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 …
A novel LSTM based deep learning approach for multi-time scale electric vehicles charging load prediction
Short-term load forecasting is an important issue in energy management system and a key
measure to maintain the stable and effective operation of power systems, providing …
measure to maintain the stable and effective operation of power systems, providing …
Electric vehicle charging load forecasting: A comparative study of deep learning approaches
Load forecasting is one of the major challenges of power system operation and is crucial to
the effective scheduling for economic dispatch at multiple time scales. Numerous load …
the effective scheduling for economic dispatch at multiple time scales. Numerous load …
Short-term load forecasting for electric vehicle charging stations based on deep learning approaches
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 …
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 …
the impact of EVs on the power grid and optimizing the operation of the power grid …
Using bayesian deep learning for electric vehicle charging station load forecasting
D Zhou, Z Guo, Y Xie, Y Hu, D Jiang, Y Feng, D Liu - Energies, 2022 - mdpi.com
In recent years, replacing internal combustion engine vehicles with electric vehicles has
been a significant option for supporting reducing carbon emissions because of fossil fuel …
been a significant option for supporting reducing carbon emissions because of fossil fuel …
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 …
Probabilistic electric vehicle charging demand forecast based on deep learning and machine theory of mind
Electric Vehicles (EVs) and corresponding charging stations have been widely popularized,
increasing the power grid's operational risk and pressure, especially for the distribution …
increasing the power grid's operational risk and pressure, especially for the distribution …
Probabilistic charging power forecast of EVCS: Reinforcement learning assisted deep learning approach
The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely
deployed with the development of large-scale transportation electrifications. However, since …
deployed with the development of large-scale transportation electrifications. However, since …
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 …
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