A hybrid electric vehicle load classification and forecasting approach based on GBDT algorithm and temporal convolutional network

T Zhang, Y Huang, H Liao, Y Liang - Applied Energy, 2023 - Elsevier
Due to the participation of large-scale electric vehicles (EVs) in Vehicle-to-Grid (V2G)
services, V2G dispatch centers need to predict the charging and discharging (C&D) loads of …

电动汽车充电站选址智能决策与优化研究综述.

魏冠元, 王冠群, 阮观梅, 耿娜 - Journal of Computer …, 2023 - search.ebscohost.com
电动汽车(electric vehicle, EV) 充电站的合理选址对推动EV 行业发展以及城市交通战略布局
具有重要作用. 通过系统梳理充电站选址智能决策和优化的相关文献, 为未来充电站选址规划 …

Learning-based demand-supply-coupled charging station location problem for electric vehicle demand management

Y Song, X Hu - Transportation Research Part D: Transport and …, 2023 - Elsevier
We present a learning-based, demand-supply-coupled optimization model for the charging
station location problem (CSLP), aiming to integrate the concept of electric vehicle (EV) …

A physics-informed graph learning approach for citywide electric vehicle charging demand prediction and pricing

H Kuang, H Qu, K Deng, J Li - Applied Energy, 2024 - Elsevier
A growing number of electric vehicles (EVs) is putting pressure on smart charging services.
As a foundation of informing drivers of vacant charging facilities and rationalizing pricing, an …

Optimal Charging Control of Electric Vehicle Fleets Based on Demand Aggregation and User-Oriented Disaggregation Respecting Data Privacy

F Gromann, AF Raab, K Strunz - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the share of electric vehicles in the transportation sector rising, solutions for their power
system and energy market integration are of increasing importance. In this context …

An urban charging load forecasting model based on trip chain model for private passenger electric vehicles cased study in Beijing

L Zhang, Z Huang, Z Wang, X Li, F Sun - Energy, 2024 - Elsevier
The rapid adoption of electric vehicles (EVs) has led to dramatic increase in charging
demands that poses great challenges for charging infrastructure. It is crucial to accurately …

GTFE-Net-BiLSTM-AM: An intelligent feature recognition method for natural gas pipelines

L Wang, C Hu, T Ma, Z Yang, W Guo, Z Mao… - Gas Science and …, 2024 - Elsevier
The recognition of pipeline features contributes to its safe management by preventing
severe consequences such as leakage resulting from bending deformation and denting …

Transfer learning based hybrid model for power demand prediction of large-scale electric vehicles

C Tian, Y Liu, G Zhang, Y Yang, Y Yan, C Li - Energy, 2024 - Elsevier
Accurately predicting the power demand of large-scale electric vehicles (EVs) is one of the
key tasks of power grid operation optimization. However, this task is difficult to complete due …

Equilibrium configuration strategy of vehicle-to-grid-based electric vehicle charging stations in low-carbon resilient distribution networks

Z Wang, L Zhang, W Tang, Z Ma, J Huang - Applied Energy, 2024 - Elsevier
Distribution networks (DNs) are under severe requirements of security and ecology, such as
maintaining continuous power supply for critical loads under extreme disasters and …

A data-driven approach to urban charging facility expansion based on bi-level optimization: A case study in a Chinese city

J Cao, Y Han, N Pan, J Zhang, J Yang - Energy, 2024 - Elsevier
This paper addresses the optimization of urban charging facilities expansion in response to
the growing charging demand and proposes a data-driven bi-level optimization framework …