• 한국조명전기설비학회지:조명전기설비
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• 제9권5호
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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.

• 전기전자학회논문지
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• 제4권2호
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• pp.233-240
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• 2000

This paper presents fuzzy clustering and wavelet transform analysis based technique for the industrial hourly load forecasting fur the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using fuzzy clustering and then wavelet transform is adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed composite model of fuzzy clustering and wavelet transform approach can be used as an attractive and effective means for the industrial hourly peak load forecasting.

• 전기학회논문지
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• 제68권1호
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• pp.27-35
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• 2019

There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

• 전기학회논문지
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• 제65권5호
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• pp.718-723
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• 2016

The temperature changes are very important in improving the accuracy of the load forecasting during the summer. It is because the cooling load in summer contribute to the increasing of the load. This paper proposes a weekend load forecasting algorithm using the temperature change characteristic in a summer of Jeju. The days before and after weekends in Jeju, when the load curves are quite different from those of normal weekdays. The temperature change characteristic are obtained by using weekends peak load and high temperature data. And load forecasted based on the sensitivity between unit temperature changes and load variations. Load forecast data with better accuracy are obtained by using the proposed temperature changes than by using the ordinary daily peak load forecasting. The method can be used to reduce the error rate of load forecast.

• 인터넷정보학회논문지
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• 제21권5호
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• pp.119-127
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• 2020

국내 전기차 (EV: Electric Vehicle) 시장이 성장함에 따라, 빠르게 증가하는 EV 충전 수요에 대응하기 위한 충전설비의 확충이 요구되고 있다. 이와 관련하여, 종합적인 설비 계획을 수립하기 위해서는 미래 시점의 충전 수요량을 예측하고 이를 바탕으로 전력설비 부하에 미치는 영향을 체계적으로 분석하는 것이 필요하다. 본 논문에서는 한국전력공사의 EV 충전 데이터를 이용하여 충전소 단위의 일별최대부하를 예측하는 LSTM(Long Short-Term Memory) 신경망 모델을 설계 및 개발한다. 이를 위해, 먼저 데이터 전처리 및 이상치 제거를 통해 정제된 데이터를 얻는다. 다음으로, 충전소 단위의 일별 특징들을 추출하여 훈련 데이터 집합을 구성하여 일별 최대 전력부하 예측 모델을 학습시킨다. 마지막으로 충전소 유형 별 테스트 집합을 이용한 성능 분석을 통해 예측 모델을 검증하고 이의 한계점을 논의한다.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.948-953
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• 2002

The electric power load during the peak time in summer is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice-storage system and heat pump system are possible solutions to settle this problem. In this study. the method of estimating temperature and humidity to forecast the cooling load of ice-storage system is suggested, then the method of forecasting the cooling load using fuzzy logic is suggested by simulating that the cooling load is calculated using actual temperature and humidity. The forecast of the temperature, humidity and cooling load are simulated, and it is shown that the forecasted data approach to the actual data. Operating the ice-storage system by the forecast of cooling load with night electric power will improve the ice-storage system efficiency and reduce the peak electric power load during the summer season as a result.

• 스마트미디어저널
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• 제8권4호
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• pp.72-79
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• 2019

The automated demand response (DR) program encourages consumers to participate in grid operation by reducing power consumption or deferring electricity usage at peak time automatically. However, successful deployment of the automated DR program sphere needs careful assessment of appliances load profile (ALP). To this end, the recent method estimates frequency, consistency, and peak time consumption parameters of the daily ALP to compute their potential score to be involved in the DR event. Nonetheless, as the daily ALP is subject to varying with respect to the DR time ALP, the existing method could lead to an inappropriate estimation; in such a case, inappropriate appliances would be selected at the automated DR operation that effected a consumer comfort level. To address this challenge, we propose a more proper method, in which all the three parameters are calculated using ALP that overlaps with DR time, not the total daily profile. Furthermore, evaluation of our method using two public residential electricity consumption data sets, i.e., REDD and REFIT, shows that our energy management systems (EMS) could properly match a DR target. A more optimal selection of appliances for the DR event achieves a power consumption decreasing target with minimum comfort level reduction. We believe that our approach could prevent the loss of both utility and consumers. It helps the successful automated DR deployment by maintaining the consumers' willingness to participate in the program.

• 전기학회논문지
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• 제65권7호
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• pp.1115-1120
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• 2016

This paper presents the daily load forecasting for special days considering the rate of operation of industrial consumers. The authors analyzed the power consumption pattern for both the special and ordinary days according to the contract power classification of industrial consumers, and selected 400~600 specific consumers for which the rates of operation during special days are needed. Load forecasting for 2014 special days considering the rate of operation of industrial consumers showed a noticeable improvement on forecasting error of daily peak demand, which proved the effectiveness of the survey for the rates of operation during special days of industrial consumers.

• 대한전기학회논문지
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• 제32권3호
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• pp.69-75
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• 1983

This paper presents a improved algorithm for the generating capacity reliability evaluation using the frequency and duration approach. One of the specific feature of this algorithm is that propose the cumulative state load model via analytic expression of load duration curve and cumulative load frequency characteristic in conside ration of daily peak load. The paper illustrates the utilization of the proposed algorithm in actual system studies using the generating system of KEPCO. The results presented will provide a valuable reference for maintaining and planing the generating system.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2005년도 동계학술발표대회 논문집
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• pp.199-204
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• 2005

The decrease of summer peak electric load of our country is very important. The government is arranging a lot of support policies and statutes. etc. to decrease of peak electric load. And ice storage system is known as one of the alternatives. The purpose of this study is to collect basic data for operating characteristics to plan the most suitable operation of capsule-type ice storage system. The storaging tank is designed to take charge 40% of total cooling load in building, In operation condition the storage tank took charge 50%. Coefficient Of Performance of daily screw refrigerator is around 4.