Research on Weak Fault Line Selection Method of Distribution Network Based on Machine Learning
In modern power systems,the distribution network serves as a bridge between transmission and users,and its stable and efficient operation is crucial to ensuring the reliability of power supply.With the development and application of machine learning technology,it has shown great potential in the field of fault diagnosis and processing.Machine learning methods can effectively identify and select weak faults by analyzing and learning a large amount of historical fault data,extracting useful features.The weak fault line selection method of distribution network based on machine learning is studied,starting from the basic concepts of distribution networks and weak faults,and elaborates on the application principles and methods of machine learning in weak fault line selection in distribution networks.The basic framework,data collection,feature extraction,and training process of the line selection method were introduced in detail,and the effectiveness of the proposed method was verified through technical testing.
machine learningweak distribution network failureline selection method
万方数据
维普
