Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform

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.