Model-free real-time EV charging scheduling based on deep reinforcement learning
Driven by the recent advances in electric vehicle (EV) technologies, EVs have become
important for smart grid economy. When EVs participate in demand response program which …
important for smart grid economy. When EVs participate in demand response program which …
A deep learning based approach for predicting the demand of electric vehicle charge
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 …
utilization for the company, reduce costs for both car owners and the company and alleviate …
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 …
has become a concern for planners and operators of EV charging stations (CSs). Due to the …
Predictive scheduling framework for electric vehicles with uncertainties of user behaviors
B Wang, Y Wang, H Nazaripouya, C Qiu… - IEEE Internet of …, 2016 - ieeexplore.ieee.org
The randomness of user behaviors plays a significant role in electric vehicle (EV) scheduling
problems, especially when the power supply for EV supply equipment (EVSE) is limited …
problems, especially when the power supply for EV supply equipment (EVSE) is limited …
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 …
[HTML][HTML] 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 …
[HTML][HTML] Synthetic data generator for electric vehicle charging sessions: modeling and evaluation using real-world data
Electric vehicle (EV) charging stations have become prominent in electricity grids in the past
few years. Their increased penetration introduces both challenges and opportunities; they …
few years. Their increased penetration introduces both challenges and opportunities; they …
[HTML][HTML] Data-driven charging demand prediction at public charging stations using supervised machine learning regression methods
Plug-in Electric Vehicle (PEV) user charging behavior has a significant influence on a
distribution network and its reliability. Generally, monitoring energy consumption has …
distribution network and its reliability. Generally, monitoring energy consumption has …
[HTML][HTML] Prediction of electric vehicles charging demand: A transformer-based deep learning approach
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 …
low-carbon and environmentally friendly and can reduce greenhouse gas emissions and air …
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 …