Study on Automatic Monitoring of Electricity Consumption for Maintenance of Low-Voltage Intelligent Distribution Boxes in Power Systems

In the development process of China's power system, automatic monitoring mode has become an important development direction.In this context, how to achieve real-time monitoring of power data in the system has become an urgent problem.In this paper, considering the current range, the controller with input current is selected to collect voltage and current data signals and detect their circuits.Through metadata integration, the semantic integration of data expression is solved to achieve the management of electric power metadata.The collected data are sequentially accessed, handled and processed, the calibration of the voltage and current signals is agreed upon, the AD-converted values are read and the electrical parameters are calculated.Using the communication protocol IEC61850, the processed electric power data is uploaded into the server to complete the electric power data reading and monitoring tasks.The real-time management platform of intelligent maintenance power box constructed in this paper is used to monitor the abnormal power data.The abnormal power data appeared at different times, and the peak value of abnormal value 1 appeared at 14:00, and the peak data was 0.91 w.The evaluation value interval of the security threat in the transmission of power data is between 100-200 g, and the energy interval fluctuates around 1000 c.The results obtained are more reasonable, and the security of the data is guaranteed.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-16
DOI
https://doi.org/10.61091/jcmcc127a-206
Primary Topic
Power Systems and Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Study on Automatic Monitoring of Electricity Consumption for Maintenance of Low-Voltage Intelligent Distribution Boxes in Power Systems

Journal of Combinatorial Mathematics and Combinatorial Computing
Power Systems and Technologies
article

Study on Automatic Monitoring of Electricity Consumption for Maintenance of Low-Voltage Intelligent Distribution Boxes in Power Systems

article en

Abstract

In the development process of China's power system, automatic monitoring mode has become an important development direction.In this context, how to achieve real-time monitoring of power data in the system has become an urgent problem.In this paper, considering the current range, the controller with input current is selected to collect voltage and current data signals and detect their circuits.Through metadata integration, the semantic integration of data expression is solved to achieve the management of electric power metadata.The collected data are sequentially accessed, handled and processed, the calibration of the voltage and current signals is agreed upon, the AD-converted values are read and the electrical parameters are calculated.Using the communication protocol IEC61850, the processed electric power data is uploaded into the server to complete the electric power data reading and monitoring tasks.The real-time management platform of intelligent maintenance power box constructed in this paper is used to monitor the abnormal power data.The abnormal power data appeared at different times, and the peak value of abnormal value 1 appeared at 14:00, and the peak data was 0.91 w.The evaluation value interval of the security threat in the transmission of power data is between 100-200 g, and the energy interval fluctuates around 1000 c.The results obtained are more reasonable, and the security of the data is guaranteed.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
China Southern Power Grid
Affordable and clean energy
Openalex Percentile: Top 93%
Power Systems and Technologies
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Study on Automatic Monitoring of Electricity Consumption for Maintenance of Low-Voltage Intelligent Distribution Boxes in Power Systems · Journal of Combinatorial Mathematics and Combinatorial Computing (2025) | TGRS Research Map | TGRS