• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1875-1876
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• 2008

네트웍 모델러(Network Modeler)는 EMS 시스템에서 전력 네크워크 토폴로지(Network Topology)를 입력하기 위한 도구이다. 네트워크 모델러는 토폴로지 정보를 입력하여 모델을 생성하고 변경하는 일과 네트워크 다이어그램을 생성하는 일 등을 처리한다. 모델을 생성하기 위해 계통요소를 나타내는 심벌을 마우스로 움직여 화면에 배치하고 각 요소의 파라미터를 설정하며 작성된 전력계통 구성이 올바른지 검사하는 기능도 수행한다. 네트워크 모델러는 주로 EMS에서 사용되었고 SCADA 시스템에서는 사용되지 않았으나, 최근 개발되고 있는 SCADA 시스템은 네트워크 모델러를 함께 포함하여 시스템의 기능을 향상시키고 있다. 그러나 기존의 Network Modeler가 EMS 시스템 개발 벤더에 따라 다른 데이터 구조를 가지고 있어서 데이터의 상호 운용성이 떨어지고, 입력방법에 있어서도 자동화 및 자료 연계가 미흡하여 관리에 많은 시간이 소요되는 단점을 가지고 있다. 본 논문에서는 CIM 기반으로 정의된 데이터 모델을 사용자가 그래픽 다이어그램을 이용하여 쉽게 네트워크 토폴로지를 정의하도록 하고, 입력정보의 상호 운영성이 향상된 CIM 기반 Network Modeler를 설계한 내용을 설명하도록 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.7
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• pp.3152-3159
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• 2012

This paper presents the new instruction-level power model for an asynchronous processor. Until now, the various power models for estimating the power dissipation of embedded processor in SoC are proposed. Since all of them are target to the synchronous processors, the accuracy is questionable when we apply those power models to the asynchronous processor in SoC. To solve this problem, we present new power model for an asynchronous processor by reflecting the behavioral features of an asynchronous circuit. The proposed power model is verified using an implementation of asynchronous processor, A8051. The simulation results of the proposed model is compared with the measurement result of gate-level synthesized A8051. The proposed power model shows the accuracy of 90.7% and the simulation time for estimation the power consumption was reduced to 1,900 times.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1391-1397
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• 1992

Improved power law flow model was suggested for the calculation of wake flow characteristics around the three dimensional ship stern in case of the formation of bilge vortex in the direction of stern. In comparison with the power law and Coles flow model, the flow velocity calculated based on this study was delayed around the boundary of inner layer and outer layer in reverse flow. More accurate results was obtained with this improved power law flow model by the velocity calculation around ship stern. Accuracy was validated with the comparison of other calculation results and experimental datas.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1039-1048
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• 2013

Generally, the buck converter controller was designed to control output voltage of the converter. However, design of the controller in photovoltaic power conditioning system is different from general design. the controller in photovoltaic power conditioning system controls input voltage of the converter(output voltage of the solar cell) for MPPT(Maximum Power Point Tracking). This paper proposes novel buck converter model which can control input voltage of the converter. We integrate this model with a model of solar cell. and linearize at the operating point(MPP). In addition, we determine whether or not suitable for the general linear controller design into small and large signal analysis.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.335-344
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• 2018

The power model is needed to handle the power consumption of mobile AMOLED display at the software level. However, the existing studies to generate the power model have required the experimental environment and equipment for the power measurement activity. In addition, the combination of RGB values used for modeling was imprudent and small, so it was difficult to reflect the mutual influence between the RGB values into the model. To solve these problems, we propose an RGB color space partitioning method, which is used to prudently sample the combinations of the RGB values based on the color or the power. We also propose a process for generating a mapping table composed of . We analyzed the characteristics of the samples generated according to the proposed partitioning methods, taking into account the color and the power, and generated the mapping table for the AMOLED display. Furthermore, we confirmed the reusability of the mapping table by utilizing one mapping table multiple times in evaluating different power models. These mapping tables are provided to researchers and can be used to generate and evaluate power models without power measurement activities.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.158-160
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• 2001

