Multiple Energy Sources Hybridization: The Future of Electric Vehicles?

Traditional distributed power sources are usually natural energy sources, their output power is not stable and difficult to join up to the grid. Battery electric vehicles(BEV) based on V2G technique is a new kind of Distributed Generation(DG). This paper introduces a V2G technique. A V2G-based BEV could be used to realize load shifting and stabilize the disturbance for DG's joining up with the grid. Many countries started researching V2G technique and in China NARI Group Corporation and Xuji Group Corporation have researched and started manufacturing practical V2G device. This paper also shows the main principle of V2G and its application in China, concludes its advantages and analyzes its development in the future.

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Review for "Impact of optimal integration of renewable energy sources and electric vehicles in practical distribution feeder with uncertain load demand"

10.1002/2050-7038.12668/v2/review2 ◽

2020 ◽

Keyword(s):

Renewable Energy ◽

Electric Vehicles ◽

Renewable Energy Sources ◽

Energy Sources ◽

Load Demand ◽

Optimal Integration ◽

Distribution Feeder

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Decision letter for "Impact of optimal integration of renewable energy sources and electric vehicles in practical distribution feeder with uncertain load demand"

10.1002/2050-7038.12668/v2/decision1 ◽

2020 ◽

Keyword(s):

Renewable Energy ◽

Electric Vehicles ◽

Renewable Energy Sources ◽

Energy Sources ◽

Load Demand ◽

Optimal Integration ◽

Distribution Feeder

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

International Journal of Emerging Electric Power Systems ◽

10.1515/ijeeps-2019-0270 ◽

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.

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Electric Mobility in Cities: The Case of Vienna

Energies ◽

10.3390/en14010217 ◽

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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