• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.675-683
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• 2015

In the 21st century, we now face the serious problems of the enormous consumption of the energy resources. Depending on the power consumption increases, both China and South Korea face a reduction in available resources. This paper considers the regression models and time-series models to compare the performance of the forecasting accuracy based on Mean Absolute Percentage Error (MAPE) in order to forecast the electricity demand accurately on the short-term period (68 months) data in Northeast China and find the relationship with Korea. Among the models the support vector regression (SVR) model shows superior performance than time-series models for the short-term period data and the time-series models show similar results with the SVR model when we use long-term period data.

• Journal of Integrative Natural Science
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• v.15 no.3
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• pp.99-110
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• 2022

Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.682-685
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• 2004

This paper investigated a method for classifying emotional states by using pulse wave signal. It focused on finding effective features for emotional state classification. The emptional states considered here consisted of interest and neutral. Classification experiments utilized 65 and 60 samples of interest and neutral states respectively. We have investigated 19 features derived from pulse wave signals by using both time domain and frequency domain analysis methods with 2 classifiers of minimum distance (normalized Euclidean distanece) and ${\kappa}$-Nearest Neighbour. The Leave-one-out cross validation was used as an evaluation mehtod. Based on experimental results, the most efficient features were a combination of 4 features consisting of (i) the mean of the first differences of the smoothed pulse rate time series signal, (ii) the mean of absolute values of the second differences of thel normalized interbeat intervals, (iii) the root mean square successive difference, and (iv) the power in high frequency range in normalized unit, which provided 80.8% average accuracy with ${\kappa}$-Nearest Neighbour classifier.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.16 no.4
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• pp.334-345
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• 2006

The objectives of this study were to analyze and compare 24 hrs personal exposure levels of MF at microenvironments such as home, school, educational institute, internet pc game room, transportation, and other places according to time activity patterns using various metrics for children attending the primary schools located near and away from the power lines, and to characterize the major microenvironments and impact factors attributed personal exposure level. The study was carried out for 44 children attending a primary school away from the lines(school A) and 125 children attending a school away from 154 kV power lines(school B), all who aged 12 years and were 6 grade, from July 2003 to December 2003. All participants filled in a questionnaire about characteristics, residence, use of electrical appliances and others. Children wore a small satchel in which EMDEX II and Lite (Enertech, Co. Ltd) and a diary of activity list for period of registration in 20 minutes blocks. All statistical calculations were made with the SAS System, Releas 6.12. The summary of results was presented below. First, about the characteristics of subjects, there no differences between two groups. The subject almost spent about 56 % of their time at home and about 20~25 % of their time at school. Fifty percent of children spent 2 hours at private educational institutes. Second, the personal exposure measurements of children in school B was statistically higher than those of children in school A by various metrics such as arithmetic mean, geometric mean, percentile(5, 25, 50, 75, 95), maximum, rate of change metric, constant field metric. The arithmetic and geometric mean magnetic fields during the time the children were at school B were 0.98 and $0.86{\mu}T$ and were about 23 times higher than those of children were at school A. In conclusion, the significant major determinants of personal exposure level is the distance from the power line to microenvironments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2113-2118
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• 2016

The precise detection of electric leakage point of underground power cable is very important to reduce cost and time of maintenance and prevent electric shock accident through expedite repair of electric leakage point. This paper proposes a electric leakage point detection system underground power cable using of half-period modulated transmission waveform and earth electric potential measurement. The developed system is composed of transmitter to generate the wanted pulse waveform, receiver to measure and display earth electric potential by the transmitted pulse in electric leakage point and PC Software program to display of GPS coordinate on detection cable line. The performance of the electric leakage point detection system was tested in the constructed underground cable leakage detection test bed. The test results on signal generation voltage precision of signal transmitter, mean detection earth voltage, mean detection leakage current and electric leakage point detection error showed the developed system can be used in electric leakage point detection underground power cable.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.511-518
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• 2009

We consider the problem of testing for change and estimating the unknown change-point in a sequence of time-ordered observations from the binomial and Poisson distributions. Including the likelihood ratio test, Gombay and Horvath (1990) tests are studied and the proposed change-point estimator is derived from their test statistic. A power study of tests and a comparison study of change-point estimators are done via simulation.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.684_685
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• 2009

A digital sampling algorithm that uses a two high resolution integrating Voltmeters which are synchronized by Phase Lock Loop (PLL) time clock for accurately measuring the parameters, active and reactive power, for sinusoidal power measurements is presented. The PLL technique provides high precision measurements, root mean square (rms), phase and complex voltage ratio, of the AC signal. The system has been designed to be used at the Korean Research Institute of Standards and Science (KRISS) as a reference power standard for electrical power calibrations. The test results have shown that the accuracy of the measurements is better than $10 {\mu}W/VA$ and the level of uncertainty is valid for the power factor range zero to 1 for both lead and lag conditions. The system is fully automated and allows power measurements and calibration of high precision wattmeters and power calibrators at the main power frequencies 50 and 60 Hz.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.8
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• pp.70-76
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• 2012

In this paper, we propose a power allocation scheme of the unlicensed user based on orthogonal frequency division multiplexing (OFDM) in the TV white space (TVWS). Power constraints in TVWS should be satisfied in the time domain. However, because OFDM has high PAPR (peak-to-average power ratio), it is difficult to satisfy power constraints of TVWS in the time domain. Furthermore, the conventional power allocation schemes cannot be generally applied to unlicensed user in TVWS. Therefore, we propose a power allocation scheme to satisfy power constraints of TVWS by reducing PAPR in the time domain. In addition, we analyze the capacity of the unlicensed user based on OFDM in a closed form. Based on the capacity analysis, as the number of subcarriers decreases, the capacity can be enhanced. In simulation results, we show that the capacity of the unlicensed user increases, as the number of subcarriers decreases and the mean of the channel between the transmitter and the receiver of the unlicensed user increases.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.548-556
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• 2005

Reliability evaluation of power distribution system is very important to both power utilities and customers. It present the probabilistic number and duration of interruption such as failure rate, SATDI, SAIFI, and CAIDI. However, it has a fatal weakness at reliability index because of accuracy of failure rate. In this paper, the Time-varying Failure Rate(TFR) of power distribution system equipment is extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) in Korea. For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential(random failure) and Weibull(aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate(MfR) through the comparison between TFR and MFR

• Architectural research
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• v.19 no.3
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• pp.71-77
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• 2017

Dynamic pricing refers to a system in which a tariff varies, according to a level of charging and applied time depending on time change. The power billing system used in the Korean Electric Power Corporation (KEPCO) is based on time of use (TOU) pricing, which is one of the dynamic pricing systems. This paper aimed to determine the operational results of a variable refrigerant flow system, to which a new control algorithm was applied, in order to respond to dynamic pricing, in summer and the utility of the new control. To do this, real measured data was acquired from a VRF system installed in a building for educational purposes, where dynamic pricing was applied for about 100 days during summer time. At the maximum load operation time period in TOU, the new control minimized operation within the indoor comfort range, an increase in refrigerant evaporation temperature in the indoor unit and the number of revolutions in a compressor in the outdoor unit was limited. As a result, power usage was decreased by 11%, and the operational cost by 14.6%. Furthermore, measurement results using the Predicted Mean Vote (PMV) model, that represented satisfaction of thermal environment, showed that 82.8% to 90.4% of the occupants of the building were satisfied during operation when the new control was applied.