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Convolutional neural network-based power system transient stability assessment and instability mode prediction

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  1. Huimin Wang & Zhaojun Steven Li, 2022. "An AdaBoost-based tree augmented naive Bayesian classifier for transient stability assessment of power systems," Journal of Risk and Reliability, , vol. 236(3), pages 495-507, June.
  2. Izabela Rojek & Dariusz Mikołajewski & Marek Andryszczyk & Tomasz Bednarek & Krzysztof Tyburek, 2025. "Leveraging Machine Learning in Next-Generation Climate Change Adaptation Efforts by Increasing Renewable Energy Integration and Efficiency," Energies, MDPI, vol. 18(13), pages 1-22, June.
  3. Andrei M. Tudose & Irina I. Picioroaga & Dorian O. Sidea & Constantin Bulac & Valentin A. Boicea, 2021. "Short-Term Load Forecasting Using Convolutional Neural Networks in COVID-19 Context: The Romanian Case Study," Energies, MDPI, vol. 14(13), pages 1-19, July.
  4. Zhang, Jinlai & Yang, Wenjie & Chen, Yumei & Ding, Mingkang & Huang, Huiling & Wang, Bingkun & Gao, Kai & Chen, Shuhan & Du, Ronghua, 2024. "Fast object detection of anomaly photovoltaic (PV) cells using deep neural networks," Applied Energy, Elsevier, vol. 372(C).
  5. Shitu Zhang & Zhixun Zhu & Yang Li, 2021. "A Critical Review of Data-Driven Transient Stability Assessment of Power Systems: Principles, Prospects and Challenges," Energies, MDPI, vol. 14(21), pages 1-13, November.
  6. Li, Yang & Zhang, Meng & Chen, Chen, 2022. "A Deep-Learning intelligent system incorporating data augmentation for Short-Term voltage stability assessment of power systems," Applied Energy, Elsevier, vol. 308(C).
  7. Zhan, Xianwen & Han, Song & Rong, Na & Cao, Yun, 2023. "A hybrid transfer learning method for transient stability prediction considering sample imbalance," Applied Energy, Elsevier, vol. 333(C).
  8. Shi, Zhongtuo & Yao, Wei & Li, Zhouping & Zeng, Lingkang & Zhao, Yifan & Zhang, Runfeng & Tang, Yong & Wen, Jinyu, 2020. "Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions," Applied Energy, Elsevier, vol. 278(C).
  9. Izzuddin Fathin Azhar & Lesnanto Multa Putranto & Roni Irnawan, 2022. "Development of PMU-Based Transient Stability Detection Methods Using CNN-LSTM Considering Time Series Data Measurement," Energies, MDPI, vol. 15(21), pages 1-20, November.
  10. Li, Chen & Kies, Alexander & Zhou, Kai & Schlott, Markus & Sayed, Omar El & Bilousova, Mariia & Stöcker, Horst, 2024. "Optimal Power Flow in a highly renewable power system based on attention neural networks," Applied Energy, Elsevier, vol. 359(C).
  11. Wang, Hanxuan & Lu, Na & Liu, Yinhong & Wang, Zhuqing & Wang, Zixuan, 2025. "A multi-module robust method for transient stability assessment against false label injection cyberattacks," Applied Energy, Elsevier, vol. 389(C).
  12. Nastaran Gholizadeh & Petr Musilek, 2021. "Distributed Learning Applications in Power Systems: A Review of Methods, Gaps, and Challenges," Energies, MDPI, vol. 14(12), pages 1-18, June.
  13. Huang, Wanjun & Zhang, Xinran & Zheng, Weiye, 2021. "Resilient power network structure for stable operation of energy systems: A transfer learning approach," Applied Energy, Elsevier, vol. 296(C).
  14. Estefania Alexandra Tapia & Delia Graciela Colomé & José Luis Rueda Torres, 2022. "Recurrent Convolutional Neural Network-Based Assessment of Power System Transient Stability and Short-Term Voltage Stability," Energies, MDPI, vol. 15(23), pages 1-24, December.
