• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2348-2355
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• 2015

Transformer mineral oil which is normally hydrocarbon based is non- biodegradable and pollutes the environment in all aspects. Though vegetable oils are eco-friendly in nature and potentially could be used in transformers as a replacement for the mineral oil, there usage is restricted because of their oxidative instability. The present work focuses on using rapeseed oil and pongamia (pongamia pinnata) oil as effective alternatives for the traditional mineral oil in power transformer. The oxidative stability of the rapeseed oil and pongamia oil is increased by using combinations of the natural and synthetic anti-oxidants as additives. The parameters like breakdown voltage, viscosity, flash point, fire point are measured for the rapeseed oil and pongamia oil with and without the additives as per IEC and ASTM standards. The results shown encouraging changes in the parameter values and ensures the use of the oils as a potential alternative insulation in power transformers.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.864-866
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• 1997

This paper presents fault recognition and interpretation in power transformers using dissolved gas analysis embedded Kohonen feature mapping. The imprecision of gas ratio analysis in dissolved gas analysis are managed by mapping in accordance with learning of Kohonen neural network. To verify the effectiveness of the proposed system, it has been tested by the historical gas records to power transformers of Korea Electric Power Corporation. More appropriate fault types can support the maintenance personnels to increase the disgnostic performance for fault of power transformers.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.40-45
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• 2005

Substation facilities have become extremely large and complex parts of electric power systems. The development of condition monitoring and diagnosis techniques has been a very significant factor in the improvement of substation transformer security. This paper presents a method to analyze the cause, the degree, and the aging process power transformers by the Self Organizing Map (SOM) method. Dissolved gas data were non-linearly transformed by the sigmoid function in SOM that works much the same way as the human decision making process. The potential for failure and the degree of aging of normal transformers are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2000.11a
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• pp.55-59
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• 2000

This paper gives various load profiles of power transformers and motors in apartment housing. The load profile of power transformer shows that it is peaked in winter by heating system, and the maximum value of load profiles in power transformer is ranged 25%∼35%, which shows it is operated on over-capacity. The maximum value of demand factor in water supply system is about 60% and this of wastewater treatment system is about 50%.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.3-6
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• 1990

The impact of the convected charges, which is caused by the electrification phenomina, in the oil-paper insulation systems of power transformers has been numerically investigated using FEM. The potential distribution of the oil-paper insulation system is assumed to be governed by three equations instead of the classical Laplace equation. When the charge density of oil and the conduction current are kept high, the field distortion or the interrace in a power transformer is considerably distorted due to the convected charges.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.371-373
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• 2001

Main functions of Generator Circuit Breaker(GCB) is cut the generator off from the main transformers and the aux. transformers when plant trip or startup. In this paper, the design requirements For GCB of nuclear power plant is examined. NRC presented the area of review, acceptance criteria and review procedures of GCB in the SRP(Standard Review Plan). In Korea, APR1400 adapted the GCB in main power system.

• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.63-64
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• 2016

This paper deal with single module design of 13.2kVrms/10kVA solid state transformers exchanging conventional transformer. We can design compact hardware system to reduce size and get higher switching frequency by using SiC devices. As a result by comparing simulation results with experiment result, it is verified.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.280-284
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• 2016

Stability and reliability of a power system in many respects depend on the condition of power transformers. Essential devices as power transformers are in a transmission and distribution system. Being one of the most expensive and important elements, a power transformer is a highly essential element, whose failures and damage may cause the outage of a power system. To detect the power transformer faults, dissolved gas analysis (DGA) is a widely-used method because of its high sensitivity to small amount of electrical faults. Among the various diagnosis methods, Rogers diagonsis method has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using PNN(Probability Neural Network) based Rogers diagnosis method. The test result show better performance than conventional Rogers diagnosis method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1605-1611
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• 2017

In this study, the characteristic lifetime of power facilities such as power transformers and GIS were investigated as the basis of power facility asset management. It is difficult to obtain the operation and failure data of the facilities in Korea. Therefore, the number of failures of the electric power facilities was calculated from the operation data and hazard rate shown in the overseas literatures, and the statistical analysis was performed using the Weibull distribution function. As a result of extracting and analyzing the data of the UK National Grid for power transformers, the characteristic lifetime (scale parameter) of 116.45 years was considered to be a very appropriate value for power transformer management and can be used as a comparative data of the analysis of the domestic transformers. As for the GIS, based on the Bays and Bay-Years data and the hazard rate according to the operation years of the 123kV GIS in Germany, it is found out that the characteristic lifetime of GIS is not so meaningful. It is necessary to decide a maintenance strategy and lifetime expectancy considering the characteristics of the design, materials and manufacturing process of GIS.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.830-839
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• 2017

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.