Research and Application of Full Lifecycle Management Strategies for Power Data

The research and application of electric power data full lifecycle management strategy aims to improve the data management efficiency and decision support capability of electric power enterprises. This paper first discusses the importance of full lifecycle management of electric power data, emphasizing the key role of data quality for electric power enterprise operations, report generation, compliance, and potential law mining. Then, the article elaborates the strategy of full life cycle management of electric power data, including the key phases of data planning and design, operation and maintenance, and protection, as well as the specific management content and methods of each phase. The study verifies through simulation experiments that the system in this paper shows excellent recognition efficiency in comparison with the traditional system, with a maximum accuracy of 1.00 and a minimum of 0.94.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1109/edpee65754.2025.00030
Primary Topic
Power Systems and Technologies
Type
article
Field-Weighted Citation Impact
0.00
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Research and Application of Full Lifecycle Management Strategies for Power Data

Hongkai Zhao, Wei Huo, Yibin Zhao, Ning Li et al.
Power Systems and Technologies
article

Research and Application of Full Lifecycle Management Strategies for Power Data

Hongkai Zhao, Wei Huo, Yibin Zhao, Ning Li, Yan Ma
article en

Abstract

The research and application of electric power data full lifecycle management strategy aims to improve the data management efficiency and decision support capability of electric power enterprises. This paper first discusses the importance of full lifecycle management of electric power data, emphasizing the key role of data quality for electric power enterprise operations, report generation, compliance, and potential law mining. Then, the article elaborates the strategy of full life cycle management of electric power data, including the key phases of data planning and design, operation and maintenance, and protection, as well as the specific management content and methods of each phase. The study verifies through simulation experiments that the system in this paper shows excellent recognition efficiency in comparison with the traditional system, with a maximum accuracy of 1.00 and a minimum of 0.94.

State Grid Corporation of China (China) (CN)
Responsible consumption and production
Openalex Percentile: Top 85%
Power Systems and Technologies
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