  15. Shuaibo Wang & Xinyuan Xiang & Jie Zhang & Zhuohang Liang & Shufang Li & Peilin Zhong & Jie Zeng & Chenguang Wang, 2025. "A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems," Energies, MDPI, vol. 18(6), pages 1-17, March.
  16. Ferencek Aljaž & Kofjač Davorin & Škraba Andrej & Sašek Blaž & Borštnar Mirjana Kljajić, 2020. "Deep Learning Predictive Models for Terminal Call Rate Prediction during the Warranty Period," Business Systems Research, Sciendo, vol. 11(2), pages 36-50, October.
  17. Chenhao, Sun & Yaoding, Wang & Xiangjun, Zeng & Wen, Wang & Chun, Chen & Yang, Shen & Zhijie, Lian & Quan, Zhou, 2024. "A hybrid spatiotemporal distribution forecast methodology for IES vulnerabilities under uncertain and imprecise space-air-ground monitoring data scenarios," Applied Energy, Elsevier, vol. 373(C).
  18. Nan Li & Jiafei Wu & Lili Shan & Luan Yi, 2024. "Transient Stability Assessment of Power Systems Based on CLV-GAN and I-ECOC," Energies, MDPI, vol. 17(10), pages 1-18, May.
  19. Jude Suchithra & Duane Robinson & Amin Rajabi, 2023. "Hosting Capacity Assessment Strategies and Reinforcement Learning Methods for Coordinated Voltage Control in Electricity Distribution Networks: A Review," Energies, MDPI, vol. 16(5), pages 1-28, March.
  20. Huang, Yaodi & Song, Yunpeng & Cai, Zhongmin, 2025. "A supervised contrastive learning method with novel data augmentation for transient stability assessment considering sample imbalance," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
  21. Hua, Weiqi & Stephen, Bruce & Wallom, David C.H., 2023. "Digital twin based reinforcement learning for extracting network structures and load patterns in planning and operation of distribution systems," Applied Energy, Elsevier, vol. 342(C).
  22. Shi, Zhongtuo & Yao, Wei & Zhao, Yifan & Ai, Xiaomeng & Wen, Jinyu & Cheng, Shijie, 2024. "Two-stage weakly supervised learning to mitigate label noise for intelligent identification of power system dominant instability mode," Applied Energy, Elsevier, vol. 359(C).
  23. Ruan, Haokai & Wei, Zhongbao & Shang, Wentao & Wang, Xuechao & He, Hongwen, 2023. "Artificial Intelligence-based health diagnostic of Lithium-ion battery leveraging transient stage of constant current and constant voltage charging," Applied Energy, Elsevier, vol. 336(C).
  24. Sun, Chenhao & Xu, Hao & Zeng, Xiangjun & Wang, Wen & Jiang, Fei & Yang, Xin, 2023. "A vulnerability spatiotemporal distribution prognosis framework for integrated energy systems within intricate data scenes according to importance-fuzzy high-utility pattern identification," Applied Energy, Elsevier, vol. 344(C).
  25. Heungseok Lee & Jongju Kim & June Ho Park & Sang-Hwa Chung, 2023. "Power System Transient Stability Assessment Using Convolutional Neural Network and Saliency Map," Energies, MDPI, vol. 16(23), pages 1-22, November.
  26. Dahu Li & Hongyu Zhou & Yuan Chen & Yue Zhou & Yuze Rao & Wei Yao, 2023. "A Frequency Support Approach for Hybrid Energy Systems Considering Energy Storage," Energies, MDPI, vol. 16(10), pages 1-16, May.
  27. Li, Jingxian & Ma, Ping & Wang, Cong & Zhang, Shaohua & Zhang, Hongli, 2024. "Dynamics analysis and adaptive neural network command filtering excitation control of stochastic power system," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).
  28. Tayo Uthman Badrudeen & Nnamdi I. Nwulu & Saheed Lekan Gbadamosi, 2023. "Neural Network Based Approach for Steady-State Stability Assessment of Power Systems," Sustainability, MDPI, vol. 15(2), pages 1-13, January.
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