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OpenAlex Citation Counts

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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.

Requested Article:

A generalizable and sensor-independent deep learning method for fault detection and location in low-voltage distribution grids
Nikolaos Sapountzoglou, Jesus Lago, Bart De Schutter, et al.
Applied Energy (2020) Vol. 276, pp. 115299-115299
Open Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

A Review of Graph Neural Networks and Their Applications in Power Systems
Wenlong Liao, Birgitte Bak‐Jensen, Jayakrishnan Radhakrishna Pillai, et al.
Journal of Modern Power Systems and Clean Energy (2022) Vol. 10, Iss. 2, pp. 345-360
Open Access | Times Cited: 181
A Comprehensive Review on Smart Grids: Challenges and Opportunities
Jesús Jaime Moreno Escobar, Oswaldo Morales Matamoros, Ricardo Tejeida Padilla, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 6978-6978
Open Access | Times Cited: 105
Artificial intelligence integrated grid systems: Technologies, potential frameworks, challenges, and research directions
Md Morshed Alam, M. J. Hossain, Md Ahasan Habib, et al.
Renewable and Sustainable Energy Reviews (2025) Vol. 211, pp. 115251-115251
Open Access | Times Cited: 2
A review of fault location and classification methods in distribution grids
Paschalia Stefanidou-Voziki, Nikolaos Sapountzoglou, Bertrand Raison, et al.
Electric Power Systems Research (2022) Vol. 209, pp. 108031-108031
Closed Access | Times Cited: 60
Cyber-Resilient Smart Cities: Detection of Malicious Attacks in Smart Grids
Mostafa Mohammadpourfard, Abdullah Khalili, İstemihan Genç, et al.
Sustainable Cities and Society (2021) Vol. 75, pp. 103116-103116
Closed Access | Times Cited: 55
Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations
Qi Liu, Bo Yang, Zhaojian Wang, et al.
IEEE Transactions on Network Science and Engineering (2022) Vol. 9, Iss. 3, pp. 1680-1696
Open Access | Times Cited: 38
Deep learning-based application for fault location identification and type classification in active distribution grids
Vasilis Rizeakos, Athanasios Bachoumis, N. Andriopoulos, et al.
Applied Energy (2023) Vol. 338, pp. 120932-120932
Closed Access | Times Cited: 27
Fault classification and location of a PMU-equipped active distribution network using deep convolution neural network (CNN)
Md. Nazrul Islam Siddique, Md Shafiullah, Saad Mekhilef, et al.
Electric Power Systems Research (2024) Vol. 229, pp. 110178-110178
Open Access | Times Cited: 13
The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review
Moamin A. Mahmoud, Naziffa Raha Md Nasir, Mathuri Gurunathan, et al.
Energies (2021) Vol. 14, Iss. 16, pp. 5078-5078
Open Access | Times Cited: 48
Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems
Bang Le-Huy Nguyen, Tuyen Vu, Thai-Thanh Nguyen, et al.
IEEE Access (2023) Vol. 11, pp. 46039-46050
Open Access | Times Cited: 20
Review on Artificial Intelligence-Based Fault Location Methods in Power Distribution Networks
Hamed Rezapour, S. Jamali, Alireza Bahmanyar
Energies (2023) Vol. 16, Iss. 12, pp. 4636-4636
Open Access | Times Cited: 19
Faulty feeder detection based on transient attenuation and waveform similarity for low-resistance grounded system
Jiandong Duan, Jinxuan Jiang, Wanying Yan, et al.
International Journal of Electrical Power & Energy Systems (2025) Vol. 165, pp. 110484-110484
Closed Access
The impact of improved PCA method based on anomaly detection on chiller sensor fault detection
Aosong Liang, Yunpeng Hu, Guannan Li
International Journal of Refrigeration (2023) Vol. 155, pp. 184-194
Closed Access | Times Cited: 13
Visual inspection of fault type and zone prediction in electrical grids using interpretable spectrogram-based CNN modeling
Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, et al.
Expert Systems with Applications (2022) Vol. 210, pp. 118368-118368
Closed Access | Times Cited: 18
Fault classification in power distribution systems based on limited labeled data using multi-task latent structure learning
Mostafa Gilanifar, Hui Wang, Jose Cordova, et al.
Sustainable Cities and Society (2021) Vol. 73, pp. 103094-103094
Open Access | Times Cited: 23
Artificial Intelligence Based Fault Detection and Classification in Power Systems: An Automated Machine Learning Approach
Tarik Hubana, Migdat Hodžić
(2024), pp. 1-6
Closed Access | Times Cited: 2
Data analysis and management for optimal application of an advanced ML-based fault location algorithm for low voltage grids
Paschalia Stefanidou-Voziki, David Cardoner-Valbuena, Roberto Villafáfila‐Robles, et al.
International Journal of Electrical Power & Energy Systems (2022) Vol. 142, pp. 108303-108303
Closed Access | Times Cited: 12
Fault Ride Through approach for Grid-Connected Photovoltaic System
Komal Bai, Vikas Sindhu, Ahteshamul Haque
e-Prime - Advances in Electrical Engineering Electronics and Energy (2023) Vol. 5, pp. 100232-100232
Open Access | Times Cited: 6
A Novel Faulty Phase Selection Method for Single-Phase-to-Ground Fault in Distribution System Based on Transient Current Similarity Measurement
Yaojing Tang, Yongle Chang, Jinrui Tang, et al.
Energies (2021) Vol. 14, Iss. 15, pp. 4695-4695
Open Access | Times Cited: 15
Detecting and Interpreting Faults in Vulnerable Power Grids With Machine Learning
Odin Foldvik Eikeland, Inga Setså Holmstrand, Sigurd Bakkejord, et al.
IEEE Access (2021) Vol. 9, pp. 150686-150699
Open Access | Times Cited: 15
Machine Learning Based Techniques for Fault Detection in Power Distribution Grid: A Review
Oladapo Tolulope Ibitoye, Moses Oluwafemi Onibonoje, Joseph O. Dada
(2022), pp. 104-107
Closed Access | Times Cited: 10
Detection and Classification of Fault Types in Distribution Lines by Applying Contrastive Learning to GAN Encoded Time-Series of Pulse Reflectometry Signals
Javier Granado Fornás, Elías Herrero, A. Llombart, et al.
IEEE Access (2022) Vol. 10, pp. 110521-110536
Open Access | Times Cited: 10
ML-Based Intermittent Fault Detection, Classification, and Branch Identification in a Distribution Network
Mojgan Hojabri, S. Nowak, Antonios Papaemmanouil
Energies (2023) Vol. 16, Iss. 16, pp. 6023-6023
Open Access | Times Cited: 5
Development of an Intelligent Digital Twins Framework for Secure Container Terminal Operations
Sergej Jakovlev, Tomas Eglynas, Miroslav Vozňák, et al.
(2021)
Closed Access | Times Cited: 12
A multi-model-integration-based prediction methodology for the spatiotemporal distribution of vulnerabilities in integrated energy systems under the multi-type, imbalanced, and dependent input data scenarios
Chenhao Sun, Zhuoyu Zhou, Xiangjun Zeng, et al.
Applied Energy (2022) Vol. 320, pp. 119239-119239
Closed Access | Times Cited: 7
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