Research on the integrated management method of electric power big data based on the grid data center

Jian Chang; Yan Gong; Kunling Liu

doi:10.1117/12.2686711

6 August 2023 Research on the integrated management method of electric power big data based on the grid data center

Jian Chang, Yan Gong, Kunling Liu

Proceedings Volume 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023); 1278104 (2023) https://doi.org/10.1117/12.2686711
Event: 2023 International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 2023, Guangzhou, JS, China

Abstract

The current traditional electric power big data integration management method realizes the intelligent scheduling and management of electric power data through load prediction of electric power data, which leads to poor data transmission performance due to the lack of pre-processing of the original data. In this regard, a research on the integrated management method of electric power big data based on the grid data center is proposed. By using asymmetric encryption technology to generate private, cipher and public keys of blocks, the signature encryption and login authentication of the collection layer are completed, pre-processing of power data is realized, and power management security analysis is conducted, and the integrated power big data management architecture is proposed. In the experiment, the data transmission performance of the proposed electric power data integration management method is verified. The analysis of the experimental results shows that the power data integration management platform built by the proposed method has a low transmission delay and has a better data transmission performance.

Citation Download Citation

Jian Chang, Yan Gong, and Kunling Liu "Research on the integrated management method of electric power big data based on the grid data center", Proc. SPIE 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 1278104 (6 August 2023); https://doi.org/10.1117/12.2686711

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