scholarly journals Transformer Oil Regeneration as a Panacea for Electric Power Utility Company‟s Equipment Optimization

2019 ◽  
Vol 8 (2) ◽  
pp. 2160-2167
Keyword(s):  
Electric Power ◽  
Dielectric Breakdown ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Power Transformers ◽  
Dissolved Metals ◽  
Power Utility ◽  
Utility Company ◽  
Before And After

Power transformers constitute the most costly equipment which often posed constraints to electric power utility companies’ management. These transformers develop faults often due to oil insulation problems resulting from poor level of insulation oil, lack of routine maintenance, contamination, age, carbonization arising from system tripping as well as degradation of paper insulation due to ageing. However, the most economical way of maintaining stability in power supply to customers is creating a routine program of transformer oil regeneration for power transformer in the network. This paper therefore presents the optimization process of transformer oil regeneration for electric power utility company equipment. In this study, combined techniques of hot oil circulation, oil purification and oil reclamation of transformer oil regeneration was used for analysis of two 15MVA, 33/11kV power transformer. The process is aimed at drying the solid insulation of the transformer through the circulation of hot oil. The results of the transformer oil test before and after carrying out oil regeneration processes for the two 15MVA transformers are obtained and presented. For each transformer, the results are in five categories of properties namely; Physical, Electrical, Chemical, Dissolved metals and Dissolved gas analysis properties. The results indicated that the viscosity of transformer 1 is better than that of transformer 2. In addition, the dielectric breakdown voltage of oil transformer 1 is of more quality than the oil in transformer 2. The results are in agreement with standard ASTMD, IEC and ISO because the transformer properties has individual standard with each having its own mark. The comparison shows that transformer oil regenerated was very close to reality because the oil in the two power transformers is close to 90 %.

scholarly journals Study of approaches to incipient fault detection in power transformer by using dissolved gas analysis

Energetika ◽  
2017 ◽  
Vol 63 (2) ◽  
Author(s):  
Ruta Liepniece ◽  
Sandra Vitolina ◽  
Janis Marks
Keyword(s):  
Fault Detection ◽  
Power Transmission ◽  
Power Transformer ◽  
Good Condition ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Power Transformers ◽  
Dissolved Gas ◽  
Dissolved Gas Analysis ◽  
Incipient Fault

To maintain the reliability of power transmission it is important to detect the incipient fault of power transformer as early as possible. If the fault of a power transformer is not detected promptly, it can evolve resulting in high repair costs or even failure of the power transformer and decreasing reliability of power transmission. The most commonly used method for power transformer fault detection is the dissolved gas analysis (DGA) of transformer oil. Various methods have been developed to interpret the data of dissolved gas analysis, but not many are applicable for the detection of the incipient fault. The detection of the incipient fault of a power transformer is included in both IEEE C57.104-2008 “Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers” and Standard of Latvian Electrotechnical Committee LEK 118 “Transformer Oil Inspection Standards”. In both standards, the limits of dissolved gases in transformer oil are divided into levels, each corresponding to different technical conditions of the power transformer including the level that indicates the incipient fault. However, these approaches vary to a great degree – one approach mostly indicates that transformers are in good condition with several cases that must be additionally evaluated, but the second approach mostly results in warning about the incipient fault, which must be confirmed by additional evaluation. The objective of this paper is to determine the most suitable approach to detect the incipient fault of power transformers. A case study is provided, which includes analysis of DGA data of 48 power transformers installed in the transmission network in Latvia with both methodologies mentioned above for detecting the incipient fault.

scholarly journals Dissolved Gas Analysis Equipment for Online Monitoring of Transformer Oil: A Review

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4057 ◽  
Author(s):  
Sergio Bustamante ◽  
Mario Manana ◽  
Alberto Arroyo ◽  
Pablo Castro ◽  
Alberto Laso ◽  
...  
Keyword(s):  
Electric Power ◽  
Online Monitoring ◽  
Oil Quality ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Power Transformers ◽  
Quality Analysis ◽  
Dissolved Gas ◽  
Correct Operation ◽  
Dissolved Gas Analysis

Power transformers are the most important assets of electric power substations. The reliability in the operation of electric power transmission and distribution is due to the correct operation and maintenance of power transformers. The parameters that are most used to assess the health status of power transformers are dissolved gas analysis (DGA), oil quality analysis (OQA) and content of furfuraldehydes (FFA) in oil. The parameter that currently allows for simple online monitoring in an energized transformer is the DGA. Although most of the DGA continues to be done in the laboratory, the trend is online DGA monitoring, since it allows for detection or diagnosis of the faults throughout the life of the power transformers. This study presents a review of the main DGA monitors, single- or multi-gas, their most important specifications, accuracy, repeatability and measurement range, the types of installation, valve or closed loop, and number of analogue inputs and outputs. This review shows the differences between the main existing DGA monitors and aims to help in the selection of the most suitable DGA monitoring approach according to the needs of each case.

