Adsorption and Sensing Properties of Dissolved Gas in Oil on Cr-Doped InN Monolayer: A Density Functional Theory Study

Dissolved gas analysis (DGA) is recognized as one of the most reliable methods in transformer fault diagnosis technology. In this paper, three characteristic gases of transformer oil (CO, C2H4, and CH4) were used in conjunction with a Cr-decorated InN monolayer according to first principle calculations. The adsorption performance of Cr–InN for these three gases were studied from several perspectives such as adsorption structures, adsorption energy, electron density, density of state, and band gap structure. The results revealed that the Cr–InN monolayer had good adsorption performance with CO and C2H4, while the band gap of the monolayer slightly changed after the adsorption of CO and C2H4. Additionally, the adsorption property of the Cr–InN monolayer on CH4 was acceptable and a significant response was simultaneously generated. This paper provides the first insights regarding the possibility of Cr-doped InN monolayers for the detection of gases dissolved in oil.

A Reserve Planning Method of Transformer Group based on Markov Reliability Model

In view of the current situation that the load difference is not considered in the existing research on public standby transformer, the reliability Markov model and public standby planning model of distribution transformer unit based on public standby mode are proposed. When the transformer fails, the standby transformer is preferred to replace the faulty transformer. The power failure time of the user is shortened from the transformer maintenance time to the standby installation and operation time. The state transition rate is the installation and operation rate of the standby transformer, and the replaced faulty transformer is converted to the standby transformer in the unavailable state. This paper applies the scheme decision analysis method to the field of engineering control, and applies the combination of the compound matter element analysis and the subjective and objective weight to the quantitative calculation of correlation entropy. This method solves the current situation that transformer faults are difficult to measure and calculate quantitatively, and it can accurately predict the healthy development trend of transformers, which has a good guiding value for the use and maintenance of transformers. At the same time, the public standby measures of distribution transformer can better solve the problem of long transformer fault repair time with a small amount of capital investment, effectively shorten the recovery time of fault outage and reduce the impact of transformer fault. The standby measures of distribution transformer have an obvious impact on the reliability of distribution system.

Review on Transformer Fault Detection and Diagnosis Algorithms

The method of fault diagnosis based on dissolved gas analysis (DGA) is of great importance to detect possible failures in the transformer and to improve the safety of the electrical system. The DGA data of the transformer in the smart grid has the characteristics of a large amount, different types and a low density of values. Since the power transformer is an important type of power supply in the electrical network, this document provides a complete overview of the power transformer and describes how to diagnose faults. Furthermore, on-line monitoring, the method of fault diagnosis and condition-based maintenance strategy decision-making method as also have been described. The paper presents detailed literature on the recent advancements and methods being adopted by various authors on fault detection.

Analysis of Total Hydrocarbon Exceeding Standard in Oil Chromatogram of a 500kV Main Transformer

Oil chromatographic analysis is widely used in transformer fault diagnosis However, the problem of excessive total hydrocarbons in the oil chromatogram caused by the failure of the transformer submersible pump is different from the failure of the transformer body. Technicians need to be able to accurately identify these two types of failure. For this problem, this article proposes a method of judging by manually starting and stopping the submersible pump and monitoring the change law of the transformer chromatographic data. This article first finds out suspicious submersible pumps through current data. Subsequently, the operator starts and stops the submersible pump and monitors the change law of the transformer chromatographic data. From this, the correlation between the start or stop of the submersible pump and the chromatographic data was found. Finally, the effectiveness of this method is verified by the submersible pump disassembly inspection and simulated live test.