Research on risk management methods for power operation data oriented to multi scenario data

Ximing Zhang; Qiuyong Yang; Jieshan Li; Jiaqi Zhao

doi:10.1117/12.3024998

13 May 2024 Research on risk management methods for power operation data oriented to multi scenario data

Ximing Zhang, Qiuyong Yang, Jieshan Li, Jiaqi Zhao

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315978 (2024) https://doi.org/10.1117/12.3024998
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

In order to improve the security of power operation data, a risk management method for multi scenario data is proposed. Based on blockchain technology, a power operation data storage model was constructed, and a data risk management model was constructed using federated reinforcement learning algorithm. Through this model, risk management processing was implemented on the data. It can be seen from the experimental results that the highest value of the Factor of safety of this method is 0.95, the lowest value is 0.78, and the highest value of the number of times of data theft prevention is 58, which indicates that this method can effectively improve the effect of data theft prevention, and the power operation data has a high Factor of safety, which indicates that this method can fully ensure the security of power operation data

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ximing Zhang, Qiuyong Yang, Jieshan Li, and Jiaqi Zhao "Research on risk management methods for power operation data oriented to multi scenario data", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315978 (13 May 2024); https://doi.org/10.1117/12.3024998

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