Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power
grid as it avoids distribution system overloads, increases power quality, and decreases …
grid as it avoids distribution system overloads, increases power quality, and decreases …
Electric vehicles charging management using machine learning considering fast charging and vehicle-to-grid operation
Electric vehicles (EVs) have gained in popularity over the years. The charging of a high
number of EVs harms the distribution system. As a result, increased transformer overloads …
number of EVs harms the distribution system. As a result, increased transformer overloads …
Review on scheduling, clustering, and forecasting strategies for controlling electric vehicle charging: Challenges and recommendations
The usage and adoption of electric vehicles (EVs) have increased rapidly in the 21st century
due to the shifting of the global energy demand away from fossil fuels. The market …
due to the shifting of the global energy demand away from fossil fuels. The market …
Machine learning approaches for EV charging behavior: A review
As the smart city applications are moving from conceptual models to development phase,
smart transportation is one of smart cities applications and it is gaining ground nowadays …
smart transportation is one of smart cities applications and it is gaining ground nowadays …
Demand-side management using deep learning for smart charging of electric vehicles
KL López, C Gagné, MA Gardner - IEEE Transactions on Smart …, 2018 - ieeexplore.ieee.org
The use of electric vehicles (EVs) load management is relevant to support electricity demand
softening, making the grid more economic, efficient, and reliable. However, the absence of …
softening, making the grid more economic, efficient, and reliable. However, the absence of …
Data-driven framework for large-scale prediction of charging energy in electric vehicles
Large-scale and high-precision predictions of the charging energy required for electric
vehicles (EVs) are essential to ensure the safety of EVs and provide reliable inputs for grid …
vehicles (EVs) are essential to ensure the safety of EVs and provide reliable inputs for grid …
Reinforcement learning based EV charging management systems–a review
HM Abdullah, A Gastli, L Ben-Brahim - IEEE Access, 2021 - ieeexplore.ieee.org
To mitigate global warming and energy shortage, integration of renewable energy
generation sources, energy storage systems, and plug-in electric vehicles (PEVs) have been …
generation sources, energy storage systems, and plug-in electric vehicles (PEVs) have been …
Electric vehicle charging system in the smart grid using different machine learning methods
Smart cities require the development of information and communication technology to
become a reality (ICT). A “smart city” is built on top of a “smart grid”. The implementation of …
become a reality (ICT). A “smart city” is built on top of a “smart grid”. The implementation of …
Data-driven charging demand prediction at public charging stations using supervised machine learning regression methods
Plug-in Electric Vehicle (PEV) user charging behavior has a significant influence on a
distribution network and its reliability. Generally, monitoring energy consumption has …
distribution network and its reliability. Generally, monitoring energy consumption has …
[HTML][HTML] Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation
EVs are becoming more popular and widely used worldwide due to their environmentally
friendliness as part of the world efforts to decrease the effects of climate change. Moreover …
friendliness as part of the world efforts to decrease the effects of climate change. Moreover …