Capacitive voltage transformer fault reason intelligent diagnosis method

Abstract

The invention relates to an intelligent diagnosis method for a fault reason of a capacitor voltage transformer. The method comprises the following steps: acquiring data to generate a training set D; the training set D is key value pair data mapped from an input data set X to an output data set Y, the input data set X is error evaluation value data, and the output data set Y is transformer fault reason data; based on an LOF (Local Outlier Factor) algorithm, carrying out preprocessing of abnormal error data elimination on an input data set X in the training set; on the basis of the pre-processed training set, RNN model training of WOA (Whale Optimization Algorithm) parameter adjustment and optimization is carried out, and on the basis of the pre-processed training set, RNN model training of WOA (Whale Optimization Algorithm) parameter adjustment and optimization is carried out; based on the trained RNN model, fault cause prediction of the capacitor voltage transformer is carried out; and operation and maintenance personnel can find out the out-of-tolerance reason of the mutual inductor in time and carry out targeted maintenance, so that the field operation and maintenance efficiency is improved, the workload of the operation and maintenance personnel is reduced, and the operation and maintenance cost is remarkably reduced.

Description

technical field [0001] The invention relates to the technical field of smart grids, in particular to an intelligent diagnosis method for the fault cause of a capacitor voltage transformer. Background technique [0002] As an important part of the electric energy metering device, the accuracy and reliability of the metering performance of the transformer is directly related to the fairness and justice of the electric energy trade settlement. Capacitive voltage transformers are divided by series capacitors, and then stepped down and isolated by electromagnetic transformers. Compared with conventional electromagnetic voltage transformers, capacitive voltage transformers not only have the advantages of high impact insulation strength, simple manufacture, small size, and light weight, but also have many advantages in terms of economy and safety. As capacitive voltage transformers are widely used, a variety of faults or defects have appeared. Common faults include high-voltage ca...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the technical problems existing in the prior art, the present invention provides an intelligent diagnosis method for the fault cause of a capacitive voltage transformer, which utilizes online error data and adopts a deep learning algorithm to intelligently judge the cause of a CVT fault. It is also convenient to obtain information about the cause of the fault, and make judgments in advance to find out the problems of the transformer as soon as possible, which will help the operation and maintenance personnel to find out the cause of the out-of-tolerance of the transformer in time, and carry out targeted maintenance, which improves the efficiency of on-site operation and maintenance. Reduce the workload of operation and maintenance personnel and significantly reduce operation and maintenance costs

Images