Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load

K Liu, Y Liu - Applied Energy, 2023 - Elsevier
As the number of electric vehicles (EVs) connected to the grid increases, the EV electricity
demand rises dramatically, affecting the grid's planning and operation and deepening the …

Deep stochastic reinforcement learning-based energy management strategy for fuel cell hybrid electric vehicles

B Jouda, AJ Al-Mahasneh, MA Mallouh - Energy Conversion and …, 2024 - Elsevier
Fuel cell hybrid electric vehicles offer a promising solution for sustainable and environment
friendly transportation, but they necessitate efficient energy management strategies (EMSs) …

[HTML][HTML] A data-aided robust approach for bottleneck identification in power transmission grids for achieving transportation electrification ambition: a case study in New …

Q Zhang, YS Liu, HO Gao, F You - Advances in Applied Energy, 2024 - Elsevier
As the enthusiasm for electric vehicles passes the range anxiety and other tests, large-scale
transportation electrification becomes a prominent topic in research and policy discussions …

Predictive Model for EV Charging Load Incorporating Multimodal Travel Behavior and Microscopic Traffic Simulation

H Bian, Q Ren, Z Guo, C Zhou, Z Zhang, X Wang - Energies, 2024 - mdpi.com
A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is
proposed in this paper, considering multimodal travel behavior and microscopic traffic …

MPC-driven optimal scheduling of grid-connected microgrid: Cost and degradation minimization with PEVs integration

A Nawaz, D Wang, A Mahmoudi, MQ Khan… - Electric Power Systems …, 2025 - Elsevier
The lifespan and degradation of energy storage systems are important factors in ensuring
efficient energy management and reducing operational costs in microgrids. This paper …

A distributed week-ahead scheduling method for the charging/discharging of plug-in electric vehicles integrated into the grid

Y Cui, Z Hu, Y Wan, J Li, C Shao… - CSEE Journal of …, 2024 - ieeexplore.ieee.org
With the proliferation of electric vehicles (EVs) around the world, the large-scale grid-vehicle
interaction (GVI) has become more and more promising recently. However, the existing …

Performance Analysis of EV Battery Based on Trip Chain Model

R Poojitha, S Lekshmi - 2024 10th International Conference on …, 2024 - ieeexplore.ieee.org
Electric Vehicle (EV) batteries are crucial for sustainable way of transportation and
understanding their performance. In this paper, a Novel method called Trip Chain Model …

Economic Indicator-Based Power Quality Assessment of Distribution Network Incorporating Electric Vehicle Stations

S Shi, Y Liu, Q Wang, B Cen - 2024 14th International …, 2024 - ieeexplore.ieee.org
The access of electric vehicle charging stations (EVCS) brings challenges to the stable
operation of the distribution network. At present, there is a lack of indicator to quantify the …

Forecasting the Flexibility Potential of Electric Vehicles Limited by Individual Charging Targets

NL Fischer, K Rudion - 2023 IEEE PES Innovative Smart Grid …, 2023 - ieeexplore.ieee.org
The future massive integration of electric vehicles into the grid represents not only an
additional load, but also a decentralized flexible resource that can be used in aggregated …

Predictive analysis of load at EVCS with deep learning algorithms

S Singh, U Nangia, NK Jain - 2024 2nd International …, 2024 - ieeexplore.ieee.org
This paper considers Electric vehicle charging station (EVCS) as load and predicts the total
charging power demand of an EVCS with deep learning algorithms. For pragmatic approach …