IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v278y2020ics0306261920312228.html
   My bibliography  Save this item

Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Fatima Zahra Zahraoui & Mehdi Et-taoussi & Houssam Eddine Chakir & Hamid Ouadi & Brahim Elbhiri, 2023. "Bellman–Genetic Hybrid Algorithm Optimization in Rural Area Microgrids," Energies, MDPI, vol. 16(19), pages 1-26, September.
  2. Walter Leal Filho & Peter Yang & João Henrique Paulino Pires Eustachio & Anabela Marisa Azul & Joshua C. Gellers & Agata Gielczyk & Maria Alzira Pimenta Dinis & Valerija Kozlova, 2023. "Deploying digitalisation and artificial intelligence in sustainable development research," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 4957-4988, June.
  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. Jose Ulises Castellanos Contreras & Leonardo Rodríguez Urrego, 2023. "Technological Developments in Control Models Using Petri Nets for Smart Grids: A Review," Energies, MDPI, vol. 16(8), pages 1-21, April.
  5. Chao-Chung Hsu & Bi-Hai Jiang & Chun-Cheng Lin, 2023. "A Survey on Recent Applications of Artificial Intelligence and Optimization for Smart Grids in Smart Manufacturing," Energies, MDPI, vol. 16(22), pages 1-15, November.
  6. 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).
  7. Hugo Gaspar Hernandez-Palma & Jonny Rafael Plaza Alvarado & Jesús Enrique García Guiliany & Guilherme Luiz Dotto & Claudete Gindri Ramos, 2024. "Implications of Machine Learning in the Generation of Renewable Energies in Latin America from a Globalized Vision: A Systematic Review," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 1-10, March.
  8. Musawenkosi Lethumcebo Thanduxolo Zulu & Rudiren Pillay Carpanen & Remy Tiako, 2023. "A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks," Energies, MDPI, vol. 16(4), pages 1-32, February.
  9. Li, Jiale & Yang, Bo & Huang, Jianxiang & Guo, Zhengxun & Wang, Jingbo & Zhang, Rui & Hu, Yuanweiji & Shu, Hongchun & Chen, Yixuan & Yan, Yunfeng, 2023. "Optimal planning of Electricity–Hydrogen hybrid energy storage system considering demand response in active distribution network," Energy, Elsevier, vol. 273(C).
  10. Zhang, Xiaojing & Khan, Khalid & Shao, Xuefeng & Oprean-Stan, Camelia & Zhang, Qian, 2024. "The rising role of artificial intelligence in renewable energy development in China," Energy Economics, Elsevier, vol. 132(C).
  11. Tawfiq Chekifi & Amine Benmoussa & Moustafa Boukraa, 2024. "Desalination Powered by Renewables: A Challenge and an AI Opportunity," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(14), pages 5419-5461, November.
  12. Prince Waqas Khan & Yongjun Kim & Yung-Cheol Byun & Sang-Joon Lee, 2021. "Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction," Energies, MDPI, vol. 14(21), pages 1-22, November.
  13. 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).
  14. Noman, Abdullah Al & Tasneem, Zinat & Sahed, Md. Fahad & Muyeen, S.M. & Das, Sajal K. & Alam, Firoz, 2022. "Towards next generation Savonius wind turbine: Artificial intelligence in blade design trends and framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  15. Mahmoud Aref & Almoataz Y. Abdelaziz & Zong Woo Geem & Junhee Hong & Farag K. Abo-Elyousr, 2023. "Oscillation Damping Neuro-Based Controllers Augmented Solar Energy Penetration Management of Power System Stability," Energies, MDPI, vol. 16(5), pages 1-21, March.
  16. Keighobadi, Jafar & Mohammadian KhalafAnsar, Hadi & Naseradinmousavi, Peiman, 2022. "Adaptive neural dynamic surface control for uniform energy exploitation of floating wind turbine," Applied Energy, Elsevier, vol. 316(C).
  17. Lu, Qing & Zhang, Yufeng, 2022. "A multi-objective optimization model considering users' satisfaction and multi-type demand response in dynamic electricity price," Energy, Elsevier, vol. 240(C).
  18. Michael Meiser & Ingo Zinnikus, 2024. "A Survey on the Use of Synthetic Data for Enhancing Key Aspects of Trustworthy AI in the Energy Domain: Challenges and Opportunities," Energies, MDPI, vol. 17(9), pages 1-29, April.
  19. Tursunboev, Jamshid & Palakonda, Vikas & Kang, Jae-Mo, 2024. "Multi-Objective Evolutionary Hybrid Deep Learning for energy theft detection," Applied Energy, Elsevier, vol. 363(C).
  20. Nazir, Lubna & Sharifi, Ayyoob, 2024. "An analysis of barriers to the implementation of smart grid technology in Pakistan," Renewable Energy, Elsevier, vol. 220(C).
  21. Pranobjyoti Lahon & Aditya Bihar Kandali & Utpal Barman & Ruhit Jyoti Konwar & Debdeep Saha & Manob Jyoti Saikia, 2024. "Deep Neural Network-Based Smart Grid Stability Analysis: Enhancing Grid Resilience and Performance," Energies, MDPI, vol. 17(11), pages 1-17, May.
  22. Huiling Qin & Shuang Li & Juncheng Zhang & Zhi Rao & Chengyu He & Zhijun Chen & Bo Li, 2024. "Online Prediction and Correction of Static Voltage Stability Index Based on Extreme Gradient Boosting Algorithm," Energies, MDPI, vol. 17(22), pages 1-14, November.
  23. 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).
  24. Lutfu Saribulut & Gorkem Ok & Arman Ameen, 2023. "A Case Study on National Electricity Blackout of Turkey," Energies, MDPI, vol. 16(11), pages 1-20, May.
  25. Yin, Linfei & Lu, Yuejiang, 2021. "Expandable deep width learning for voltage control of three-state energy model based smart grids containing flexible energy sources," Energy, Elsevier, vol. 226(C).
  26. Cai, Qingsen & Luo, XingQi & Wang, Peng & Gao, Chunyang & Zhao, Peiyu, 2022. "Hybrid model-driven and data-driven control method based on machine learning algorithm in energy hub and application," Applied Energy, Elsevier, vol. 305(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.