DIAGNOSIS OF OLTC USING DGA AND STATIC WINDING RESISTANCE TEST

On Load Tap Changer (OLTC) failure occurs is due to the insulation degradation and contacts failure inside it. Other than that, contacts wear influences the OLTC performances. The worn contacts will cause hotspots in the OLTC tank and cause the insulating oil to degrade faster. As a result, this will lead to the damage of complete transformer unit. Thus, the research work that has been carried out applied the Dissolved Gas Analysis (DGA) via latest Duval Triangle method during the diagnosis of OLTC rated at 33/11kV, 30MVA at the first stage to provide early indication of OLTC�s breakdown. The Static Winding Resistance Test is then applied at the second stage to figure out any increase of contact resistances for all phases. In addition, it is expected to have a relationship between both results. The results showed that it was proven that by performing DGA via latest Duval Triangle method, the early indication of OLTC�s breakdown can be obtained. Besides, this paper revealed that the Static Winding Resistance Test was capable to provide any sign of bad contacts in fixed condition as well as looses connections

Diagnosis of OLTC via Duval Triangle Method and Dynamic Current Measurement

Power transformers studies have shown that the main cause of power transformers failures is the On Load Tap Changer (OLTC). OLTC failure occurs due to the insulation degradation and contacts failure inside it. Other than that, contacts wear influences the OLTC performance and this phenomenon has not been deeply investigated. The worn contacts will cause hotspots in the OLTC tank and cause the insulating oil to degrade faster. Consequently, this will lead to the damage of complete transformer unit. Thus, the research work that has been carried out applied three different stages related to the diagnosis of OLTC. Firstly, fault detection of power transformer's OLTC is done mainly based on the results of the DGA interpretation by using the latest Duval Triangle method. Then, the results that obtained from latest Duval Triangle method are compared with the results carried out from Dynamic Current Measurement (DCM). Finally, research validation through visual inspection is applied to validate the results obtained from both DGA and DCM

Condition Monitoring of Distribution Transformer's Mechanical Parts Using Sweep Frequency Response Analysis (SFRA)

Distribution transformer is the key element in the electricity transmission throughout the nation. Hence, serious attention for the transformer condition monitoring is a crucial. With an occurrence of short-circuit in the power system, the transformer active parts such as core and winding will experience a mechanical movement created by the electromagnetic forces. There are various types of transformer condition monitoring measurement in market, but the monitoring of the mechanical movement in transformer is still lacking. Therefore, Sweep Frequency Response Analysis (SFRA) has been introduced to assess any mechanical movement especially of the transformer's core and winding. The frequency response of the transformer provides mechanical information of core and winding conditions. The SFRA measurement results were validated using the actual transformer untanking process

MECHANICAL CONDITION ASSESSMENT OF TNB IN-SERVICE DISTRIBUTION TRANSFORMERS USING SWEEP FREQUENCY RESPONSE ANALYSIS (SFRA)

Distribution transformers in TNB (Tenaga Nasional Berhad) are exposed to the thermal and electrical stresses. Those stresses are effecting to the main mechanical active parts in transformer such as core and winding. In field, lightning strikes and cable faults may cause problem due to transformer core and winding. Sweep Frequency Response Analysis (SFRA) is an off-line diagnostic tool used for finding out any possible winding displacement or mechanical deterioration inside the transformer especially core and winding. SFRA diagnosis is made based on the comparison between two SFRA responses and any significant difference in low, middle and high frequency sub-bands region would potentially indicate mechanical or electrical problem to the winding and core of transformer. The aim of this paper is to assess the condition of TNB in-service distribution transformers by using SFRA method

ANALYSIS OF KRAFT PAPER INSULATION�S LIFE FOR 15MVA POWER DISTRIBUTION TRANSFORMER IN TENAGA NASIONAL BERHAD

Among the most expensive and major equipment in any transmission and distribution electrical network is a transformer. Examples of electrical insulations for transformer are mineral oil and cellulose based paper. The said insulations degraded as transformers performed their work, while the most critical component of the transformer insulation system is the paper insulation. It is not easily replaced as compared to oil where it is easily reconditioned in-order to remove water and contaminants. Experimental and simulation studies on paper insulation showed that temperature, oxygen and moisture contents contributed to its degradation. Moisture and Furan were produced from these deterioration processes. In this study level of 2- Furaldehyde (2FAL) were obtained from Tenaga Nasional Berhad (TNB) in-service distribution power transformer. Categorizations were then carried out on these data for endof- life analysis. This study shows that the end-of-life in years derived from probability density function (Pdf)) can be used to estimate the life of paper insulation

Evaluation of Transformer Core and Winding Conditions from SFRA Measurement Results using Statistical Techniques for Distribution Transformers

