[HTML][HTML] Prediction of electric vehicles charging demand: A transformer-based deep learning approach

S Koohfar, W Woldemariam, A Kumar - Sustainability, 2023 - mdpi.com
Electric vehicles have been gaining attention as a cleaner means of transportation that is
low-carbon and environmentally friendly and can reduce greenhouse gas emissions and air …

[HTML][HTML] Performance comparison of deep learning approaches in predicting EV charging demand

S Koohfar, W Woldemariam, A Kumar - Sustainability, 2023 - mdpi.com
Electric vehicles (EVs) contribute to reducing fossil fuel dependence and environmental
pollution problems. However, due to complex charging behaviors and the high demand for …

[HTML][HTML] Seasonal electric vehicle forecasting model based on machine learning and deep learning techniques

HAI El-Azab, RA Swief, NH El-Amary, HK Temraz - Energy and AI, 2023 - Elsevier
In this paper, multiple featured machine learning algorithms and deep learning algorithms
are applied in forecasting the electric vehicles charging load profile from real datasets of …

Electric vehicle charging demand forecasting using deep learning model

Z Yi, XC Liu, R Wei, X Chen, J Dai - Journal of Intelligent …, 2022 - Taylor & Francis
Greenhouse gas (GHG) emission and excessive fuel consumption have become a pressing
issue nowadays. Particularly, CO2 emissions from transportation account for approximately …

[HTML][HTML] Deep learning LSTM recurrent neural network model for prediction of electric vehicle charging demand

J Shanmuganathan, AA Victoire, G Balraj, A Victoire - Sustainability, 2022 - mdpi.com
The immense growth and penetration of electric vehicles has become a major component of
smart transport systems; thereby decreasing the greenhouse gas emissions that pollute the …

Short-term electric vehicle charging demand prediction: A deep learning approach

S Wang, C Zhuge, C Shao, P Wang, X Yang, S Wang - Applied Energy, 2023 - Elsevier
Short-term prediction of the Electric Vehicle (EV) charging demand is of great importance to
the operation of EV fleets and charging stations. This paper develops a Long Short-Term …

[HTML][HTML] Using machine learning methods to predict electric vehicles penetration in the automotive market

S Afandizadeh, D Sharifi, N Kalantari… - Scientific Reports, 2023 - nature.com
Electric vehicles (EVs) have been introduced as an alternative to gasoline and diesel cars to
reduce greenhouse gas emissions, optimize fossil fuel use, and protect the environment …

[HTML][HTML] 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 …

Comparative analysis of deep learning models for electric vehicle charging load forecasting

MP Sasidharan, S Kinattingal, SP Simon - Journal of The Institution of …, 2023 - Springer
Grid-connected plug-in electric vehicle charging stations having integrated renewable
energy sources like photovoltaic (PV) systems with battery energy storage help manage the …

[HTML][HTML] 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 …