Household EV charging demand prediction using machine and ensemble learning
S Ai, A Chakravorty, C Rong - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
The global popularization of electric vehicles (EVs) poses an opportunity for the construction
of micro-grid and smart community within energy internet on competent the massive and …
of micro-grid and smart community within energy internet on competent the massive and …
Transfer learning-based framework enhanced by deep generative model for cold-start forecasting of residential EV charging behavior
A Forootani, M Rastegar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reliable smart charging requires forecasting the charging behavior of EVs. Deep learning
algorithms could present a solution. However, deep neural networks (DNNs) require a large …
algorithms could present a solution. However, deep neural networks (DNNs) require a large …
Electric vehicle driver clustering using statistical model and machine learning
Electric Vehicle (EV) is playing a significant role in the distribution energy management
systems since the power consumption level of the EVs is much higher than the other regular …
systems since the power consumption level of the EVs is much higher than the other regular …
[HTML][HTML] Assessment of hybrid transfer learning method for forecasting EV profile and system voltage using limited EV charging data
The number of electric vehicles (EV) is increasing exponentially, significantly affecting the
planning and operation of future electricity grids, albeit the availability of EV data is very …
planning and operation of future electricity grids, albeit the availability of EV data is very …
User behavior clustering based method for EV charging forecast
The increasing adoption of electric vehicles poses new problems for the electrical
distribution network. For this reason, proper electric vehicle forecasting will be of …
distribution network. For this reason, proper electric vehicle forecasting will be of …
Prediction of EV charging behavior using machine learning
As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are
becoming increasingly popular for their contribution in reducing greenhouse gas emissions …
becoming increasingly popular for their contribution in reducing greenhouse gas emissions …
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 …
[HTML][HTML] Artificial deep neural network enables one-size-fits-all electric vehicle user behavior prediction framework
A Ahmadian, V Ghodrati, R Gadh - Applied Energy, 2023 - Elsevier
As greener mobility becomes the norm with the advent of electric vehicles (EVs), a natural
question arises: how big of a change are we seeing in terms of the stochastic energy …
question arises: how big of a change are we seeing in terms of the stochastic energy …
Ensemble learning for charging load forecasting of electric vehicle charging stations
Electric vehicles (EVs) can help reduce the dependency on fossil oil and increasing
concerns on environmental pollution problems. However, due to the complex charging …
concerns on environmental pollution problems. However, due to the complex charging …
Short-Term Forecasting of Electric Vehicle Load Using Time Series, Machine Learning, and Deep Learning Techniques
G Vishnu, D Kaliyaperumal, PB Pati, A Karthick… - World Electric Vehicle …, 2023 - mdpi.com
Electric vehicles (EVs) are inducing revolutionary developments to the transportation and
power sectors. Their innumerable benefits are forcing nations to adopt this sustainable …
power sectors. Their innumerable benefits are forcing nations to adopt this sustainable …