• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.371-373
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• 2001

In this paper, we present 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. Daily load patterns are classified by two methods dependent upon possession information. In case we possess daily load profiles make use of K-mean algorithm and in case we have not daily load profiles, make use of customer information of KEPCO. As the parameters of the load pattern classification, we use are daily load profiles and customer information of each distribution transformers. Data management system is used for NT oracle. We can present peak load magnitude, initial load magnitude and peak load duration for daily load patterns by 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. We think that this paper contributes to enhancing the distribution transformer overload criterion.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.475-485
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• 2017

This paper develops a conversion function and method transforming from daily peak load curve used $LOLE_D$ [days/year] to hourly load curve used $LOLE_H$[hours/year]and describes relationship between $LOLE_D$ [days/year] and $LOLE_H$ [hours/year]. The indices can not only be transformed just arithmetically but also have different characteristics physically because of using their different load curves. The conversion function is formulated as variables of capacity and forced outage rate of generator, hourly load daily load factor and daily peak load yearly load factor, etc. Therefore, the conversion function (${\gamma}={\varphi}$(.)) can not be simple. In this study, therefore, the function is formulated as linear times of separated two functions. One is an exponential formed conversion function of daily load factor. Another is formulated with an exponential typed conversion function of daily peak load yearly load factor. Futhermore, this paper presents algorithm and flow chart for transforming from $LOLE_D$[days/year] to $LOLE_H$[hours/year]. The proposed conversion function is applied to sample system and actual KPS(Korea Power System) in 2015. The exponent coefficients of the conversion functions are assessed using proposed method. Finally, assessment errors using conversion function for case studies of sample system and actual system are evaluated to certify the firstly proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.39-49
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• 2013

This paper presents a method of improving the performance of a day-ahead 24-h load curve and peak load forecasting. The next-day load curve is forecasted using radial basis function (RBF) neural network models built using the best design parameters. To improve the forecasting accuracy, the load curve forecasted using the RBF network models is corrected by the weighted sum of both the error of the current prediction and the change in the errors between the current and the previous prediction. The optimal weights (called "gains" in the error correction) are identified by differential evolution. The peak load forecasted by the RBF network models is also corrected by combining the load curve outputs of the RBF models by linear addition with 24 coefficients. The optimal coefficients for reducing both the forecasting mean absolute percent error (MAPE) and the sum of errors are also identified using differential evolution. The proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange. Simulation results reveal satisfactory forecasts: 1.230% MAPE for daily peak load and 1.128% MAPE for daily load curve.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.5
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• pp.37-40
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• 1995

In this paper, we investigate the daily load curve and yearly lighting hours of general and industrial Korean lighting apparatus. The daily load curve of lighting apparatus shows the peak use at 8 p.m. in general and 10 a.m. in industrial building. The yearly lighting hours are 2,948 hours in general and 4,066 hors in industrial building.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.689-698
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• 2011

In South Korea, Total Maximum Daily Load (TMDL) has been enforced since 2004 to restore and manage water quality in the watersheds. However, the appraisal of TMDL in South Korea has lots of weaknesses to establish the plan for recovery of water quality because it just evaluates the target water quality during the particular flow duration interval. In the United States, Load Duration Curve (LDC) method bas been widely used in the TMDL to evaluate the water quality and pollutant loads considering variation of stream flow. In a recent study, web-based Load Duration Curve system was developed to create the LDC automatically and provide the convenience of use. In this study, web-based Load Duration Curve system was applied in the Gapyeongcheon watershed using the daily flow and 8-day interval water quality data, and Q-L Rating Curve was used to evaluate the water quality and pollutant load in the watershed, also. As a result of study, water quality and pollutant load in Gapyeongcheon watershed were met with water quality standard and allocated load in the all flow durations. Web-based Load Duration Curve system could be applied to the appraisal of South Korean TMDL because it can be used to judge the impaired flow duration and build up the plan of load reduction, and it could enhance the publicity. But, web-based Load Duration Curve system should be enhanced through addition of load assessment tools such as Q-L rating curve to evaluate water quality and pollutant load objectively.

