scholarly journals Studying the Formation of the Charging Session Number at Public Charging Stations for Electric Vehicles

2020 ◽  
Vol 12 (14) ◽  
pp. 5571
Author(s):  
Anastasia Gorbunova ◽  
Ilya Anisimov ◽  
Elena Magaril
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Electric Energy ◽  
Hydrocarbon Fuel ◽  
Energy System ◽  
Road Transport ◽  
Preliminary Calculation ◽  
Charging Infrastructure ◽  
Charging Stations

The energy industry is a leader of introduction and development of energy supply technologies from renewable energy sources. However, there are some disadvantages of these energy systems, namely, the low density and inconsistent nature of the energy input, which leads to an increase in the cost of the produced electric energy in comparison to the traditional energy complexes using hydrocarbon fuel resources. Therefore, the smart grid technology based on preliminary calculation parameters of the energy system develops in cities. This area should also be used to organize the charging infrastructure of electric vehicles, as the electrification of road transport is one of the global trends. As a result, a current task of the transport and energy field is the development of scientifically based approaches to the formation of the urban charging infrastructure for electric vehicles. The purpose of the article is to identify the features of the application flow formation for the charge of the electric vehicle battery. The results obtained provide a basis for building a simulation model for determining the required number of charging stations in the city, taking into account the criteria of minimizing operating costs for electric vehicle owners and energy companies.

Feasibility Study of Renewable Energy Integrated Electric Vehicle Charging Infrastructure

2016 ◽  
pp. 313-349
Author(s):  
Azhar Ul-Haq ◽  
Marium Azhar
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Area Network ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

This chapter presents a detailed study of renewable energy integrated charging infrastructure for electric vehicles (EVs) and discusses its various aspects such as siting requirements, standards of charging stations, integration of renewable energy sources for powering up charging stations and interfacing devices between charging facilities and smart grid. A smart charging station for EVs is explained along with its essential components and different charging methodologies are explained. It has been recognized that the amalgamation of electric vehicles in the transportation sector will trigger power issues due to the mobility of vehicles beyond the stretch of home area network. In this regard an information and communication technology (ICT) based architecture may support EVs management with an aim to enhance the electric vehicle charging and energy storage capabilities with the relevant considerations. An ICT based solution is capable of monitoring the state of charge (SOC) of EV batteries, health and accessible amount of energy along with the mobility of EVs.

Feasibility Study of Renewable Energy Integrated Electric Vehicle Charging Infrastructure

2020 ◽  
pp. 158-194
Author(s):  
Azhar Ul-Haq ◽  
Marium Azhar
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Area Network ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

This chapter presents a detailed study of renewable energy integrated charging infrastructure for electric vehicles (EVs) and discusses its various aspects such as siting requirements, standards of charging stations, integration of renewable energy sources for powering up charging stations and interfacing devices between charging facilities and smart grid. A smart charging station for EVs is explained along with its essential components and different charging methodologies are explained. It has been recognized that the amalgamation of electric vehicles in the transportation sector will trigger power issues due to the mobility of vehicles beyond the stretch of home area network. In this regard an information and communication technology (ICT) based architecture may support EVs management with an aim to enhance the electric vehicle charging and energy storage capabilities with the relevant considerations. An ICT based solution is capable of monitoring the state of charge (SOC) of EV batteries, health and accessible amount of energy along with the mobility of EVs.

scholarly journals Simulation of Future Electric Vehicle Charging Behavior—Effects of Transition from PHEV to FEV

2019 ◽  
Vol 10 (2) ◽  
pp. 42 ◽  
Author(s):  
Igna Vermeulen ◽  
Jurjen Rienk Helmus ◽  
Mike Lees ◽  
Robert van den Hoed
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Early Years ◽  
Charging Infrastructure ◽  
Agent Based ◽  
Electric Vehicle Charging ◽  
Subsidy Scheme ◽  
Infrastructure Performance ◽  
Charging Stations