Distribution transformers in TNB (Tenaga Nasional Berhad) Malaysia are exposed to thermal and electrical stresses. Those stresses are effecting the main mechanical active parts in transformer such as core and winding. In field, lightning strikes and cable faults may cause problem due to transformer core and winding. SFRA diagnosis is made based on the comparison between two SFRA responses and any significant difference in low, middle and high frequency sub-bands region would potentially indicate mechanical or electrical problem due to core and winding of transformer. Instead of using graphical comparison, statistical techniques such as Cross-correlation Coefficient Function (CCF), Standard Deviation (SD) and Absolute Sum of Logarithmic Error (ASLE) can be used to interpret the SFRA results in a proper way. The aim of this paper is to evaluate the condition of TNB distribution transformer by using SFRA method in line with the interpretation from the statistical techniques

Kraft Paper Insulation’s Life Assessment and Effects of Oxygen and Moisture to Paper Insulation’s Deterioration Rate

Examples of electrical insulations for transformer are mineral oil and cellulose based paper. The said insulations degraded as transformers performed their work, while the most critical component of the transformer insulation system is the paper insulation. It is not easily replaced as compared to oil where it is easily reconditioned in-order to remove water and contaminants. Studies on paper insulation showed that temperature, oxygen and moisture contents contributed to its degradation. Moisture and Furan were produced from these deterioration processes. The paper is focused on the effect of oxygen and moisture contents to deterioration rate of Kraft paper insulation and end-of-life analysis using 2 Furaldehyde (2FAL). Level of temperature, oxygen, moisture contents and 2FAL were obtained from in-service distribution power transformers. Assessments were then carried out on these collected data to determine the effect of oxygen and moisture contents to 2FAL formation. Categorizations were then carried out on 2FAL data for end-of-life analysis using Weibull as a life data analysis. This study shows that moisture give more implication to paper insulation degradation rate compared to oxygen and the end-of-life in years derived from Weibull probability function can be used to estimate the life of paper insulation

Condition Assessment of OLTC Using Duval Triangle and Static Winding Resistance Test

On Load Tap Changer (OLTC) failure occurs is due to the insulation degradation and contacts failure inside it. Other than that, contacts wear influences the OLTC performances. The worn contacts will cause hotspots in the OLTC tank and cause the insulating oil to degrade faster. As a result, this will lead to the damage of complete transformer unit. Thus, the research work that has been carried out applied the Dissolved Gas Analysis (DGA) via latest Duval Triangle method during the diagnosis of OLTC at the first stage to provide early indication of OLTC’s breakdown. The Static Winding Resistance Test is then applied at the second stage to figure out any increase of contact resistances for all phases. The capability of Static Winding Resistance Test in order to provide any sign of bad contacts in fixed condition can be done by comparing two different conditions which are before and after maintenance

Simulation of TDR Circuit for the analysis of Wave Propagation in XLPE cable Model

Wave propagation characteristic of single phase medium voltage MV cross-linked-polyethylene (XLPE) cable is determined by using Time Domain Reflectometry (TDR). It involves sending electrical pulse along a cable by using an oscilloscope to observe the reflected pulses. By using electrical circuit analysis and transmission line theory, the relationship between the actual and the reflected pulses from the test cable to the reflected pulses measured from an oscilloscope can be obtained. In actual field, test cable is usually lossy cable. By using the high frequency XLPE cable model, the distributed parameters which consist of R, resistance per-unit length (/m), L, inductance per-unit length (H/m), C, capacitance per-unit length (F/m) and G, conductance per-unit length (S/m) are represented and applied in the TDR PSpice circuit simulation. Therefore by using simulation of TDR in PSpice circuit, it delivered the wave propagation characteristic which is attenuation. This paper as a reference guides to study how wave propagate in TDR measurement system and from the analysis and results of TDR simulation, the attenuation from XLPE cable model can be obtained

Transformer Mechanical Integrity Evaluation Via Unsupervised Neural Network (UNN) In Smart Grid Network

This paper describes the classification of mechanical integrity of transformers using unsupervised neural networks (UNN). Transformers are the integral part of electrical system or smart grid networks since the last century. Self-Organizing Maps (SOM) is one type of UNN the widely used to do assessment on any system such as biomedical engineering, load contingency analysis and etc. The application of CIGRE standard and SOM in the research are enhancing the ability to do mechanical integrity assessment on the transformers for condition monitoring. Motivation for this research is to fill in the gap of excess FRA raw data for better assessment. This research proved that the new proposed method using SOM integrated with CIGRE standard able to do mechanical examination especially on core, winding and magnetic part of the transformer compared to current OMICRON SFRAnalyzer tool that employed Chinese Standard