• Journal of Korean Society on Water Environment
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• v.28 no.6
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• pp.890-895
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• 2012

Duration curves describe the percentage of time that a certain water quality (total/fecal coliform (=TC/FC)) or discharge is exceeded. The curves methodology are usually based on daily records and are useful in estimating how many days per year and event will be exceeded. The technique was further applied to estimated TC/FC loading to the Geumho River, using the daily mean flow rate and TC/FC concentration data during January, 2001 and December, 2011 for the Geumhogang6 (=Seongseo water level station) where an automated monitoring station is located in Gangchang-bridge. Low flow of the Seongseo (=11.1 cms) was equivalent to 75.3% on an exceedance probability scale. Load Duration curve for TC/FC loading at the Seongseo was constructed. Standard load duration curve was constructed with the water quality criteria for class III (TC/FC concentration = 5000/1000 CFU/ 100 mL). By plotting TC/FC observed load duration curve with standard load duration curve, it could be revealed that water quality do not meet the desired water quality for 68.8/11.2% on an exceedance probability scale. IF linear correlation between flow rate and coliform concentration is assumed, it can be interpreted that water quality exceed desired criteria when daily average flow rate is over 11.9/109.9 cms.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.97-109
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• 2018

The LDC (Load Duration Curve) method can analyze river water quality changes according to flow rate and seasonal conditions. It is also possible to visually recognize whether the target water quality is exceeded or the size of the reduction load. For this reason, it is used for the optimal reduction of TPLCs and analysis of the cause of water pollution. At this time, the flow duration curve should be representative of the water body hydrologic curve, but if not, the uncertainty of the interpretation becomes big because the damaged flow condition is changed. The purpose of this study is to estimate the daily mean flow of the unit watershed using the HSPF model and to analyze the difference of the flow duration curves according to the cumulative daily mean flow rate using the NSE technique. The results show that it is desirable to construct the flow duration curve by using the daily average flow rate of at least 5 years although there is a difference by unit watershed. However, this is the result of the water bodies at the end of Han River basin watershed, so further study on various water bodies will be necessary in the future.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.163-165
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• 1996

In this paper, we are proposed development of electric energy method and load curve. A daily electric energy is forecasted using artificial neural network. The load curve is obtained by combining forecasted electric energy and typical daily load patterns which are classified using KSOM and Fuzzy system. As a result, we know that we could get more accurate results and easier application than the results from based on the hourly historical data.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.166-166
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• 2017

현재 우리나라에서 많은 연구에 활용되고 있는 오염부하지속곡선(Load duration curve, LDC)은 단일 기준유량의 문제점을 개선하기 위해 전체 유량 범위를 고려한 수질오염총량관리제(Total Maximum Daily Loads, TMDL) 평가 기법으로 개발되었다(Choi et al., 2012). LDC를 이용해 목표수질 달성여부를 분석하기 위해서는 일유량자료를 바탕으로 유량지속곡선(Flow Duration Curve, FDC)의 작성이 선행되어야 하는데(Park and Oh, 2012), 365일 연속적으로 측정된 실측 자료를 이용하는 것이 가장 확실하고 정확한 방법이다. 그러나 현재 환경부에서는 총량관리 단위유역에서 8일 간격으로 실측 유량 및 수질 측정이 이루어지고 있고, 특히 주로 비강우 시에 측정이 이루어지고 있는 실정이기 때문에 고유량에 대한 모니터링 자료가 부족한 실정이다. 이 같은 이유로 많은 연구에서 불연속적인 평균 8일 간격 유량을 그대로 사용하거나 일유량자료를 확보하기 위해 다양한 방법을 이용하고 있다. 그러나 이러한 유량자료의 변동은 유랑지속곡선에 변화를 주고 결과적으로는 LDC를 이용한 목표수질 달성여부를 판단함에 있어 불확실성이 있다. 이에 본 연구의 목적은 환경부 총량측정망 8일유량자료와 이와 연계성이 있는 국토교통부 하천유량 측정망 일유량자료를 이용하여 각각의 LDC를 작성하고, 이러한 일유량과 8일유량 사용이 LDC를 이용하여 목표수질에 대한 오염부하 특성분석에 어떠한 영향을 미치는지 유량 조건별로 차이를 비교분석하는 데 있다.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.224-231
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• 2012

It is necessary to develop flow duration curve (FDC) on each unit watershed in order to analyze flow conditions in the stream for the management of Total Maximum Daily Loads (TMDLs). This study investigated a simple method to develop FDC for the general use of the curve. A simple equation for daily flow estimation was derived from the regression analysis between the 8-day interval flow data of a unit watershed and the daily flow monitoring data of an adjacent upstream region. FDC can be prepared with the calculation of daily flow by the equation for each unit watershed. An annual and a full-period FDC were drawn for each unit watershed in Guem river basin. Standard flow such as low and ordinary flow can be obtained from the annual FDC. Major percentile of flow such as 10, 25, 50, 75 or 90% can be obtained from the full-period FDC. It is considered that this simple method of developing FDC can be utilized more widely for the calculation of standard flow and the assessment of water quality in the process of TMDLs.