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A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network

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  1. Raquel Martinez & Pablo Castro & Alberto Arroyo & Mario Manana & Noemi Galan & Fidel Simon Moreno & Sergio Bustamante & Alberto Laso, 2022. "Techniques to Locate the Origin of Power Quality Disturbances in a Power System: A Review," Sustainability, MDPI, vol. 14(12), pages 1-27, June.
  2. Artvin-Darien Gonzalez-Abreu & Roque-Alfredo Osornio-Rios & Arturo-Yosimar Jaen-Cuellar & Miguel Delgado-Prieto & Jose-Alfonso Antonino-Daviu & Athanasios Karlis, 2022. "Advances in Power Quality Analysis Techniques for Electrical Machines and Drives: A Review," Energies, MDPI, vol. 15(5), pages 1-26, March.
  3. Li, Jianbin & Chen, Zhiqiang & Cheng, Long & Liu, Xiufeng, 2022. "Energy data generation with Wasserstein Deep Convolutional Generative Adversarial Networks," Energy, Elsevier, vol. 257(C).
  4. Mohammad Reza Shadi & Hamid Mirshekali & Rahman Dashti & Mohammad-Taghi Ameli & Hamid Reza Shaker, 2021. "A Parameter-Free Approach for Fault Section Detection on Distribution Networks Employing Gated Recurrent Unit," Energies, MDPI, vol. 14(19), pages 1-15, October.
  5. Shao, Han & Henriques, Rui & Morais, Hugo & Tedeschi, Elisabetta, 2024. "Power quality monitoring in electric grid integrating offshore wind energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
  6. Noor Hussain & Mashood Nasir & Juan Carlos Vasquez & Josep M. Guerrero, 2020. "Recent Developments and Challenges on AC Microgrids Fault Detection and Protection Systems–A Review," Energies, MDPI, vol. 13(9), pages 1-31, May.
  7. Zemin Gao & Mingtao Ding, 2022. "Application of convolutional neural network fused with machine learning modeling framework for geospatial comparative analysis of landslide susceptibility," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 833-858, September.
  8. Zahoor Ali Khan & Muhammad Adil & Nadeem Javaid & Malik Najmus Saqib & Muhammad Shafiq & Jin-Ghoo Choi, 2020. "Electricity Theft Detection Using Supervised Learning Techniques on Smart Meter Data," Sustainability, MDPI, vol. 12(19), pages 1-25, September.
  9. Jiajun Cai & Kai Zhang & Hui Jiang, 2023. "Power Quality Disturbance Classification Based on Parallel Fusion of CNN and GRU," Energies, MDPI, vol. 16(10), pages 1-12, May.
  10. Enrique Reyes-Archundia & Wuqiang Yang & Jose A. Gutiérrez Gnecchi & Javier Rodríguez-Herrejón & Juan C. Olivares-Rojas & Aldo V. Rico-Medina, 2024. "Effect of Phase Shifting on Real-Time Detection and Classification of Power Quality Disturbances," Energies, MDPI, vol. 17(10), pages 1-14, May.
  11. Zakarya Oubrahim & Yassine Amirat & Mohamed Benbouzid & Mohammed Ouassaid, 2023. "Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review," Energies, MDPI, vol. 16(6), pages 1-41, March.
  12. Cheng-I Chen & Sunneng Sandino Berutu & Yeong-Chin Chen & Hao-Cheng Yang & Chung-Hsien Chen, 2022. "Regulated Two-Dimensional Deep Convolutional Neural Network-Based Power Quality Classifier for Microgrid," Energies, MDPI, vol. 15(7), pages 1-16, March.
  13. Nuno M. Rodrigues & Fernando M. Janeiro & Pedro M. Ramos, 2023. "Power Quality Transient Detection and Characterization Using Deep Learning Techniques," Energies, MDPI, vol. 16(4), pages 1-11, February.
  14. Igual, R. & Medrano, C., 2020. "Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  15. Xiao, Tianqi & You, Fengqi, 2023. "Building thermal modeling and model predictive control with physically consistent deep learning for decarbonization and energy optimization," Applied Energy, Elsevier, vol. 342(C).
  16. Arafat, M.Y. & Hossain, M.J. & Alam, Md Morshed, 2024. "Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
  17. Artvin-Darien Gonzalez-Abreu & Miguel Delgado-Prieto & Roque-Alfredo Osornio-Rios & Juan-Jose Saucedo-Dorantes & Rene-de-Jesus Romero-Troncoso, 2021. "A Novel Deep Learning-Based Diagnosis Method Applied to Power Quality Disturbances," Energies, MDPI, vol. 14(10), pages 1-17, May.
  18. Lin Yang & Linming Guo & Wenhai Zhang & Xiaomei Yang, 2022. "Classification of Multiple Power Quality Disturbances by Tunable-Q Wavelet Transform with Parameter Selection," Energies, MDPI, vol. 15(9), pages 1-16, May.
  19. Liu, Yulong & Jin, Tao & Mohamed, Mohamed A., 2023. "A novel dual-attention optimization model for points classification of power quality disturbances," Applied Energy, Elsevier, vol. 339(C).
  20. Sun, Chenhao & Wang, Xin & Zheng, Yihui, 2020. "An ensemble system to predict the spatiotemporal distribution of energy security weaknesses in transmission networks," Applied Energy, Elsevier, vol. 258(C).
  21. Azam Bagheri & Roger Alves de Oliveira & Math H. J. Bollen & Irene Y. H. Gu, 2022. "A Framework Based on Machine Learning for Analytics of Voltage Quality Disturbances," Energies, MDPI, vol. 15(4), pages 1-14, February.
  22. Zhang, Liangheng & Jiang, Congmei & Pang, Aiping & He, Yu, 2024. "Super-efficient detector and defense method for adversarial attacks in power quality classification," Applied Energy, Elsevier, vol. 361(C).
  23. da Silva, Roberto Perillo Barbosa & Quadros, Rodolfo & Shaker, Hamid Reza & da Silva, Luiz Carlos Pereira, 2020. "Effects of mixed electronic loads on the electrical energy systems considering different loading conditions with focus on power quality and billing issues," Applied Energy, Elsevier, vol. 277(C).
  24. David Lumbreras & Eduardo Gálvez & Alfonso Collado & Jordi Zaragoza, 2020. "Trends in Power Quality, Harmonic Mitigation and Standards for Light and Heavy Industries: A Review," Energies, MDPI, vol. 13(21), pages 1-24, November.
  25. 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.
  26. Hong, Ying-Yi & Rioflorido, Christian Lian Paulo P., 2019. "A hybrid deep learning-based neural network for 24-h ahead wind power forecasting," Applied Energy, Elsevier, vol. 250(C), pages 530-539.
  27. Radovan Turović & Dinu Dragan & Gorana Gojić & Veljko B. Petrović & Dušan B. Gajić & Aleksandar M. Stanisavljević & Vladimir A. Katić, 2022. "An End-to-End Deep Learning Method for Voltage Sag Classification," Energies, MDPI, vol. 15(8), pages 1-22, April.
  28. Ren, Tao & Modest, Michael F. & Fateev, Alexander & Sutton, Gavin & Zhao, Weijie & Rusu, Florin, 2019. "Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
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