Review of optimized layout of electric vehicle charging infrastructures

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.

Role of government subsidies in the new energy vehicle charging infrastructure industry:a three-party game perspective

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.

Charging infrastructure planning for electric vehicle in India:Present status and future challenges

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.

Reliability of electric vehicle charging infrastructure:A cross-lingual deep learning approach

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.

A Review on Electric Vehicle Charging Infrastructure Development in the UK

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.

An Electricity Demand-Based Planning of Electric Vehicle Charging Infrastructure

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.

Public Charging Infrastructure in Germany–A Utilization and Profitability Analysis

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.

A joint model of infrastructure planning and smart charging strategies for shared electric vehicles

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.

Research on dynamic matching model of electric vehicles and charging facilities in China:A case study of taxis in Beijing

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.

Opportunity Cost Model of Infrastructure Access Charges for Chinese Railways

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.

Python Supervised Co-simulation for a Day-long Harmonic Evaluation of EV Charging

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.

Whole-system thinking, development control, key barriers and promotion mechanism for EV development

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.