Model Construction of Big Data Asset Management System for Digital Power Grid Regulation

Authors

  • Silong Wu Financial Shared Service Center, Guangdong Power Grid Corporation, Guangzhou, China
  • Yangchen Yu Financial Shared Service Center, Guangdong Power Grid Corporation, Guangzhou, China
  • Yongquan Cheng YGSOFT INC. Co., Ltd, Zhuhai, China
  • Min Xu YGSOFT INC. Co., Ltd, Zhuhai, China
  • Guanyu Zhang YGSOFT INC. Co., Ltd, Zhuhai, China

DOI:

https://doi.org/10.5755/j01.itc.52.4.32642

Keywords:

Digital power grid, Digital big data, Asset management, System model, Grey prediction, AR-tree index organization

Abstract

There are many and complex big data in digital power grid regulation, which leads to the difficulty of big data asset management. Therefore, a model of big data asset management system in digital power grid regulation is constructed. The model consists of three parts: data acquisition, data safe storage and data index. The data acquisition architecture is designed, and the data acquisition results are filled with missing values and corrected with grey prediction method. Using AR-Tree index organization to realize the digital power grid regulation big data index, and achieve the goal of high-quality management of digital power grid regulation big data assets. Store the filled and corrected data in the blockchain to ensure data security. The experimental results show that the average recall and precision of this method are 96.9% and 97.9%, and the data acquisition quality is high. After the application of this method, there is almost no unsafe data, and the proportion of safe data is higher, which shows that this method can ensure the security of big data storage. The response time of digital power grid regulation big data index is below 0.21s, and the index efficiency is higher.

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Published

2023-12-22

Issue

Section

Articles