The Netherlands is a frontrunner in the field of public charging infrastructure, having one of the highest number of public charging stations per electric vehicle (EV) in the world. During the early years of adoption (2012–2015), a large percentage of the EV fleet were plugin hybrid electric vehicles (PHEV) due to the subsidy scheme at that time. With an increasing number of full electric vehicles (FEVs) on the market and a current subsidy scheme for FEVs only, a transition of the EV fleet from PHEV to FEV is expected. This is hypothesized to have an effect on the charging behavior of the complete fleet, and is reason to understand better how PHEVs and FEVs differ in charging behavior and how this impacts charging infrastructure usage. In this paper, the effects of the transition of PHEV to FEV is simulated by extending an existing agent-based model. Results show important effects of this transition on charging infrastructure performance.

scholarly journals Determinants of Electric Vehicle Diffusion in China

2021 ◽  
Author(s):  
Martin Kalthaus ◽  
Jiatang Sun
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Central Government ◽  
License Plate ◽  
Panel Estimation ◽  
Charging Infrastructure ◽  
Electric Cars ◽  
Local Air Pollution ◽  
Charging Stations ◽  
Positive Effect

AbstractWe analyze the effect of four determinants of electric vehicle diffusion in China for a panel of 31 regions for the period 2010–2016. We analyze diffusion of four different electric vehicle types, namely battery electric cars and buses as well as plug-in hybrid electric cars and buses. System GMM panel estimation results show that total monetary subsidies have a positive effect only on the diffusion of battery electric cars. A closer look reveals that subsidies provided by regional governments are decisive for all types of vehicles but the subsidy provided by the central government and its degression over time dilute the overall effect of subsidies and is partly detrimental. Non-monetary ownership policies, such as license-plate lotteries, show a positive effect only for battery electric cars. Availability of public charging infrastructure increases diffusion of all vehicle types. Charging points are relevant for cars, while charging stations are especially decisive for the diffusion of electric buses. Using local environmental conditions as a novel determinant for the diffusion of electric vehicles reveals that the local air pollution influences the diffusion of buses, but not of cars.

scholarly journals Assessment of the Use of Renewable Energy Sources for the Charging Infrastructure of Electric Vehicles

2020 ◽  
Vol 4 (6) ◽  
pp. 539-550
Author(s):  
A. D. Gorbunova ◽  
I. A. Anisimov
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Energy Supply ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Charging Infrastructure ◽  
Smart Charging ◽  
Charging Stations ◽  
The City

Application of renewable energy sources is a relevant area of energy supply for urban infrastructure. In 2019, the share of energy produced by such sources reached 11% (for solar energy) and 22% (for wind energy) of the total energy produced during the year. However, these systems require an improvement in their efficiency that can be achieved by introducing electric vehicles. They can accumulate, store and transfer surplus energy to the city’s power grid. A solution to this problem is a smart charging infrastructure. The existing studies in the field of charging infrastructure organization for electric vehicles consider only models locating charging stations in the city or the calculation of their required number. These calculations are based on socio-economic factors and images of a potential owner of an electric vehicle. Therefore, the aim of this study is to develop a methodology for determining the location of charging stations and their required number. The calculation will include the operating features of the existing charging infrastructure, which has not been done before. Thus, the purpose of this article is to research the operation of the existing charging infrastructure. This will provide an opportunity to develop approaches to the energy supply of charging infrastructure and city’s power grid from renewable energy sources. The article presents an analysis of data on the number of charging sessions during the year, month and day. This data enable us to construct curves of the charging session number and suggest ways to conduct the next stages of this study. Doi: 10.28991/esj-2020-01251 Full Text: PDF

scholarly journals Electric Vehicle and its Types

2021 ◽  
Vol 9 (VII) ◽  
pp. 3553-3555
Author(s):  
P. M. Tripathi
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fossil Fuels ◽  
Hybrid Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Additional Energy ◽  
Charging Infrastructure ◽  
Hybrid Electric ◽  
The Impact

Electric vehicles are an important option for reducing greenhouse gas emissions. Electric vehicles not only reduce dependence on fossil fuels, but also reduce the impact of ozone-depleting substances and promote widespread adoption of renewable energies. Despite extensive research into the properties and characteristics of electric vehicles as well as the nature of their charging infrastructure, electric vehicle construction and grid modeling continue to evolve and become limited. regime. This paper presents market penetration surveys for electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles and battery electric vehicles, and describes optimal engineering and modeling approaches. their differences. Research on critical barriers and inadequate charging equipment targets developing countries like India, which makes the study unique. The development of the new Vehicle to Grid concept has created additional energy sources when renewable energy sources are not available. We conclude that considering the specific characteristics of an electric vehicle is important in the mobility of the electric vehicle.

