Research on the Application of Deep Learning Algorithm in Distribution Network Fault Location System

The application research of fault location system is critical in the fault location of intelligent distribution network, however it has an issue with erroneous performance positioning. The typical Neural network algorithms is unable to address the inaccurate fault location issue in the fault location of intelligent distribution network, and the result is insufficient. As a result, a Deep learning algorithms-based application research of distribution network fault location system is provided, and application research of distribution network fault location system is assessed. To begin, the artificial neural network theory is used to discover the influencing elements, and the indicators are split based on the application research of fault location system's needs to decrease interference factors in the application research of fault location system. The artificial neural network theory is then used to create a Deep learning algorithms application research of fault location system scheme, and the outcomes of the application research of fault location system are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Deep learning algorithms outperforms the standard Neural network algorithms in terms of application research of fault location system accuracy and time of influencing variables.