IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v290y2021ics0306261921002646.html
   My bibliography  Save this item

Artificial intelligence to support the integration of variable renewable energy sources to the power system

Citations

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


Cited by:

  1. Lee, Chi-Chuan & Fang, Yuzhu & Quan, Shiyun & Li, Xinghao, 2024. "Leveraging the power of artificial intelligence toward the energy transition: The key role of the digital economy," Energy Economics, Elsevier, vol. 135(C).
  2. Vladimir Franki & Darin Majnarić & Alfredo Višković, 2023. "A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector," Energies, MDPI, vol. 16(3), pages 1-35, January.
  3. Yin, Linfei & Zhou, Hang, 2024. "Modal decomposition integrated model for ultra-supercritical coal-fired power plant reheater tube temperature multi-step prediction," Energy, Elsevier, vol. 292(C).
  4. Yousaf, Imran & Ohikhuare, Obaika M. & Li, Yong & Li, Yanshuang, 2024. "Interconnectedness between electricity and artificial intelligence-based markets during the crisis periods: Evidence from the TVP-VAR approach," Energy Economics, Elsevier, vol. 139(C).
  5. Xu, Jing & Wang, Xiaoying & Gu, Yujiong & Ma, Suxia, 2023. "A data-based day-ahead scheduling optimization approach for regional integrated energy systems with varying operating conditions," Energy, Elsevier, vol. 283(C).
  6. Christian Urom & Gideon Ndubuisi & Hela Mzoughi & Khaled Guesmi, 2024. "Exploring the coherency and predictability between the stocks of artificial intelligence and energy corporations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
  7. Latifa A. Yousef & Hibba Yousef & Lisandra Rocha-Meneses, 2023. "Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions," Energies, MDPI, vol. 16(24), pages 1-27, December.
  8. Iorgovan Daniela, 2024. "Artificial Intelligence and Renewable Energy Utilization," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 2776-2783.
  9. He, Huizi & Sun, Mei & Li, Xiuming & Mensah, Isaac Adjei, 2022. "A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features," Energy, Elsevier, vol. 244(PA).
  10. Urom, Christian & Ndubuisi, Gideon & Guesmi, Khaled & Benkraien, Ramzi, 2022. "Quantile co-movement and dependence between energy-focused sectors and artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
  11. Wu, Chunying & Sun, Lingfang & Piao, Heng & Yao, Lijia, 2024. "Adaptive fuzzy finite time integral sliding mode control of the coordinated system for 350 MW supercritical once-through boiler unit to enhance flexibility," Energy, Elsevier, vol. 302(C).
  12. Kingsley Ukoba & Kehinde O. Olatunji & Eyitayo Adeoye & Tien-Chien Jen & Daniel M. Madyira, 2024. "Optimizing renewable energy systems through artificial intelligence: Review and future prospects," Energy & Environment, , vol. 35(7), pages 3833-3879, November.
  13. Gubareva, Mariya & Shafiullah, Muhammad & Teplova, Tamara, 2025. "Cross-quantile risk assessment: The interplay of crude oil, artificial intelligence, clean tech, and other markets," Energy Economics, Elsevier, vol. 141(C).
  14. Sun, Lingyun & Yin, Jiemin & Bilal, Ahmad Raza, 2023. "Green financing and wind power energy generation: Empirical insights from China," Renewable Energy, Elsevier, vol. 206(C), pages 820-827.
  15. Ferahtia, Seydali & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal techno-economic energy management strategy for building’s microgrids based bald eagle search optimization algorithm," Applied Energy, Elsevier, vol. 306(PB).
  16. Wiesheu, Michael & Rutešić, Luka & Shukhobodskiy, Alexander Alexandrovich & Pogarskaia, Tatiana & Zaitcev, Aleksandr & Colantuono, Giuseppe, 2021. "RED WoLF hybrid storage system: Adaptation of algorithm and analysis of performance in residential dwellings," Renewable Energy, Elsevier, vol. 179(C), pages 1036-1048.
  17. 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.
  18. Bin Li & Yuxiang Tan & Qingqing Guo & Weihuan Wang, 2023. "Application of Comprehensive Evaluation of Line Loss Lean Management Based on Big-Data-Driven Paradigm," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
  19. Cui, Zhipeng & Xu, Jing & Liu, Wenhao & Zhao, Guanjia & Ma, Suxia, 2023. "Data-driven modeling-based digital twin of supercritical coal-fired boiler for metal temperature anomaly detection," Energy, Elsevier, vol. 278(PA).
  20. Md Tariqul Islam & M. J. Hossain, 2023. "Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-33, February.
  21. 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).
  22. Daniel Icaza Alvarez & Fernando González-Ladrón-de-Guevara & Jorge Rojas Espinoza & David Borge-Diez & Santiago Pulla Galindo & Carlos Flores-Vázquez, 2025. "The Evolution of AI Applications in the Energy System Transition: A Bibliometric Analysis of Research Development, the Current State and Future Challenges," Energies, MDPI, vol. 18(6), pages 1-31, March.
  23. Zulfiqar, M. & Kamran, M. & Rasheed, M.B. & Alquthami, T. & Milyani, A.H., 2023. "A hybrid framework for short term load forecasting with a navel feature engineering and adaptive grasshopper optimization in smart grid," Applied Energy, Elsevier, vol. 338(C).
  24. Thangjam, Aditya & Jaipuria, Sanjita & Dadabada, Pradeep Kumar, 2023. "Time-Varying approaches for Long-Term Electric Load Forecasting under economic shocks," Applied Energy, Elsevier, vol. 333(C).
  25. Apurva Goel & Snehal Masurkar & Girish R. Pathade, 2024. "An Overview of Digital Transformation and Environmental Sustainability: Threats, Opportunities, and Solutions," Sustainability, MDPI, vol. 16(24), pages 1-36, December.
  26. Zhao, Guanjia & Cui, Zhipeng & Xu, Jing & Liu, Wenhao & Ma, Suxia, 2022. "Hybrid modeling-based digital twin for performance optimization with flexible operation in the direct air-cooling power unit," Energy, Elsevier, vol. 254(PC).
  27. Feng, Fangfang & Li, Junjun & Zhang, Feng & Sun, Jinghuan, 2024. "The impact of artificial intelligence on green innovation efficiency: Moderating role of dynamic capability," International Review of Economics & Finance, Elsevier, vol. 96(PB).
  28. Adamczyk, Wojciech & Myöhänen, Kari & Klajny, Marcin & Kettunen, Ari & Klimanek, Adam & Ryfa, Arkadiusz & Białecki, Ryszard & Sładek, Sławomir & Zdeb, Janusz & Budnik, Michał & Peczkis, Grzegorz & Prz, 2024. "Development and demonstration of advanced predictive and prescriptive algorithms to control industrial installation," Energy, Elsevier, vol. 313(C).
  29. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
  30. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2025. "The Energy Hunger Paradox of Artificial Intelligence: End of Clean Energy or Magic Wand for Sustainability?," Sustainability, MDPI, vol. 17(7), pages 1-32, March.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.