Method for evaluating running health state of magnetic control paralleling reactor

Abstract

The invention discloses a method for evaluating the running health state of a magnetic control paralleling reactor. The method comprises the steps that (1), the running characteristic of the magnetic control paralleling reactor is considered, indexes for evaluating the running health state of the magnetic control paralleling reactor are specifically selected, and the measured values of the evaluation indexes are obtained; (2), normalization processing is carried out on the measured values of the evaluation indexes through reactor preventive test regulations and the data of field researches, and evaluation index quantized values of the same measuring unit are obtained; (3), solution of the state grade membership degree is carried out on the evaluation index quantized values based on the fuzzy theory, and the different state grade membership degrees of all the evaluation indexes are obtained; (4), the running health state of the magnetic control reactor is comprehensively evaluated through an evidence theory evaluation model, and the running state of the magnetic control reactor is determined. According to the method, sample learning does not need to be carried out through a large number of prior data, and the running state of the reactor can be accurately diagnosed.

Description

technical field [0001] The invention relates to the technical field of evaluating the operating state of substation equipment, in particular to a method for evaluating the operating health state of a magnetically controlled shunt reactor. Background technique [0002] With the continuous improvement of the modernization of my country's power network, the transformation of power transmission and transformation equipment from planned maintenance to condition-based maintenance is an inevitable trend in the development of power grids. High-voltage shunt reactor is an important type of power transmission and transformation equipment in the power network. It plays the role of adjusting the reactive power distribution of the line, improving the power frequency voltage distribution along the line, improving the power transmission efficiency of the grid, and enhancing the stability of the system. Therefore, the reactor runs The status is related to the safe and stable operation of th...

AI Technical Summary

Problems solved by technology

The early diagnosis methods of dissolved gas in oil in reactor health status include chromatographic analysis method and three-ratio method. These two methods are simple to implement, but the accuracy is not high, and the state quantity considered is small, which is not enough to fully reflect the reactor status. Operating status

In response to these shortcomings, other scholars have proposed a neural network reactor fault diagnosis method and a Bayesian network evaluation method. The artificial neural network has a powerful self-learning function and data processing capabilities, but it requires a large number of samples for pre-training and learning; Bayesian network evaluation methods The Schneider network evaluation method comprehensively considers the history, current and future state of the reactor, and the comprehensive state of the reactor is determined by the Bayesian network, but this evaluation method also requires a large amount of historical data as the training samples of the Bayesian network

At present, the reactor health status assessment is to analyze the current value of the state quantity obtained from the preventive test or the maintenance test as the original information, and there are few studies on the change trend of the state quantity

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