• 신재생에너지
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• 제10권2호
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• 설비공학논문집
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• 제23권4호
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• pp.265-272
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• 2011

The electrical load profiles of end-users must be analysed properly to introduce distributed generation system efficiently. In this study, numerical simulation for predicting a residential electrical load profile was developed to satisfy categorized electricity consumption range. We applied bottom-up approach to compose electrical load profile by using data from official reports and statistics. The electrical load profile produced from the simulation predicted peak times of public report accurately and agreed well with the standard residential electrical load profile of official reports within average error of 16.2%.

• 전기학회논문지P
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• 제63권4호
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• pp.295-300
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• 2014

The frequency is an important operating parameter of a power system. There is an increasing importance of constant monitoring of frequency to achieve stable power supply by WAMS(wide area monitoring system) and FNET(Frequency Monitoring Network). This paper is part of development of a network-based frequency monitoring and failure prediction system for wide-area intelligent protection relaying. In this paper, analysis of propagation speed of power frequency by generation drop using the PSS/E was carried out. For dynamic analysis, the 11 metropolitan areas offices of KEPCO divided into five groups of Seoul, Gangwon, Chungcheong, Honam, and Yeongnam group, study was performed.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권9호
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• pp.567-569
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• 2005

NARX(Nonlinear AutoRegressive with eXogenous input) neural network was used for prediction of nuclear reactor behavior which was influenced by control rods in short-term period and also by the concentration of xenon and boron in long-term period in load following operations. The developed model was designed to predict reactor power, xenon worth and axial offset with different burnup states when control rods and boron were adjusted in load following operations. Data of the Korea Next Generation PWR were collected by ONED94 code. The test results presented exhibit the capability of the NARX neural network model to capture the long term and short term dynamics of the reactor core and the developed model seems to be utilized as a handy tool for the use of a plant simulation.

• 통합자연과학논문집
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• 제12권1호
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• pp.20-23
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• 2019

Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

• 천문학회보
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• 제44권1호
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• pp.82.3-82.3
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• 2019

In this study, we generate future full disk magnetograms in 12, 24, 36 and 48 hours advance from SDO/HMI images using deep learning. To perform this generation, we apply the convolutional generative adversarial network (cGAN) algorithm to a series of SDO/HMI magnetograms. We use SDO/HMI data from 2011 to 2016 for training four models. The models make AI-generated images for 2017 HMI data and compare them with the actual HMI magnetograms for evaluation. The AI-generated images by each model are very similar to the actual images. The average correlation coefficient between the two images for about 600 data sets are about 0.85 for four models. We are examining hundreds of active regions for more detail comparison. In the future we will use pix2pix HD and video2video translation networks for image prediction.

• 항공우주기술
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• 제13권1호
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• pp.44-54
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• 2014

본 논문에서는 3구 추력기 2모듈 형태의 추력기시스템 기준으로 발사체 상단 자세제어용 추력기시스템 명령생성방식 2가지를 제시한다. 하나는 혼합오차함수를 이용하는 방식이고, 다른 하나는 명령혼합함수를 이용하는 방식이다. 시뮬레이션을 통해 두 방식을 비교 분석한 결과, 제어축 간의 상호 간섭, 각축 제어기의 독립적인 설계와 분석 용이성, 비행성능 예측 가능성 등의 관점에서 명령혼합 알고리듬이 상대적으로 유리함을 보인다.

• 한국유체기계학회 논문집
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• 제1권1호
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• pp.7-16
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• 1998

An interactive mode of grid generation system has been developed for a Navier-Stokes design procedure of axial flow compressors. The present grid generator adopts the multiblock H-grid structure, which simplifies the creation of computational grids about complex turbomachinery geometries and facilitate the manipulation of multiple grid blocks for multirow flow fields. The numerical algorithm adopts the combination of the algebraic and elliptic method to create the internal grids efficiently and quickly. The system consists of four separated modules, which are linked together with a common graphical user interface. The system input is made of the results of the preliminary design. The final grids generated from each module of the system are used as the preprocessor for the performance prediction of the two-or three-dimensional flow simulation inside the blade passage. Application to the blade design of the LP compressor was demonstrated to be very reliable and practical in support of design activities. This customized system are coupled strongly with the design procedure of the turbomachinery cascades using the Navier-Stokes technique.

• 한국유체기계학회 논문집
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• 제16권1호
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• pp.11-16
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• 2013

A numerical study was conducted to improve the performance of an impeller of centrifugal compressor. Nine design variables were chosen with constraints. Only meridional contours and blade profile were adjusted. ANN (Artificial Neural Net) was adopted as a main optimization algorithm with PSO (Particle Swarm Optimization) in order to reduce the optimization time. At first, ANN was learned and trained with the design variable sets which were obtained using DOE (Design of Experiment). This ANN was continuously improved its accuracy for each generation of which population was one hundred. New design variable set in each generation was selected using a non-gradient based method of PSO in order to obtain the global optimized result. After $7^{th}$ generation, the prediction difference of efficiency and pressure ratio between ANN and CFD was less than 0.6%. From more than 1,200 design variable sets, a pareto of efficiency versus pressure ratio was obtained and an optimized result was selected based on the multi-objective function. On this optimized impeller, the efficiency and pressure ratio were improved by 1% and 9.3%, respectively.

• 한국세라믹학회지
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• 제42권12호
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• pp.846-853
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• 2005

For the performance prediction of a planar-type solid oxide fuel cell, the computational analysis of transport phenomena with a simplified treatment of heat generation by the electrochemical reaction is conducted. From the result of the computational analysis, it is shown that the electrochemical reaction is closely related to the transport phenomena inside a solid oxide fuel cell. Transport phenomena including heat and mass transfer influences on the distribution of local current density and, as a result, on the performance characteristics of the fuel cell. Computational analysis is also extended to the parametric study to investigate the performance behavior of the fuel cell with different amount of supplied fuel flow rates. It is also demonstrated that the mathematical formulation and computational procedures proposed in this study can be applied to prove the importance of the specific TPB area in the manufacturing process of electrodes in solid oxide fuel cells.