consumers’frame of mind concerns about adapting to e-mobility is anxiety over charging times and driving range.Thus,the development of charging stations plays a crucial role in promoting electric vehicles(EVs).This study investigates to identify different barriers that exist in the Indian context related to the adoption of e-mobility.Furthermore,this work emphasizes the recent developments in charging infrastructure planning in India.Also,the status of installed charging stations is examined.Developing appropriate charging stations are associated with several challenges,which are also highlighted to provide guidance to public and private entities that can be adopted in their respective business model.As India has the second largest population and is the seventh largest country in the world,the EV adoption rate of India is considerably low compared to other countries;for India,there is a long way to match the growth rate of EV adoption.Hence it becomes essential to develop a robust and suitable charging infrastructure to promote the sale and use of EVs in India.
基金a research project in collaboration with and sponsored by XU JI Power Co.,Ltd.,Xuchang,China。
文摘This paper focuses on the development of electric vehicle(EV)charging infrastructure in the UK,which is a vital part of the delivering ultra-low-emission vehicle(ULEV)and will transition into low emission energy systems in the near future.Following a brief introduction to global landscape of EV and its infrastructure,this paper presents the EV development in the UK.It then unveils the government policy in recent years,charging equipment protocols or standards,and existing EV charging facilities.Circuit topologies of charging infrastructure are reviewed.Next,three important factors to be considered in a typical site,i.e.,design,location and cost,are discussed in detail.Furthermore,the management and operation of charging infrastructure including different types of business models are summarized.Last but not least,challenges and future trends are discussed.
基金supported by funding from the National Science Foundation(Nos.1931980 and 1945332)Microsoft Azure for researchand the U.S.State Department Diplomacy Lab.
文摘Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector.Deployment of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across regions.In this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including Chinese.We investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously available.We find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of interest.This evidence contrasts with predictions in the U.S.and European markets,where the performance is closer to parity.We also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.
基金supported by the Federal Ministry for Economic Affairs and Energy(No.01MZ18006G).
文摘The current increase in the number of electric vehicles in Germany requires an adequately developed charging infrastructure.Large numbers of public and semi-public charging stations are necessary to ensure sufficient coverage of charging options.In order to make the installation worthwhile for the mostly private operators as well as public ones,a sufficient utilization is decisive.This paper gives an overview of the differences in the utilization across the public charging infrastructure in Germany.To this end,a dataset on the utilization of 21164 public and semi-public charging stations in Germany is evaluated.The installation and operating costs of various charging stations are modeled and economically evaluated in combination with the utilization data.It is shown that in 2019-2020,the average utilization in Germany was rather low,albeit with striking regional differences.We consider future scenarios allowing the regional development forecasting of economic viability.It is demonstrated that a growth in electric mobility of 20%-30%per year leads to a large number of economically feasible charging parks in urban agglomeration areas.
基金the support of the National Natural Science Foundation of China(72325006,72488101,and 72293601)the Sze Family Foundationthe Climate Imperative Foundation(#2024-001465)
文摘In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including increased peak power demand and the need for substantial upgrades to power infrastruc-ture.Here,we introduce an integrated model to assess fast and ultrafast charging impacts for represen-tative charging stations in China,combining real-world charging patterns and detailed station optimization models.We find that larger stations with 12 or more chargers experience modest peak power increases of less than 30%when fast-charging power is doubled,primarily because shorter charg-ing sessions are less likely to overlap.For more typical stations(e.g.,8-9 chargers and 120 kW·charger^(−1)),upgrading chargers to 350-550 kW while allowing managed dynamic waiting strategies(of∼1 minute)can reduce overall charging times to∼9 minutes.At stations,deploying battery storage and/or expanding transformers can help manage future increases in station loads,yet the primary device cost of the former is∼4 times higher than that of the latter.Our results offer insights for charging infrastructure planning,EV-grid interactions,and associated policymaking.
文摘Driven by the dual carbon goals and the national strategy for the high-quality development of the advanced manufacturing industry,along with the trend of economic transformation,China’s new energy vehicle market has experienced explosive growth,which has spurred a surge in the construction of domestic charging infrastructure.Charging infrastructure not only supports achieving dual carbon goals and the development of the new energy vehicle industry but also undertakes the new historical mission of infrastructure in China’s new development stage,becoming a crucial infrastructure connecting energy decarbonization and transportation electrification[1].In recent years,central and local governments have placed great emphasis on this field.They have introduced policies from various angles,including comprehensive macro-level measures,government planning,financial subsidies,charging rates,industry management,and scientific and technological innovation,to promote the moderately advanced development of charging facilities.
基金This research was funded by the National Social Science Fund of China[Grant number.16AGL004].
