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Application of Artificial Intelligence in Power System Monitoring and Fault Diagnosis

Author

Listed:
  • Guang Wang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Jiale Xie

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Shunli Wang

    (School of Information Engineering, Southwest University of Science and Technology, Mianyang 621000, China)

Abstract

Emerging technologies such as artificial intelligence (AI), big data analytics, and deep learning have gained widespread attention in recent years and have demonstrated great potential for application in many industrial fields [...]

Suggested Citation

  • Guang Wang & Jiale Xie & Shunli Wang, 2023. "Application of Artificial Intelligence in Power System Monitoring and Fault Diagnosis," Energies, MDPI, vol. 16(14), pages 1-3, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5477-:d:1197374
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    References listed on IDEAS

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    1. Ainhoa Pujana & Miguel Esteras & Eugenio Perea & Erik Maqueda & Philippe Calvez, 2023. "Hybrid-Model-Based Digital Twin of the Drivetrain of a Wind Turbine and Its Application for Failure Synthetic Data Generation," Energies, MDPI, vol. 16(2), pages 1-20, January.
    2. Jianfeng Zheng & Zhichao Chen & Qun Wang & Hao Qiang & Weiyue Xu, 2022. "GIS Partial Discharge Pattern Recognition Based on Time-Frequency Features and Improved Convolutional Neural Network," Energies, MDPI, vol. 15(19), pages 1-14, October.
    3. Lianhong Chen & Chao Wang & Rigang Zhong & Jin Wang & Zheng Zhao, 2022. "Intelligent Modeling of the Incineration Process in Waste Incineration Power Plant Based on Deep Learning," Energies, MDPI, vol. 15(12), pages 1-12, June.
    4. Chenqiang Luo & Zhendong Zhang & Dongdong Qiao & Xin Lai & Yongying Li & Shunli Wang, 2022. "Life Prediction under Charging Process of Lithium-Ion Batteries Based on AutoML," Energies, MDPI, vol. 15(13), pages 1-15, June.
    5. Raad Salih Jawad & Hafedh Abid, 2023. "HVDC Fault Detection and Classification with Artificial Neural Network Based on ACO-DWT Method," Energies, MDPI, vol. 16(3), pages 1-18, January.
    6. Valerio Francesco Barnabei & Fabrizio Bonacina & Alessandro Corsini & Francesco Aldo Tucci & Roberto Santilli, 2023. "Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data," Energies, MDPI, vol. 16(9), pages 1-15, April.
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