Fuzzy logic based system to diagnose internal faults of power transformer

2011 ◽  
Author(s):  
U. Mohan Rao ◽  
M. Vijay Praneeth Reddy ◽  
R. K. Jarial
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Internal Faults

A Novel Approach for Classifying Transient Phenomena in Power Transformers

2004 ◽  
Vol 1 (2) ◽  
Author(s):  
El Sayed M. Tag Eldin
Keyword(s):  
Fuzzy Logic ◽  
Wavelet Transforms ◽  
Power Transformer ◽  
Current Transformer ◽  
Transient Phenomena ◽  
Protective Relay ◽  
Novel Approach ◽  
Inrush Currents ◽  
Internal Faults ◽  
External Faults

The role of a power transformer protective relay is to rapidly operate the tripping during internal faults and block the tripping during magnetizing inrush. This paper presents a new approach for classifying transient phenomena in power transformer, which may be implemented in digital relaying for transformer differential protection. Discrimination between internal faults, external faults with current transformer saturation and magnetizing inrush currents is achieved by combining wavelet transforms and fuzzy logic. The wavelet transform is applied for the analysis of the power transformer transient phenomena because of its ability to extract information from the transient signals in both time and frequency domain. Fuzzy logic is used because of the uncertainty in the differential current signals and relay settings. MATLAB power system toolbox is used to generate current signals at both sides of a power transformer in a typical system with various conditions. The simulation results obtained show that the new algorithm provides a high operating sensitivity for internal faults and remains stable for external faults and inrush currents.

scholarly journals A Novel Technique to Precise the Diagnosis of Power Transformer Internal Faults

2013 ◽  
pp. 169-173
Author(s):  
U. Mohan Rao ◽  
D.Vijay Kumar
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Gas Analysis ◽  
Response Analysis ◽  
Fuzzy Logic Algorithm ◽  
Mechanical Deformations ◽  
Catastrophic Failures ◽  
Internal Faults ◽  
Rule Bases ◽  
Thermal Oil

Power transformers are to be monitored frequently to avoid catastrophic failures which are more or less related to internal faults for which many techniques and tools are developed, somehow many of these techniques rely on experts analysis and are well effected by environmental conditions which leads to misdiagnosing of the unit. In this paper a new fuzzy logic algorithm (FLA) based technique is developed which gives the vulnerability status of internal faults by considering thermal, electrical and mechanical conditions prevailing in the transformer and integrating them. This system takes a set of test results of dissolved gas analysis, break down voltage, and sweep frequency response analysis so that aliasing effects and misdiagnosing can be reduced at a glance. It also facilitates to give current prevailing condition of Paper thermal, Oil thermal, Partial discharge, Electrical arching, oil break down voltage, and mechanical deformations related with core and windings individually so that corresponding remedies can be taken by the technologists. This system consists of 10 fuzzy logic controllers and is connected by considering technical conditions and reasons, the rule bases of these controllers were developed by considering various standards and experience of TIFAC CORE in NIT-Hamirpur. This fuzzy logic based system is tested and found that it is highly precise in classifying the critical statues of any transformer, reducing misdiagnosing and aliasing effects and identifying the current prevailing conditions.

Inter-turn fault stability enrichment and diagnostic analysis of power system network using wavelet transformation-based sample data control and fuzzy logic controller

2021 ◽  
pp. 014233122110070
Author(s):  
Arunesh Kumar Singh ◽  
Abhinav Saxena ◽  
Nathuni Roy ◽  
Umakanta Choudhury
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Wavelet Transformation ◽  
Fuzzy Logic Controller ◽  
Power Transformer ◽  
Harmonic Distortion ◽  
Inrush Current ◽  
Data Control ◽  
Sample Data ◽  
Z Transformation

In this paper, performance analysis of power system network is carried out by injecting the inter-turn fault at the power transformer. The injection of inter-turn fault generates the inrush current in the network. The power system network consists of transformer, current transformer, potential transformer, circuit breaker, isolator, resistance, inductance, loads, and generating source. The fault detection and termination related to inrush current has some drawbacks and limitations such as slow convergence rate, less stability and more distortion with the existing methods. These drawbacks motivate the researchers to overcome the drawbacks with new proposed methods using wavelet transformation with sample data control and fuzzy logic controller. The wavelet transformation is used to diagnose the fault type but contribute lesser for fault termination; due to that, sample data of different signals are collected at different frequencies. Further, the analysis of collected sample data is assessed by using Z-transformation and fuzzy logic controller for fault termination. The stability, total harmonic distortion and convergence rate of collected sample data among all three methods (wavelet transformation, Z-transformation and fuzzy logic controller) are compared for fault termination by using linear regression analysis. The complete performance of fault diagnosis along with fault termination has been analyzed on Simulink. It is observed that after fault injection at power transformer, fault recovers faster under fuzzy logic controller in comparison with Z-transformation followed by wavelet transformation due to higher stability, less total harmonic distortion and faster convergence.

A Fuzzy Logic Proposal for Diagnosis Multiple Incipient Faults in a Power Transformer

2021 ◽  
pp. 187-198
Author(s):  
J. C. Fernández ◽  
L. B. Corrales ◽  
F. H. Hernández ◽  
I. F. Benítez ◽  
J. R. Núñez
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
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.

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