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10 August 2023 Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform
Jun Wei, Fanglin Guo, Ce Li, Linxiang Zhao, Hua Wang, Xiaoxia Kou, Hongyu Long
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Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 1274821 (2023) https://doi.org/10.1117/12.2689902
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China
Abstract
In order to effectively solve the problems of power system front-end technology diversification and low explicit programming efficiency, a "visual programming" method based on low-code development platform is proposed. This method uses component-based graphical programming tools to build front-end pages, designs data collection forms through the platform, and delivers the collected data to the back-end neural network model for training, so as to predict the fault risk of distribution line units, improve the power enterprise's ability to adapt to demand changes, carry out operation and maintenance more pertinently, and greatly improve the business staff's ability.
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Jun Wei, Fanglin Guo, Ce Li, Linxiang Zhao, Hua Wang, Xiaoxia Kou, and Hongyu Long "Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 1274821 (10 August 2023); https://doi.org/10.1117/12.2689902
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KEYWORDS
Data modeling
Software development
Neural networks
Power grids
Computer programming
Computer security
Artificial neural networks
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