Power monitoring data access control system based on BP neural network
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Guanyu Zhang
,
Haibin Liu
Abstract
With the rapid development of social economy, the demand for electric power engineering is gradually increasing. The power supply system is constantly developing in the direction of large space and automation, and various high and new technologies are also constantly improving. The power monitoring data access control system is used to monitor and control the power production and supply process and improve the power supply efficiency. The further development of the region also has a higher demand for power and energy supply. For the problem that the natural environment of transmission and distribution lines in various power grids is uncertain, which makes the line operation unsafe. This paper proposed a power monitoring data access control system based on BP (back propagation, abbreviated as BP) neural network. This paper described the related concepts of BP neural network and power monitoring system, and described the functions and construction methods of power monitoring data access control system. On this basis, relevant experiments were carried out to verify the performance of the proposed system. The experimental results showed that the fault detection accuracy of the traditional algorithm was about 93 %, while the fault detection accuracy of the algorithm in this paper was more than 98 %. The highest accuracy rate was 99.88 %, and the accuracy rate of fault detection was greatly improved.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. And all authors have seen the manuscript and approved to submit to your journal. We confirm that the content of the manuscript has not been published or submitted for publication elsewhere.
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Data availability statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Articles in the same Issue
- Frontmatter
- Research Articles
- Intelligent identification algorithm and key point detection of abnormal vibration of transmission tower based on machine learning
- Design and development of power data service platform based on multi dimension
- Evaluation on power marketing decision evaluation based on Bayesian network
- Power monitoring data access control system based on BP neural network
- Investigation and application of key technologies of aggregated flash payment based on marketing blockchain in the context of massive distributed generation grid connection
- Research on RBF neural network adaptive control of three-point contactless measuring device for CNC roller grinder
- Measurement of surface vibration signal of 500 kV transformer and analysis of its frequency characteristics
- Evaluation on key technologies for the construction of low-carbon index of electric power based on “double carbon”
- Application scenario evaluation of modified converter for quadratic Boost high gain DC-DC: taking the constant off time control mode as an example
- Efficiency of artificial intelligence automatic control system and data processing unit based on edge computing technology
- Design of mountain fire prevention monitoring system for transmission lines based on machine vision algorithms
