• 설비공학논문집
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• 제22권8호
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• pp.515-522
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• 2010

In order to improve the efficiency of a transformer cooling system, the intelligent algorithm was developed. The intelligent algorithm is composed of a setpoint algorithm and a control algorithm. The setpoint algorithm was developed by the neural network, and the control algorithm was developed by the fuzzy logic. These algorithms were used for the control of a blower and an oil pump of the transformer cooling system. In order to analyse performances of these algorithms, the dynamic model of a transformer cooling system was used. Based on various performance tests, energy savings and stable controls of a transformer cooling system were observed. Therefore, control algorithms developed for this study may be effectively used for the control of a transformer cooling system.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 하계학술발표대회 논문집
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• pp.22-29
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• 2008

In order to improve the efficiency of a main transformer in a tilting train, the optimal operation of a cooling system is necessary. For the development of optimal control algorithms of a cooling system, mathematical models of a main transformer cooling system were developed. These include dynamic models of a main transformer, an oil pump, an oil cooler, a blower, and a pipe. Control algorithms for a blower and an oil pump were selected in order to identify the effectiveness of dynamic models. A simulation program was developed by using the developed dynamic models and the selected control algorithms. Simulation results showed good predictions of dynamic behaviors of a main transformer cooling system. Therefore, dynamic models, which were developed in this study, may be effectively used to develop control algorithms of a main transformer cooling system.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.955-960
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• 2009

In order to improve the efficiency of the main transformer in a tilting train, the optimal operation of a cooling system is necessary. Mathematical models of a main transformer cooling system were developed. These include models for the main transformer, the oil pump, the oil cooler, and the blower. The optimal oil temperature algorithm was also developed. This consists of the optimal setpoint algorithm and the control algorithm. A simulation program was developed by using mathematical models and the optimal oil temperature algorithm. Simulation results showed that the dynamic behavior of a main transformer cooling system was predicted well by mathematical models and a main transformer cooling system was controlled effectively by the optimal oil temperature algorithm.

• 설비공학논문집
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• 제22권2호
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• pp.70-77
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• 2010

In order to improve the efficiency of a main transformer in a train, the optimal operation of a cooling system is necessary. For the development of optimal control algorithms of a cooling system, mathematical models of a main transformer cooling system were developed. These include static and dynamic models of a main transformer, an oil pump, an oil cooler, and a blower. Static models were used to find optimal oil temperatures of the inlet and the outlet of a transformer. Dynamic models were used to predict transient performances of control algorithms of a blower and an oil pump. Simulation results showed good predictions of the static and the dynamic behavior of a main transformer cooling system. Therefore, mathematical models developed in this study may be effectively used for the development of control algorithms of a main transformer cooling system.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 동계학술발표대회 논문집
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• pp.387-392
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• 2008

In order to improve the efficiency of the main transformer in a tilting train, the optimal operation of a cooling system is necessary. For the development of the optimal control algorithm of a cooling system, the mathematical model of a main transformer cooling system was developed. This includes the dynamic model of a main transformer, an oil pump, an oil cooler and a blower. The system algorithm of a cooling system, which consists of the temperature setpoint algorithm and the temperature control algorithm, was developed. Optimal oil temperatures of the inlet and the outlet of the main transformer were obtained by considering the total electric power consumption of the system. The oil inlet temperature was controlled by the blower and the oil outlet temperature was controlled by the oil pump. A simulation program was developed by using the mathematical model and the system algorithm. Simulation results showed that the system algorithm developed from this study may be effectively used to control the main transformer cooling system in a tilting train.

• International Journal of Advanced Culture Technology
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• 제4권2호
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• pp.47-56
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• 2016

In transformer cooling systems, oil temperature is controlled through the use of a blower and oil pump. For this paper, set-point algorithms, a reset algorithm and control algorithms of the cooling system were developed by neural networks and fuzzy logics. The oil inlet temperature was set by a $2{\times}2{\times}1$ neural network, and the oil temperature difference was set by a $2{\times}3{\times}1$ neural network. Inputs used for these neural networks were the transformer operating ratio and the air inlet temperature. The inlet set temperature was reset by a fuzzy logic based on the transformer operating ratio and the oil outlet temperature. A blower was used to control the inlet oil temperature while the oil pump was used to control the oil temperature difference by fuzzy logics. In order to analysis the performance of these algorithms, the initial start-up test and the step change test were performed by using the dynamic model of a transformer cooling system. Test results showed that algorithms developed for this study were effective in controlling the oil temperature of a transformer cooling system.

• 설비공학논문집
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• 제6권1호
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• pp.54-65
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• 1994

Performance of naturally circulating cooling system of $SF_6$ gas charged transformer was simulated and the variations of gas flow rate, maximum coil temperature, gas temperature and cooling air temperature were investigated with respect to the height of radiator, interplates distance and heat generation rate at core. The results show that the height of radiator most significantly affects the performance of natural circulating cooling system of transformer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.61-64
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• 2001

Demand for development of 154kV Less-Flammable Power transformer is now increasing greatly instead of a oil-immersed transformer for preventing disasters and Less-flammability of substations. The most important point in developing Less-flammable transformer is cooling system. This paper describes the study on cooling characteristic of Less-flammable transformer.

• 전기학회논문지P
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• 제62권1호
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• pp.6-11
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• 2013

In this paper, the temperature characteristics of mold transformer for the distribution power system have been analyzed by using computational fluid dynamics(CFD). The model has been modeled by coil, cores, insulating materials and frames about 3MVA grade mold transformer and analyzed the temperature distribution of the structure with a heat fluid. The fluid, which is incompressible ideal gas, is analyzed as a turbulent flow phenomenon on the assumption that it is natural cooling of transformer cooling system. Through this study, by examining the temperature distribution and hot-spot of the structure field of the mold transformer, cooling design and temperature distribution information, which are demanded for designing are estimated.

• 전자공학회논문지 IE
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• 제49권2호
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• pp.40-45
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• 2012

본 논문은 전력용 변압기의 최적화된 온도제어를 위하여 부하율을 이용하여 권선최고점온도를 예측하고 냉각장치를 제어하는 방법을 제안하였다. 전력용 변압기의 최적화된 온도제어를 위하여, 하중함수를 사용하여 부하전류에 따른 부하율과 권선온도, 외기온도, 오일온도 등을 바탕으로 권선최고점온도를 예측하는 상관관계식을 제시한다. 또한, 이를 전력용변압기에 적용하여 제어한 결과를 제시한다.