Improving smart charging prioritization by predicting electric vehicle departure time

O Frendo, N Gaertner… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Electric vehicles (EVs) are increasingly used for commuting to the workplace where
employees expect charging opportunities. Limited power supply in existing infrastructures …

Modeling of machine learning with SHAP approach for electric vehicle charging station choice behavior prediction

I Ullah, K Liu, T Yamamoto, M Zahid, A Jamal - Travel Behaviour and …, 2023 - Elsevier
Growing electric mobility makes it difficult for electric vehicles (EVs) to charge adequately
while charging infrastructure capacities are limited. Due to the prolonged charging times …

Probabilistic forecasts of time and energy flexibility in battery electric vehicle charging

J Huber, D Dann, C Weinhardt - Applied energy, 2020 - Elsevier
Users charging the batteries of their electric vehicles in an uncoordinated manner can
present energy systems with a challenge. One possible solution, smart charging, relies on …

Aggregated electric vehicle fast-charging power demand analysis and forecast based on LSTM neural network

M Chang, S Bae, G Cha, J Yoo - Sustainability, 2021 - mdpi.com
With the widespread use of electric vehicles, their charging power demand has increased
and become a significant burden on power grids. The uncoordinated deployment of electric …

A deep learning approach for prediction of electrical vehicle charging stations power demand in regulated electricity markets: The case of Morocco

M Boulakhbar, M Farag, K Benabdelaziz… - Cleaner Energy …, 2022 - Elsevier
The transport sector is a prominent source of increasing fuel consumption and greenhouse
gas (GHG) emissions. Electric vehicle (EV) is deemed an appealing solution for those …

Hybrid deep learning mechanism for charging control and management of Electric Vehicles

AK Venkitaraman, VSR Kosuru - European Journal of Electrical …, 2023 - ejece.org
In perspective of their environmental friendliness and energy efficiency, Electric Vehicles
(EVs) are posing a threat to traditional gasoline automobiles. Identifying the future charging …

Short-term load forecasting for electric vehicle charging stations based on deep learning approaches

J Zhu, Z Yang, Y Guo, J Zhang, H Yang - Applied sciences, 2019 - mdpi.com
Short-term load forecasting is a key task to maintain the stable and effective operation of
power systems, providing reasonable future load curve feeding to the unit commitment and …

Short-term electric vehicles charging load forecasting based on deep learning in low-quality data environments

X Shen, H Zhao, Y Xiang, P Lan, J Liu - Electric Power Systems Research, 2022 - Elsevier
The accurate prediction of electric vehicles (EVs) load is the research basis for evaluating
the impact of EVs on the power grid and optimizing the operation of the power grid …

Electric vehicles charging management using machine learning considering fast charging and vehicle-to-grid operation

M Shibl, L Ismail, A Massoud - Energies, 2021 - mdpi.com
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 …

EV idle time estimation on charging infrastructure, comparing supervised machine learning regressions

A Lucas, R Barranco, N Refa - Energies, 2019 - mdpi.com
The adoption of electric vehicles (EV) has to be complemented with the right charging
infrastructure roll-out. This infrastructure is already in place in many cities throughout the …