文摘Charging infrastructure supports the rapid development of China's new energy vehicle industry.It not only plays a decisive role in providing accessible and convenient services for electric vehicle(EV)users but also,in one of the seven new infrastructure areas,plays an important role in stabilizing growth and unleashing economic potential during the new coronavirus(COVID-19)pandemic,impacting China's economy.In this study,the system dynamics model was used to predict the development of the EV industry and the demand for charging infrastructure,while considering the influence of policy,increase in EV mileage,and consumer purchase intention index.Furthermore,using the matching of EVs and charging infrastructure in Beijing and policy oriented sensitivity analysis,a simulation of the construction of battery swap taxis and power stations under three policy scenarios was conducted.This research shows that with policies implemented to support charging infrastructure and swapping compatible taxis,Beijing can achieve its goal of replacing all EVs with fast-swap batteries and fast-charging functions within three years.
文摘For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sidak, Spulber, put forward M-ECPR （Market Efficient Component Pricing Rule） method for bottleneck infrastructures. In this article, we bring the M-ECPR principles into the study of Chinese railways pricing of its network infrastructures. Combined with our Engineer Model and Opportunity Cost Model, we analyzed the special conditions faced by Chinese railways, and developed a model for sharing infrastructure fees among freight and passenger transportations. Engineer Model split Variable Cost （VC） and Fixed Cost （FC） into freight and passenger activities, and Opportunity Cost Model take the insufficient supply of infrastructure capacity into consideration. Of course, the subsidy from the government greatly affected the price standard for bottleneck facilities, or so-called network infrastructures.
基金National Natural Science Foundation of China(52002345)Public Policy Research Funding Scheme of The Government of the Hong Kong Special Administrative Region(Project Number:2023.A6.232.23B)+2 种基金Hong Kong Polytechnic University[P0013893P0038213P0041230].
文摘This paper presents a data-driven joint model designed to simultaneously deploy and operate infrastructure for shared electric vehicles(SEVs).The model takes into account two prevalent smart charging strategies:the Time-of-Use(TOU)tariff and Vehicle-to-Grid(V2G)technology.We specifically quantify infrastructural demand and simulate the travel and charging behaviors of SEV users,utilizing spatiotemporal and behavioral data extracted from a SEV trajectory dataset.Our findings indicate that the most cost-effective strategy is to deploy slow chargers exclusively at rental stations.For SEV operators,the use of TOU and V2G strategies could potentially reduce charging costs by 17.93%and 34.97%respectively.In the scenarios with V2G applied,the average discharging demand is 2.15kWh per day per SEV,which accounts for 42.02%of the actual average charging demand of SEVs.These findings are anticipated to provide valuable insights for SEV operators and electricity companies in their infrastructure investment decisions and policy formulation.
基金funding from the Electronic Components and Systems for European Leadership Joint Undertaking under grant agreement No.876868support from the European Union's Horizon 2020 research and innovation programme and Germany,Slovakia,Netherlands,Spain,Italy.
文摘To accurately simulate electric vehicle DC fast chargers'(DCFCs')harmonic emission,a small time step,i.e.,typically smaller than 10μs,is required owing to switching dynamics.However,in practice,harmonics should be continuously assessed with a long duration,e.g.,a day.A trade-off between accuracy and time efficiency thus exists.To address this issue,a multi-time scale modeling framework of fast-charging stations(FCSs)is proposed.In the presented framework,the DCFCs'input impedance and harmonic current emission in the ideal grid condition,that is,zero grid impedance and no background harmonic voltage,are obtained based on a converter switching model with a small timescale simulation.Since a DCFC's input impedance and harmonic current source are functions of the DCFC's load,the input impedance and harmonic emission at different loads are obtained.Thereafter,they are used in the fast-charging charging station modeling,where the DCFCs are simplified as Norton equivalent circuits.In the station level simulation,a large time step,i.e.,one minute,is used because the DCFCs'operating power can be assumed as a constant over a minute.With this co-simulation,the FCSs'long-term power quality performance can be assessed time-efficiently,without losing much accuracy.
基金This work was partially supported National High Technology R&D Program of China(863 Program)(No.2012AA050804).
文摘Electric vehicles(EVs)have received significant attention because of the potential energy savings and emission reductions they enable.However,current studies and demonstrations have focused mainly on specific technologies and equipment types,which cannot in themselves solve the predicaments facing EVs.This study points out that EVs will form a large,complex system that needs to be optimized over different aspects to compete with traditional vehicles.Therefore,wholesystem thinking is needed to support the development control of EVs,with a broader scope than operational control,and the core issue is the interaction between EVs and power grid,including their coordinated development and operational management.For development control of EVs,a target system and a step-wise optimization method are presented,as well as the basic principles for designing the target system.There are two key barriers in EVs’development:the research and mass production of highperformance power batteries,and the formulation of a favorable mechanism to capture benefits and encourage development.To address the problems of EV development,a promotion method that combines franchising with moderate competition is proposed.The concepts and methods developed in this study can facilitate the research and development of EVs.