본 논문은 PSCAD/EMTDC프로그램을 이용한 제주-해남 HVDC시스템의 해석모델 개발과 해석모델을 이용한 제주-해남 HVDC시스템의 운전특성에 대한 분석 내용을 기술하였다. 제주-해남 HVDC의 안정적인 운용을 위해서는 HVDC시스템의 이해와 함께 제주교류계통의 계통특성도 같이 고려되어야 한다. 이를 위해서는 제주-해남 HVDC와 제주교류계통을 포함하는 시뮬레이션 모델을 개발하여 다양한 상황에서의 시뮬레이션을 수행하여야 한다. 본 논문에서는 AC계통과 DC 계통의 상호작용에 의한 영향 분석과 교직연계계통의 계통운용 특성에 대해서 EMTDC 제주-해남 HVDC모델과 제주 AC계통 등가축약 모델을 이용하여 분석한 결과를 설명하였다. PSCAD/EMTDC는 EMTP와 더불어 전력시스템의 과도현상 해석을 위한 신뢰성 있는 프로그램이다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.211-218
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• 2012

Fossil fuel is used all over the world and it produces greenhouse gases due to fossil fuel use. Therefore, it cause global warming and is serious environmental pollution. In order to decrease the environmental pollution, we should use renewable energy which is clean energy. Among several renewable energy, wind energy is the most promising one. Wind power generation is does not produce environmental pollution and could not be exhausted. However, due to wind power generation has irregular power output, it is important to predict generated electrical energy accurately for smoothing wind energy supply. There, we consider use ramp characteristic to forecast accurate wind power output. The ramp increase and decrease rapidly wind power generation during in a short time. Therefore, it can cause problem of unbalanced power supply and demand and get damaged wind turbine. In this paper, we make prediction models using power ramp rate as well as wind speed and wind direction to increase prediction accuracy. Prediction model construction algorithm used multilayer neural network. We built four prediction models with PRR, wind speed, and wind direction and then evaluated performance of prediction models. The predicted values, which is prediction model with all of attribute, is nearly to the observed values. Therefore, if we use PRR attribute, we can increase prediction accuracy of wind power generation.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.307-314
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• 2022

Recently, researches using deep learning-based models are being actively conducted to replace statistical-based time series forecast techniques to predict electric power demand. The result of analyzing the researches shows that the performance of the LSTM-based prediction model is acceptable, but it is not sufficient for long-term regional-wide power demand prediction. In this paper, we propose a WaveNet deep learning model to predict electric power demand 24-hour-ahead with temperature data in order to achieve the prediction accuracy better than MAPE value of 2% which statistical-based time series forecast techniques can present. First of all, we illustrate a delated causal one-dimensional convolutional neural network architecture of WaveNet and the preprocessing mechanism of the input data of electric power demand and temperature. Second, we present the training process and walk forward validation with the modified WaveNet. The performance comparison results show that the prediction model with temperature data achieves MAPE value of 1.33%, which is better than MAPE Value (2.33%) of the same model without temperature data.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.9
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• pp.54-65
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• 1999

As the integration ratio and operating speed increase, it has become an important problem to estimate the dissipated power during the design procedure to reduce th TTM(time to market). This paper proposed a prediction model for the maximum dissipated power of a CMOS logic gate. This model uses a calculating method. It was constructed by including the characteristics of MOSFETs, the operational characteristics of the gate, and the characteristics of the input signals. As the construction procedure, a maximum power estimation model for CMOS inverter was formed first, And then, a conversion model to convert a multiple input CMOS gate into a corresponding CMOS inverter was proposed. Finally, the power model for inverter was applied to the converted result so that the model could be applied to a general CMOS gate. We designed several CMOS gates in layout level with $0.6{\mu}m$ design rule to apply both to HSPICE simulation and to the proposed models. The comparison between the two results showed that the gate conversion model and the power estimation model had within 5% and 10% of the relative errors, respectively. Those values show that the proposed models have sufficient accuracies. Also in calculation time, the proposed models were more than 30 times faster than HSPICE simulation. Consequently, it can be said that the proposed model could be used efficiently to estimate the maximum dissipated power of a CMOS logic gate during the design procedure.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.423-424
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• 2012

본 논문에서는 피크 전류 모드 제어를 적용한 플라이백 컨버터의 정확한 Control-to-Output Transfer Function을 제시한다. 기존 저주파 극점만으로 간략화 된 모델은 실제 디스크리트 모델(Discrete Model)과 소신호 해석에서 많은 차이를 보인다. 본 논문에서는 정확한 저주파 극점을 유도하고, PSIM을 통한 모의실험을 통해 제안된 모델에 대한 정확성을 검증한다.