Distribution Network Line Loss Anomaly Detection Based on Joint Neural Network
With the continuous promotion of energy internet strategy,distribution network plays an increasingly important role in energy internet.The line loss rate of distribution network is one of the important evaluation indexes of electric power compa-nies.The inaccurate diagnosis of abnormal line loss is an urgent problem for electric power companies to solve.This paper presents a method of abnormal line loss detection in distribution network based on joint neural network.The collected data of the distribution network are preprocessed,and the combined neural network is used to predict the line loss and load to realize the detection of abnormal lines in the substations under the control.In this paper,simulation experiments are carried out with the operating data of the distribution network administered by a city power supply company,and several groups of comparison experiments are designed to verify the effectiveness of the proposed method.The experimental results show that the method based on the joint neural network can diagnose the abnormal line loss quickly and accurately,and has practical application val-ue.
joint neural networklong and short-term memoryanomaly detectionline loss
万方数据
维普
