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Machine learning driven smart electric power systems: Current trends and new perspectives

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Cited by:

  1. Ahmad, Tanveer & Madonski, Rafal & Zhang, Dongdong & Huang, Chao & Mujeeb, Asad, 2022. "Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  2. Bakhshideh Zad, Bashir & Toubeau, Jean-François & Bruninx, Kenneth & Vatandoust, Behzad & De Grève, Zacharie & Vallée, François, 2022. "Supervised learning-assisted modeling of flow-based domains in European resource adequacy assessments," Applied Energy, Elsevier, vol. 325(C).
  3. Chongchong Xu & Zhicheng Liao & Chaojie Li & Xiaojun Zhou & Renyou Xie, 2022. "Review on Interpretable Machine Learning in Smart Grid," Energies, MDPI, vol. 15(12), pages 1-31, June.
  4. Lin, Wen-Ting & Chen, Guo & Huang, Yuhan, 2022. "Incentive edge-based federated learning for false data injection attack detection on power grid state estimation: A novel mechanism design approach," Applied Energy, Elsevier, vol. 314(C).
  5. 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).
  6. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski & Ibrahim Alhamrouni, 2024. "AI Applications to Enhance Resilience in Power Systems and Microgrids—A Review," Sustainability, MDPI, vol. 16(12), pages 1-35, June.
  7. Li, Yutong & Hou, Jian & Yan, Gangfeng, 2024. "Exploration-enhanced multi-agent reinforcement learning for distributed PV-ESS scheduling with incomplete data," Applied Energy, Elsevier, vol. 359(C).
  8. Domagoj Badanjak & Hrvoje Pandžić, 2021. "Distribution-Level Flexibility Markets—A Review of Trends, Research Projects, Key Stakeholders and Open Questions," Energies, MDPI, vol. 14(20), pages 1-26, October.
  9. Hassani, Hossein & Razavi-Far, Roozbeh & Saif, Mehrdad, 2022. "Real-time out-of-step prediction control to prevent emerging blackouts in power systems: A reinforcement learning approach," Applied Energy, Elsevier, vol. 314(C).
  10. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Zhao, Yiwen & Zhan, Weipeng, 2023. "Stacking regression technology with event profile for electric vehicle fast charging behavior prediction," Applied Energy, Elsevier, vol. 336(C).
  11. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  12. Lan, Puzhe & Han, Dong & Xu, Xiaoyuan & Yan, Zheng & Ren, Xijun & Xia, Shiwei, 2022. "Data-driven state estimation of integrated electric-gas energy system," Energy, Elsevier, vol. 252(C).
  13. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
  14. Paul Arévalo & Francisco Jurado, 2024. "Impact of Artificial Intelligence on the Planning and Operation of Distributed Energy Systems in Smart Grids," Energies, MDPI, vol. 17(17), pages 1-22, September.
  15. Fernández-Blanco, Ricardo & Morales, Juan Miguel & Pineda, Salvador, 2021. "Forecasting the price-response of a pool of buildings via homothetic inverse optimization," Applied Energy, Elsevier, vol. 290(C).
  16. Xi He & Heng Dong & Wanli Yang & Wei Li, 2023. "Multi-Source Information Fusion Technology and Its Application in Smart Distribution Power System," Sustainability, MDPI, vol. 15(7), pages 1-16, April.
  17. Tursunboev, Jamshid & Palakonda, Vikas & Kang, Jae-Mo, 2024. "Multi-Objective Evolutionary Hybrid Deep Learning for energy theft detection," Applied Energy, Elsevier, vol. 363(C).
  18. Keyong Hu & Zheyi Fu & Chunyuan Lang & Wenjuan Li & Qin Tao & Ben Wang, 2024. "Short-Term Photovoltaic Power Generation Prediction Based on Copula Function and CNN-CosAttention-Transformer," Sustainability, MDPI, vol. 16(14), pages 1-18, July.
  19. liu, Qian & li, Yulin & jiang, Hang & chen, Yilin & zhang, Jiang, 2024. "Short-term photovoltaic power forecasting based on multiple mode decomposition and parallel bidirectional long short term combined with convolutional neural networks," Energy, Elsevier, vol. 286(C).
  20. Igor Simone Stievano & Riccardo Trinchero, 2023. "Advanced Techniques for the Modeling and Simulation of Energy Networks," Energies, MDPI, vol. 16(5), pages 1-3, February.
  21. Mbungu, Nsilulu T. & Ismail, Ali A. & AlShabi, Mohammad & Bansal, Ramesh C. & Elnady, A. & Hamid, Abdul Kadir, 2023. "Control and estimation techniques applied to smart microgrids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
  22. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
  23. Valerio Mariani & Giovanna Adinolfi & Amedeo Buonanno & Roberto Ciavarella & Antonio Ricca & Vincenzo Sorrentino & Giorgio Graditi & Maria Valenti, 2024. "A Survey on Anomalies and Faults That May Impact the Reliability of Renewable-Based Power Systems," Sustainability, MDPI, vol. 16(14), pages 1-29, July.
  24. Saidatul Habsah Asman & Nur Fadilah Ab Aziz & Ungku Anisa Ungku Amirulddin & Mohd Zainal Abidin Ab Kadir, 2021. "Transient Fault Detection and Location in Power Distribution Network: A Review of Current Practices and Challenges in Malaysia," Energies, MDPI, vol. 14(11), pages 1-37, May.
  25. Dong, Wei & Chen, Xianqing & Yang, Qiang, 2022. "Data-driven scenario generation of renewable energy production based on controllable generative adversarial networks with interpretability," Applied Energy, Elsevier, vol. 308(C).
  26. Nebiyu Kedir & Phuong H. D. Nguyen & Citlaly Pérez & Pedro Ponce & Aminah Robinson Fayek, 2023. "Systematic Literature Review on Fuzzy Hybrid Methods in Photovoltaic Solar Energy: Opportunities, Challenges, and Guidance for Implementation," Energies, MDPI, vol. 16(9), pages 1-38, April.
  27. Mahfuzur Rahman & Solaiman Chowdhury & Mohammad Shorfuzzaman & Mohammad Kamal Hossain & Mohammad Hammoudeh, 2023. "Peer-to-Peer Power Energy Trading in Blockchain Using Efficient Machine Learning Model," Sustainability, MDPI, vol. 15(18), pages 1-15, September.
  28. Bozhen Jiang & Qin Wang & Shengyu Wu & Yidi Wang & Gang Lu, 2024. "Advancements and Future Directions in the Application of Machine Learning to AC Optimal Power Flow: A Critical Review," Energies, MDPI, vol. 17(6), pages 1-17, March.
  29. Arman Goudarzi & Farzad Ghayoor & Muhammad Waseem & Shah Fahad & Issa Traore, 2022. "A Survey on IoT-Enabled Smart Grids: Emerging, Applications, Challenges, and Outlook," Energies, MDPI, vol. 15(19), pages 1-32, September.
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