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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

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Showing 1-25 of 45 citing articles:

Spatial-temporal load prediction of electric bus charging station based on S2TAT
Guangnian Xiao, Hailin Tong, Yaqing Shu, et al.
International Journal of Electrical Power & Energy Systems (2025) Vol. 164, pp. 110446-110446
Closed Access | Times Cited: 8
A systematic methodology for mid-and-long term electric vehicle charging load forecasting: The case study of Shenzhen, China
Yanchong Zheng, Ziyun Shao, Yumeng Zhang, et al.
Sustainable Cities and Society (2020) Vol. 56, pp. 102084-102084
Closed Access | Times Cited: 105
Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach
Yuanzheng Li, Shangyang He, Yang Li, et al.
IEEE Transactions on Intelligent Vehicles (2022) Vol. 8, Iss. 1, pp. 344-357
Open Access | Times Cited: 65
Current status, challenges, and prospects of data-driven urban energy modeling: A review of machine learning methods
Prajowal Manandhar, Hasan Rafiq, Edwin Rodríguez-Ubiñas
Energy Reports (2023) Vol. 9, pp. 2757-2776
Open Access | Times Cited: 30
FMGCN: Federated Meta Learning-Augmented Graph Convolutional Network for EV Charging Demand Forecasting
Linlin You, Q Chen, Haohao Qu, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 14, pp. 24452-24466
Closed Access | Times Cited: 8
Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation
Jean-Michel Clairand, Javier Rodríguez-García, Carlos Álvarez-Bel
Energies (2018) Vol. 11, Iss. 11, pp. 3188-3188
Open Access | Times Cited: 63
Assessing transport emissions reduction while increasing electric vehicles and renewable generation levels
Paula Bastida-Molina, Elías Hurtado-Pérez, Elisa Peñalvo López, et al.
Transportation Research Part D Transport and Environment (2020) Vol. 88, pp. 102560-102560
Open Access | Times Cited: 59
Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies
Jean-Michel Clairand, Paulo Guerra-Terán, Xavier Serrano-Guerrero, et al.
Energies (2019) Vol. 12, Iss. 16, pp. 3114-3114
Open Access | Times Cited: 58
Modeling Energy Demand—A Systematic Literature Review
Paul Verwiebe, Stephan Seim, Simon Burges, et al.
Energies (2021) Vol. 14, Iss. 23, pp. 7859-7859
Open Access | Times Cited: 51
A comprehensive scheduling model for electric vehicles in office buildings considering the uncertainty of charging load
Yan Ding, Yan Zhu, Qiaochu Wang, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 151, pp. 109154-109154
Closed Access | Times Cited: 17
Short‐term load forecasting at electric vehicle charging sites using a multivariate multi‐step long short‐term memory: A case study from Finland
Tim Unterluggauer, Kalle Rauma, Pertti Järventausta, et al.
IET Electrical Systems in Transportation (2021) Vol. 11, Iss. 4, pp. 405-419
Open Access | Times Cited: 33
Smart Charging: A Comprehensive Review
Sanchari Deb, Mikko Pihlatie, Mohammed Al-Saadi
IEEE Access (2022) Vol. 10, pp. 134690-134703
Open Access | Times Cited: 23
Mid- and long-term strategy based on electric vehicle charging unpredictability and ownership estimation
Hui Hwang Goh, Lian Zong, Dongdong Zhang, et al.
International Journal of Electrical Power & Energy Systems (2022) Vol. 142, pp. 108240-108240
Closed Access | Times Cited: 22
Deep Learning Based on Multi-Decomposition for Short-Term Load Forecasting
Seon Hyeog Kim, Gyul Lee, Gu-Young Kwon, et al.
Energies (2018) Vol. 11, Iss. 12, pp. 3433-3433
Open Access | Times Cited: 41
Electric Bus Scheduling and Timetabling, Fast Charging Infrastructure Planning, and Their Impact on the Grid: A Review
Kayhan Alamatsaz, Sadam Hussain, Chunyan Lai, et al.
Energies (2022) Vol. 15, Iss. 21, pp. 7919-7919
Open Access | Times Cited: 20
A charging station planning model considering electric bus aggregators
Jean-Michel Clairand, Mario González, Irvin Cedeño, et al.
Sustainable Energy Grids and Networks (2022) Vol. 30, pp. 100638-100638
Open Access | Times Cited: 19
An improved Wolf pack algorithm for optimization problems: Design and evaluation
Xuan Chen, Feng Cheng, Cong Liu, et al.
PLoS ONE (2021) Vol. 16, Iss. 8, pp. e0254239-e0254239
Open Access | Times Cited: 21
Prediction of Charging Demand of Electric City Buses of Helsinki, Finland by Random Forest
Sanchari Deb, Xiao‐Zhi Gao
Energies (2022) Vol. 15, Iss. 10, pp. 3679-3679
Open Access | Times Cited: 15
Factor analysis and carbon price prediction based on empirical mode decomposition and least squares support vector machine optimized by improved particle swarm optimization
Wei Sun, Yawen Wang
Carbon Management (2020) Vol. 11, Iss. 3, pp. 315-329
Closed Access | Times Cited: 22
Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart Cities
Fayez Alanazi, Talal Obaid Alshammari, Abdelhalim Azam
Sustainability (2023) Vol. 15, Iss. 22, pp. 16030-16030
Open Access | Times Cited: 7
Clustered multi-node learning of electric vehicle charging flexibility
Mostafa Gilanifar, Masood Parvania
Applied Energy (2020) Vol. 282, pp. 116125-116125
Closed Access | Times Cited: 20
Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China
Jian Chen, Fangyi Li, Ranran Yang, et al.
Energies (2020) Vol. 13, Iss. 17, pp. 4387-4387
Open Access | Times Cited: 16
Transit electrification state of the art: A machine-learning based text mining approach
Gamal Eldeeb, Moataz Mohamed
Transportation Research Part D Transport and Environment (2022) Vol. 111, pp. 103446-103446
Closed Access | Times Cited: 10
Analysis of Different Neural Networks and a New Architecture for Short-Term Load Forecasting
Lintao Yang, Yang Hong-geng
Energies (2019) Vol. 12, Iss. 8, pp. 1433-1433
Open Access | Times Cited: 17
Combined forecasting system for short‐term bus load forecasting based on clustering and neural networks
Ioannis P. Panapakidis, Nikolaos Skiadopoulos, Georgios C. Christoforidis
IET Generation Transmission & Distribution (2020) Vol. 14, Iss. 18, pp. 3652-3664
Open Access | Times Cited: 13
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