• 전기학회논문지
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• 제66권3호
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• pp.493-499
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• 2017

This paper proposes a combined very-short-term and short-term multi-variate time-series model for 24 hour load forecasting. First, the best model for very-short-term and short-term load forecasting is selected by considering the least error value, and then they are combined by the optimal forecasting time. The actual load data of industry complex is used to show the effectiveness of the proposed model. As a result the load forecasting accuracy of the combined model has increased more than a single model for 24 hour load forecasting.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3878-3887
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• 2022

For the future energy-mix policy for carbon neutrality, demand for the capability of load-follow operation has emerged in nuclear power plants in order to accommodate the intermittency of renewable energy. The short-term decay heat analysis is also required to evaluate the decay heat level varied by the power level change during the load-follow operation, which is a very important parameter in terms of short-term decay heat removal during a grace time. In this study, the short-term decay heat level for 10 days after the shutdown was evaluated for both seasonal and daily load-follow cases. Additionally, the nuclide-wise contribution to the accumulated decay heat for 10 days was analyzed for further understanding of the short-term decay heat behavior. The result showed that in the seasonal case, the decay heat level was mainly determined by the power level right before the shutdown and the amount of each nuclide was varied with the power variation due to the long variation interval of 90 days. Whereas, in the daily case, the decay heat level was strongly impacted by the average power level during operation and meaningful mass variations for those nuclides were not observed due to the short variation interval of 0.5 days.

• Journal of Korean Biological Nursing Science
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• 제22권2호
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• pp.111-118
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• 2020

Purpose: The purpose of this study was to understand the impact of long- and short-term energy drinks on anxiety-like, depressionlike, and cognitive behavior in adolescent rats. Methods: Adolescent rats (age six weeks) were randomly classified into a control group (CON), a long-term administration group (LT), and a short-term administration group (ST). The LT group was orally administered 1.5 mL/100 g (body weight) of energy drink twice daily for 14 days, the ST group was orally administered for one day, and the control group applied the same amount of normal saline. Later, an open-field test, a forced swim test, novel object recognition test, and an 8-arm radial maze test was conducted to assess the rats' anxiety, depression, and cognitive function. Results: There were different effects in the long- and short-term groups of energy drink administration. In the LT group, anxiety- and depressive-like behavior increased because of increased movement in the side corner and decrease of immobility time. Also, the time to explore novel objects decreased, and the number of correct responses was reduced, indicating a learning and memory function disorder. However, the ST group was not different from the control group. Conclusion: These results indicate that long-term consumption of energy drinks can increase anxiety-like, depression-like behavior, and this can lead to decrease in learning and memory functions. Thus, nurse and health care providers should understand the impact of energy drink consumption in adolescence to provide appropriate practices and education.

• 음성과학
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• 제3권
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• pp.156-166
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• 1998

In this paper, I would like to propose a dividing method by estimating the inflection points and the average magnitude energy in speech signals. The method proposed in this paper gave not only a satisfactory solution for the problems on dividing method by zero-crossing rate, but could estimate the feature of the transient period after dividing the starting point and transient period in speech signals before steady state. In the results of the experiment carried out with monosyllabic speech, it was found that even through speech samples indicated in D.C. level, the staring and ending point of the speech signals were exactly divided by the method. In addition to the results, I could compare with the features, such as the length of transient period, the short term energy, the frequency characteristics, in each speech signal.

• 한국태양에너지학회 논문집
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• 제33권5호
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1480-1491
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• 2015

In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a three-layered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible. The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models

• 대한전기학회논문지:시스템및제어부문D
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• 제50권12호
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• pp.590-596
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• 2001

The pre-emphasis is an essential process for speech signal processing. Widely used two methods are the typical method using a fixed value near unity and te optimal method using the autocorrelation ratio of the signal. This study proposes a new pre-emphasis method using the short-term energy difference of speech signal, which can effectively compensate the glottal source characteristics and lip radiation characteristics. Using the proposed pre-emphasis, speech analysis, such as spectrum estimation, formant detection, is performed and the results are compared with those of the conventional two pre-emphasis methods. The speech analysis with 5 single vowels showed that the proposed method enhanced the spectral shapes and gave nearly constant formant frequencies and could escape the overlapping of adjacent two formants. comparison with FFT spectra had verified the above results and showed the accuracy of the proposed method. The computational complexity of the proposed method reduced to about 50% of the optimal method.

• 전기학회논문지
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• 제59권11호
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• pp.1956-1963
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• 2010

Studies on the development of various energy management programs and real-time bidirectional information infrastructures have been actively conducted to promote the reduction of power demands and CO2 emissions effectively. In the conventional energy management programs, the demand response program that can transition or transfer the power use spontaneously for power prices and other signals has been largely used throughout the inside and outside of the country. For measuring the effect of such demand response program, it is necessary to exactly estimate short-term loads. In this study, the power consumption patterns in both individual and group consumers were analyzed to estimate the exact short-term loads, and the relationship between the actual power consumption and seasonal factors was also analyzed.

• 기술혁신연구
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• 제23권4호
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• pp.89-121
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• 2015

최근 에너지 정책이 장기화되는 이유는 에너지 정책에 영향을 주는 변수가 증가하고 이러한 변수가 갖는 영향력의 불확실성이 높아짐에 따라, 단기적 단편적 접근을 통해 에너지 이슈에 대한 근본적인 대처가 어려워졌기 때문이다. 에너지 정책을 장기적 관점에서 다루기 위해서는 기존과는 다른 거버넌스적 접근이 필요하며, 이와 같은 맥락에서 전환이론을 에너지 정책에 적용하기 위한 연구가 활발히 진행되고 있다. 본 연구는 네덜란드의 전환관리 모델과 에너지 전환사례를 바탕으로 수정된 전환관리 모델을 제시하고, 이를 기반으로 우리나라 에너지 정책의 시스템 전환적 특성을 평가하는 것을 목적으로 한다. 분석 결과 우리나라의 에너지 정책형성 과정에 전환적 사고가 폭넓게 확산되어 가고 있으나, 정책집행 과정을 중심으로 효과적인 전환관리를 위해 대응해야할 과제도 존재하고 있음을 확인하였다.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1304-1310
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• 2015

In remote islands, due to expense of existing generation systems, installation of photovoltaic cells (PVs) and wind turbines has a chance of reducing generation costs. However, in island power systems, even short-term power fluctuations change the frequency of grids because of their small inertia constant. In order to compensate power fluctuations, the authors proposed the power consumption control of pumps which send water to tanks. The power control doesn’t affect water users’ convenience as long as tanks hold water. Based on experimental characteristics of a pump system, this paper shows methods to determine reference power consumption of the system with compensation for short-term PV fluctuations while satisfying water demand. One method uses a PI controller and the other method calculates reference power consumption from water flow reference. Simulations with a PV and a pump system are carried out to find optimum parameters and to compare the methods. Results show that both PI control method and water flow calculation method are useful for satisfying the water demand constraint. The water demand constraint has a little impact to suppression of the short-term power fluctuation in this condition.