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 …

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 …

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 based approach for predicting the demand of electric vehicle charge

MD Eddine, Y Shen - The Journal of Supercomputing, 2022 - Springer
Predicting the demand for Electric Vehicle charging energy is essential to increase
utilization for the company, reduce costs for both car owners and the company and alleviate …

Electric vehicle charging load forecasting: A comparative study of deep learning approaches

J Zhu, Z Yang, M Mourshed, Y Guo, Y Zhou, Y Chang… - Energies, 2019 - mdpi.com
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 …

A novel LSTM based deep learning approach for multi-time scale electric vehicles charging load prediction

J Zhu, Z Yang, Y Chang, Y Guo, K Zhu… - 2019 IEEE Innovative …, 2019 - ieeexplore.ieee.org
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 …

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 …

Short-term load forecasting model of electric vehicle charging load based on MCCNN-TCN

J Zhang, C Liu, L Ge - Energies, 2022 - mdpi.com
The large fluctuations in charging loads of electric vehicles (EVs) make short-term
forecasting challenging. In order to improve the short-term load forecasting performance of …

Ensemble learning for charging load forecasting of electric vehicle charging stations

X Huang, D Wu, B Boulet - 2020 IEEE Electric Power and …, 2020 - ieeexplore.ieee.org
Electric vehicles (EVs) can help reduce the dependency on fossil oil and increasing
concerns on environmental pollution problems. However, due to the complex charging …

Deep-learning-based probabilistic forecasting of electric vehicle charging load with a novel queuing model

X Zhang, KW Chan, H Li, H Wang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
With the emerging electric vehicle (EV) and fast charging technologies, EV load forecasting
has become a concern for planners and operators of EV charging stations (CSs). Due to the …