Research on Condensation Prediction Model of Distribution Cabinets Based on Bp Neural Network

The distribution cabinet is one of the areas most affected by the condensation phenomenon. The generation of condensation within the distribution cabinet is influenced by temperature and humidity fluctuations, as well as other climatic conditions. This phenomenon can result in impaired insulation performance, accelerated equipment ageing, equipment failure, and compromised safe and stable operation of the distribution cabinet. Furthermore, the condensation phenomenon poses a threat to the safety of the power system. This paper explores the condensation mechanism of distribution cabinets and the development of technology for its prediction. Initially, a condensation experiment is conducted to obtain the condensation characteristics. The establishment of a condensation warning model employing the BP neural network (BPNN) is then undertaken to predict the condensation risk of distribution cabinets. The findings demonstrate the efficacy of the warning model developed in this study, substantiating its potential for enhancing the safety and reliability of power systems.