Optimal operation of energy hubs integrated with electric vehicles, load management, combined heat and power unit and renewable energy sources

2022 ◽  
Vol 48 ◽  
pp. 103822
Author(s):  
Ruihua Li ◽  
Sanam SaeidNahaei
Keyword(s):  
Renewable Energy ◽  
Power Unit ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Combined Heat And Power ◽  
Optimal Operation ◽  
Load Management ◽  
Energy Sources

Optimal operation of a multi-energy system considering renewable energy sources stochasticity and impacts of electric vehicles

Energy ◽  
2019 ◽  
Vol 186 ◽  
pp. 115841 ◽  
Author(s):  
Mustafa Ata ◽  
Ayşe Kübra Erenoğlu ◽  
İbrahim Şengör ◽  
Ozan Erdinç ◽  
Akın Taşcıkaraoğlu ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Optimal Operation ◽  
Energy Sources

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.

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