scholarly journals An Alternative Approach for Oil-immersed High Voltage Power Transformer Dissolved Gas Analysis Diagnostic Techniques

2019 ◽  
Vol 18 (2) ◽  
pp. 1-7
Author(s):  
Ahmad Karimi Mehrabadi ◽  
Asaad Shemshadi ◽  
Hossein Shateri
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Diagnostic Techniques ◽  
Inference Engine ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Power Transformers ◽  
Fuzzy Logic Inference ◽  
Triangle Method ◽  
Logic Inference

This article presents alternative analyzing method of extracted dissolved gases related to insulating oil of power transformers. Analysis of soluble and free gas is one of the most commonly used troubleshooting methods for detecting and evaluating equipment damage. Although the analysis of oil-soluble gases is often complex, it should be expertly processed during maintenance operation. The destruction of the transformer oil will produce some hydrocarbon type gases. The development of this index is based on two examples of traditional evaluation algorithms along with fuzzy logic inference engine. Through simulation process, the results of the initial fractures in the transformer are obtained in two ways by the "Duval Triangle method” and "Rogers’s ratios". In continue, three digit codes containing the fault information are created based on the fuzzy logic inference engine to achieve better results and eliminate ambiguous zones in commonly used methods, especially in the “Duval Triangle method”. The proposed method is applied to 80 real transformers to diagnose the fault by analyzing the dissolved oil based on fuzzy logic. The results illustrate the proficiency of this alternative proposed algorithm. Finally, with utilization of a neural network the alternative practical inference function is derived to make the algorithm more usable in the online condition monitoring of power transformers.

scholarly journals Dissolved Gas Analysis of Insulating Oil in Electric Power Transformers: A Case Study Using SDAE-LSTM

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zhao Luo ◽  
Zhiyuan Zhang ◽  
Xu Yan ◽  
Jinghui Qin ◽  
Zhendong Zhu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Electric Power ◽  
Recognition Accuracy ◽  
Power Transformer ◽  
Gas Analysis ◽  
Parameter Analysis ◽  
Power Transformers ◽  
Dissolved Gas ◽  
Insulating Oil ◽  
Dissolved Gas Analysis

Dissolved gas analysis (DGA) is the most important tool for fault diagnosis in electric power transformers. To improve accuracy of diagnosis, this paper proposed a new model (SDAE-LSTM) to identify the dissolved gases in the insulating oil of power transformers and perform parameter analysis. The performance evaluation is attained by the case studies in terms of recognition accuracy, precision ratio, and recall ratio. Experiment results show that the SDAE-LSTM model performs better than other models under different input conditions. As evidenced from the analyses, the proposed model achieves considerable results of recognition accuracy (95.86%), precision ratio (95.79%), and recall ratio (97.51%). It can be confirmed that the SDAE-LSTM model using the dissolved gas in the power transformer for fault diagnosis and analysis has great research prospect.

scholarly journals Predicting the influence of the non-sinusoidal network mode on power transformers

2019 ◽  
Vol 114 ◽  
pp. 04005
Author(s):  
Ngo Van Cuong ◽  
Lidiia I. Kovernikova
Keyword(s):  
Service Life ◽  
Electric Power ◽  
Power Quality ◽  
Electrical Equipment ◽  
Operating Conditions ◽  
Transformer Oil ◽  
Power Transformers ◽  
Electrical Network ◽  
Electrical Networks ◽  
Current Harmonics

The parameters of electrical network modes often do not meet the requirements of Russian GOST 32144-2013 and the guidelines of Vietnam. In the actual operating conditions while there is the non-sinusoidal mode in electrical networks voltage and current harmonics are present. Harmonics result in overheating and damage of power transformers since they cause additional active power losses. Additional losses lead to the additional heat release, accelerating the process of insulating paper, transformer oil and magnetic structure deterioration consequently shortening the service life of a power transformer. In this regard there arises a need to develop certain scientific methods that would help demonstrate that low power quality, for instance could lead to a decrease in the electrical equipment service life. Currently we see a development of automated systems for continuous monitoring of power quality indices and mode parameters of electrical networks. These systems could be supplemented by characteristics calculating programs that give out a warning upon detection of the adverse influence of voltage and current harmonics on various electrical equipment of both electric power providers and electric power consumers. A software program presented in the article may be used to predict the influence of voltage and current harmonics on power transformers.

scholarly journals Fuzzy Algorithm for Power Transformer Diagnostics

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Nitin K. Dhote ◽  
Jagdish B. Helonde
Keyword(s):  
Gas Chromatography ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gas ◽  
Inference System ◽  
Incipient Faults ◽  
The World

Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results fall outside conventional methods codes or when more than one fault exist in the transformer. To overcome these limitations, the fuzzy inference system (FIS) is proposed. Two hundred different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.