scholarly journals A Novel Distributed System of e-Vehicle Charging Stations Based on Pumps as Turbine to Support Sustainable Micromobility

2021 ◽  
Vol 13 (4) ◽  
pp. 1847
Author(s):  
Gabriella Balacco ◽  
Mario Binetti ◽  
Leonardo Caggiani ◽  
Michele Ottomanelli
Keyword(s):  
Electric Vehicles ◽  
Water Distribution ◽  
Water Pressure ◽  
Renewable Energy Sources ◽  
Water Distribution Network ◽  
Electrical Energy ◽  
Road Transport ◽  
Optimal Number ◽  
Point Of View ◽  
Charging Stations

Recent statistics shows that CO2 emissions from road transport have been increasing. In addition, the paradigm of “more electric vehicles” does not seem to be positive from the environmental point of view. In fact, assuming the current energy mix system, studies focusing on Life Cycle Assessment and Well-To-Wheels analysis demonstrate that electric vehicles are less eco-friendly than traditional internal combustion-based engines. Then, it is mandatory to shift toward renewable energy sources to produce electricity with less CO2 emission. In this work, it is proposed to use a new e-vehicles charging system based on Pumps used as Turbine (PATs). This system uses the pressure in excess that could be available in a water distribution network (WDN). Such an excess of pressure is usually destroyed by pressure-reducing valves with the aim to reduce water leaks. PATs are also able to reduce water pressure and produce electrical energy that can be supplied to e-vehicles charging stations. Then, a bi-level methodology to design and optimize the e-charging stations system for (individual or shared) e-bikes and/or e-scooters is proposed. The method allows determining the optimal number of e-vehicles, charging stations docks, and PATs on the study area according to the WDN layout and hydraulic properties as well as the road network characteristics and demand of e-vehicles. The potential of the methodology is shown by an application to a real case study.

Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohamad Nassereddine
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Power Network ◽  
Network Stability ◽  
Fast Charging ◽  
Electrical Loads ◽  
Charging Stations

AbstractRenewable energy sources are widely installed across countries. In recent years, the capacity of the installed renewable network supports large percentage of the required electrical loads. The relying on renewable energy sources to support the required electrical loads could have a catastrophic impact on the network stability under sudden change in weather conditions. Also, the recent deployment of fast charging stations for electric vehicles adds additional load burden on the electrical work. The fast charging stations require large amount of power for short period. This major increase in power load with the presence of renewable energy generation, increases the risk of power failure/outage due to overload scenarios. To mitigate the issue, the paper introduces the machine learning roles to ensure network stability and reliability always maintained. The paper contains valuable information on the data collection devises within the power network, how these data can be used to ensure system stability. The paper introduces the architect for the machine learning algorithm to monitor and manage the installed renewable energy sources and fast charging stations for optimum power grid network stability. Case study is included.

scholarly journals Electric Mobility in Cities: The Case of Vienna

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 217
Author(s):  
Amela Ajanovic ◽  
Marina Siebenhofer ◽  
Reinhard Haas
Keyword(s):  
Electric Vehicles ◽  
Future Development ◽  
Urban Areas ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Road Transport ◽  
Electric Mobility ◽  
Policy Framework ◽  
The Future ◽  
Historical Developments

Environmental problems such as air pollution and greenhouse gas emissions are especially challenging in urban areas. Electric mobility in different forms may be a solution. While in recent years a major focus was put on private electric vehicles, e-mobility in public transport is already a very well-established and mature technology with a long history. The core objective of this paper is to analyze the economics of e-mobility in the Austrian capital of Vienna and the corresponding impact on the environment. In this paper, the historical developments, policy framework and scenarios for the future development of mobility in Vienna up to 2030 are presented. A major result shows that in an ambitious scenario for the deployment of battery electric vehicles, the total energy demand in road transport can be reduced by about 60% in 2030 compared to 2018. The major conclusion is that the policies, especially subsidies and emission-free zones will have the largest impact on the future development of private and public e-mobility in Vienna. Regarding the environmental performance, the most important is to ensure that a very high share of electricity used for electric mobility is generated from renewable energy sources.

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