An approach to diagnose incipient faults of power transformer using dissolved gas analysis of mineral oil by ratio methods using fuzzy logic

2016 ◽  
Author(s):  
Rahul Soni ◽  
Kaushal Chaudhari
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Mineral Oil ◽  
Gas Analysis ◽  
Dissolved Gas ◽  
Dissolved Gas Analysis ◽  
Incipient Faults

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.

Condition Monitoring of High Voltage Transformer using Dissolved Gas Analysis Methods

2021 ◽  
Vol 9 (VI) ◽  
pp. 1759-1770
Author(s):  
Dayyala Ravi
Keyword(s):  
Power Transmission ◽  
Power Transformer ◽  
Accurate Method ◽  
Mineral Oil ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gas ◽  
Voltage Transformer ◽  
Transformer Protection ◽  
Dissolved Gas Analysis

Power transformer plays a significant role in the entire power transmission network; thus, transformer protection requires more attention for fault free electric supply. when the mineral oil and insulation inside the transformer is subjected to high thermal and electrical stresses, gases are created by the decay of mineral oil and cellulose. Different gases create different faults, Identification of faults inside the power transformer before they occur reduces its failure rate during its service period. For Knowing the fault condition of power transformer, Dissolved Gas Analysis (DGA) is proven to be as accurate method based on combination of concentration of gases like CO, CO2, H2, C2H6, C2H4, C2H2 etc., Dissolved gas analysis is the most important test in determining the fault condition of a transformer and it is the first indicator of a problem and can identify deteriorating insulation and oil, overheating hot spots, partial discharge and arcing. For developing this DGA Techniques, the MATLAB GUIDE interface can be used for making easy interaction between the user and software developed. This software is designed using some conditional statements and logical functions to get the type of faults in transformers based on the concentration of gases in transformer oil. The faults in transformer using dissolved gases analysis are detected using methods such as key gas, Roger’s methods, IEC ratio, Doernenburg ratio, Duval triangle and the Combined DGA methods. In this paper, these four methods of dissolved gas analysis (DGA) are presented and explained briefly.

scholarly journals Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Edwell T. Mharakurwa ◽  
G. N. Nyakoe ◽  
A. O. Akumu
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Total Energy ◽  
Power Transformer ◽  
Gas Analysis ◽  
Dissolved Gas ◽  
Dissolved Gas Analysis ◽  
Fault Severity ◽  
Incipient Fault ◽  
Transformer Maintenance

Decision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques cannot quantify the detected fault severity. Fault severity is the core property in transformer maintenance rankings. This paper presents a fuzzy logic methodology in determining transformer faults and severity through use of energy of fault formation of the evolved gasses during transformer faulting event. Additionally, the energy of fault formation is a temperature-dependent factor for all the associated evolved gases. Instead of using the energy-weighted DGA, the calculated total energy of related incipient fault is used for severity determination. Severity of faults detected by fuzzy logic-based key gas method is evaluated through the use of collected data from several in-service and faulty transformers. DGA results of oil samples drawn from transformers of different specifications and age are used to validate the model. Model results show that correctly detecting fault type and its severity determination based on total energy released during faults can enhance decision-making in prioritizing maintenance of faulty transformers.

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