Knowledge Management for Electric Power Utility Companies

2010 ◽  
pp. 97-122
Author(s):  
Campbell Booth
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Electric Power ◽  
Asset Management ◽  
Effective Practices ◽  
Power Utility ◽  
Utility Company ◽  
Utility Companies ◽  
Power Utilities ◽  
Behavioural Aspects

This chapter will present an overview of the challenges presented to modern power utility companies and how many organizations are facing particularly pressing problems with regards to an ageing workforce and a general shortage of skills; a situation that is anticipated to worsen in the future. It is proposed that knowledge management (KM) and decision support (DS) may contribute to a solution to these challenges. The chapter describes the end-to-end processes associated with KM and DS in a power utility context and attempts to provide guidance on effective practices for each stage of the described processes. An overview of one particular power utility company that has embraced KM is presented, and it is proposed that the function of asset management within power utilities in particular may benefit from KM. The chapter focuses not only on KM techniques and implementation, but, equally, if not more importantly, on the various cultural and behavioural aspects that are critical to the success of any KM/DS initiative.

scholarly journals A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 1009 ◽  
Author(s):  
Rahman Azis Prasojo ◽  
Harry Gumilang ◽  
Suwarno ◽  
Nur Ulfa Maulidevi ◽  
Bambang Anggoro Soedjarno
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Local Population ◽  
Gas Analysis ◽  
Power Transformers ◽  
Support Vector ◽  
Dissolved Gas ◽  
New Approach ◽  
Dissolved Gas Analysis ◽  
Novel Approach

In determining the severity of power transformer faults, several approaches have been previously proposed; however, most published studies do not accommodate gas level, gas rate, and Dissolved Gas Analysis (DGA) interpretation in a single approach. To increase the reliability of the faults’ severity assessment of power transformers, a novel approach in the form of fuzzy logic has been proposed as a new solution to determine faults’ severity using the combination of gas level, gas rate, and DGA interpretation from the Duval Pentagon Method (DPM). A four-level typical concentration and rate were established based on the local population. To simplify the assessment of hundreds of power transformer data, a Support Vector Machine (SVM)-based DPM with high agreements to the graphical DPM has been developed. The proposed approach has been implemented to 448 power transformers and further implementation was done to evaluate faults’ severity of power transformers from historical DGA data. This new approach yields in high agreement with the previous methods, but with better sensitivity due to the incorporation of gas level, gas rate, and DGA interpretation results in one approach.

Parallelization Analysis of Dissolved Gases in Transformer Oil Based on Random Forest Algorithm

2014 ◽  
Vol 519-520 ◽  
pp. 98-101
Author(s):  
De Wen Wang ◽  
Zhi Wei Sun
Keyword(s):  
Fault Diagnosis ◽  
Random Forest ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gases ◽  
Random Forest Algorithm ◽  
Dissolved Gas ◽  
Important Method ◽  
Transformer Fault

Dissolved gas analysis (DGA) in oil is an important method for transformer fault diagnosis. This paper use random forest parallelization algorithm to analysis the dissolved gases in transformer oil. This method can achieve a fast parallel fault diagnosis for power equipment. Experimental results of the diagnosis of parallelization of random forest algorithm with DGA samples show that this algorithm not only can improve the accuracy of fault diagnosis, and more appropriate for dealing with huge amounts of data, but also can meet the smart grid requirements for fast fault diagnosis for power transformer. And this result also verifies the feasibility and effectiveness of the algorithm.

Transformer Fault Diagnosis with the Duval Triangle and Heuristic Techniques

2014 ◽  
Vol 535 ◽  
pp. 157-161
Author(s):  
Jeeng Min Ling ◽  
Ming Jong Lin ◽  
Chao Tang Yu
Keyword(s):  
Fault Diagnosis ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gas ◽  
Power Company ◽  
Triangle Method ◽  
Diagnosis Method ◽  
Combustible Gases ◽  
Transformer Fault

Dissolved gas analysis (DGA) is an effective tool for detecting incipient faults in power transformers. The ANSI/IEEE C57.104 standards, the most popular guides for the interpretation of gases generated in oil-immersed transformers, and the IEC-Duval triangle method are integrated to develop the proposed power transformer fault diagnosis method. The key dissolved gases, including H2, CH4, C2H2, C2H4, C2H6, and total combustible gases (TCG), suggested by ASTM D3612s instruction for DGA is investigated. The tested data of the transformer oil were taken from the substations of Taiwan Power Company. Diagnosis results with the text form called IEC-Duval triangle method show the validation and accuracy to detect the incipient fault in the power transformer.

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