STEMM Institute Press
Science, Technology, Engineering, Management and Medicine
Research on the Path of Artificial Intelligence Technology to Improve the Security of New Power System
DOI: https://doi.org/10.62517/jbdc.202501104
Author(s)
Haobo Liang*, Yingxiong Leng, Jinman Luo, Jie Chen, Xiaoji Guo
Affiliation(s)
Dongguan Power Supply Bureau, Guangdong Power Grid Corporation, Dongguan, China *Corresponding Author
Abstract
This paper explores the application of artificial intelligence (AI) technologies to enhance the security of new power systems. It begins with an introduction to AI and new power systems, followed by a detailed analysis of the security requirements specific to these systems. The paper defines and classifies power system security, addressing the unique challenges posed by new power infrastructures, and identifies key security factors. It then discusses how AI can improve security in power systems through intelligent perception and monitoring, intelligent analysis and decision-making, network security protection, and intelligent collaboration and autonomy. The study concludes by highlighting the potential of AI in transforming the security landscape of modern power systems, emphasizing its ability to adapt to evolving threats and enhance system resilience.
Keywords
Artificial Intelligence; New Power System; Security Requirements; Intelligent Monitoring; Network Security
References
[1]Tushar, W., & Ghosh, S. (2018). Artificial Intelligence for Electric Power System Protection: A Survey. IEEE Transactions on Industrial Informatics, 14(8), 3524-3533. [2]Mubarak, M., & Chakrabarti, S. (2021). Artificial Intelligence and Machine Learning for Power System Optimization and Management. IEEE Transactions on Power Systems, 36(5), 3759-3769. [3]Wang, J., Zhong, H., Xia, Q., & Kang, C. (2020). Review of key technologies for new-type power system with high proportion of renewable energy. Journal of Modern Power Systems and Clean Energy, 8(5), 935-947. [4]Zhao, Y., Song, Y., & Li, H. (2019). Overview of artificial intelligence applications in power systems. Energy Reports, 5, 1456-1464. [5]He, C., & Zhuang, Z. (2021). Artificial intelligence for renewable energy systems: A comprehensive review. Energy Conversion and Management, 234, 113908. [6]Zhao, B., Liu, W., & Li, S. (2020). Artificial Intelligence for Power System Control and Protection: A Review. IEEE Transactions on Smart Grid, 11(5), 4190-4202. [7]Zhou, K., Liu, T., & Zhang, X. (2016). Application of Artificial Intelligence in Power System Automation and Optimization: A Review. Energy Reports, 2, 303-315. [8]Guan, X., & Wang, J. (2020). Artificial Intelligence in Power System and Energy Management: A Review of Applications. Renewable and Sustainable Energy Reviews, 119, 109531. [9]Kusiak, A., & Zhang, Z. (2011). Optimization of Wind Turbine Energy Efficiency Using Artificial Intelligence. IEEE Transactions on Energy Conversion, 26(3), 711-718. [10]Duan, J., Chen, Y., & Hu, Z. (2020). Artificial Intelligence Techniques in Power System Reliability Evaluation: A Review. Applied Energy, 259, 114151. [11]Zhao, Q., Wu, L., & Wang, J. (2019). A Review of Applications of Artificial Intelligence Techniques in Power System Protection and Control. IEEE Access, 7, 45670-45681. [12]Jiang, Z., & Liu, Y. (2019). Application of Deep Learning in Power System Stability Analysis and Control. Energy Reports, 5, 619-629. [13]Yu, C., Zhang, L., & Li, D. (2017). Artificial Intelligence and Big Data in Power System Control and Protection: A Review. Electric Power Systems Research, 146, 29-42.
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