• 한국조명전기설비학회지:조명전기설비
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• 제11권5호
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• pp.62-66
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• 1997

본 논문에서는 평일환산비를 사용하여 단기부하를 상정하는 알고리즘을 제시한다. 평일환산비로 주 주기성을 제거하고, 5개의 상정구간과 3 형태의 중회귀모델을 구성한다. 상정결과 상정도가 2.8〔%〕정도로 양호한 결과를 얻었다. 이로서 특수일(주말)부하의 전력수요상정도 가능하게 되었다. 중회귀 모델을 이용한 전력수요상정시의 큰 문제점인 특수일(주말)의 전력수요를 상정하는 방법이 제시됨으로서 상정도의 향상은 물론 신뢰성있는 상정모델의 구성이 가능하게 되었다.

• 융합신호처리학회논문지
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• 제2권3호
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• pp.73-78
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• 2001

특수일 부하를 예측하기 위하여 BP 신경회로망 모형과 다중 회귀모형을 구성한다. 신경회로망 모형은 패턴 변환비를 이용하고, 다중회귀 모형은 평일 환산비를 이용하여 특수일 부하를 예측한다. 주간 피크 부하예측 모형에 패턴 변환비를 이용하여 짧고 긴 특수일 부하를 예측 한 결과 주간 평균 오차율이 1∼2[%]로 나와 본 기법의 적합성을 확인할 수 있다. 하지만, 패턴 변환비 방법으로는 하계의 특수일 부하 예측은 어려웠다. 따라서 기온-습도, 불쾌지수 등을 설명변수로 하는 다중 회귀 모형을 구성하고 평일 환산비를 이용하여 하계의 특수일 부하를 예측한다. 평일만의 예측 모형과 예측 결과를 비교해 보면 월 평균 오차율이 비슷하게 나와 이용한 방법의 적합성을 확인하였다. 그리고, 통계적 검정을 통해 구성한 예측 모형의 유효성을 입증할 수 있었다. 이로서 본 연구에서 제시한 특수일 부하를 예측하는 기법의 적합성을 확인함으로서 피크 부하 예측시 큰 난점 중의 하나가 해결되었다.

• 대한전기학회논문지
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• 제45권4호
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• pp.511-516
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• 1996

In this paper, weekly maximum power demand forecasting method in consideration of temperature estimation using a time series model was presented. The method removing weekly, seasonal variations on the load and irregularities variation due to unknown factor was presented. The forecasting model that represent the relations between load and temperature which get a numeral expected temperature based on the past 30 years(1961~1990) temperature was constructed. Effect of holiday was removed by using a weekday change ratio, and irregularities variation was removed by using an autoregressive model. The results of load forecasting show the ability of the method in forecasting with good accuracy without suffering from the effect of seasons and holidays. Percentage error load forecasting of all seasons except summer was obtained below 2 percentage. (author). refs., figs., tabs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1177-1179
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• 1997

In this paper, short-term power demand forecast using exclusion of week periodicity presented. Week periodicity excluded from weekday change ratio. Forecast term of five and multiple regression model of the three form was composed. Forecast result was good. Therefore, It Could be the power demand forecast of special day(weekend). This method may contribute improvement of forecast accuracy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.295-297
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• 2000

In case of power demand forecasting the most important problem is to deal with the load of special-days, Accordingly, this paper presents a method that forecasting special-days load with regression models and neural networks. Special-days load in summer season was forecasted by the multiple regression models using weekday change ratio Neural networks models uses pattern conversion ratio, and orthogonal polynomial models was directly forecasted using past special-days load data. forecasting result obtains % forecast error of about $1{\sim}2[%]$. Therefore, it is possible to forecast long and short special-days load.

• 대한가정학회지
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• 제27권1호
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• pp.111-126
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• 1989

The aim of the present study is to research into the household work time change and its structure in urban home makers by the choosen eleven studies and KBS's Data 1981, 1983, 1985, 1987. This study were proceeded under some limitations, it is choosen eleven studies that is different region: large city, medium and small town, and the household work's categories of original auther were changed. And KBS's Data was composed of general formation without personal character of home maker: FLC, number of childeren, family type, education, region. Although this study have a certain meaning of implementation, research into the household work time change and its's structure. The major findings of this study can be autlined as follows: (1) Total household work time did'nt so much changed through the choosen eleven studies compared with the last twenty years ago. In the change of each province household work time, time connected with meals and dwelling did not showed consistancy of change. But cloth laundering and mending time of 80's were declined compared with 70's. Family care time of 80's was increased, home management and buying time was declined untill '85, but again increasing trend '87. In choosen eleven studies, the household work time structure of urban home makers can be outlined: time connected with Meals>Family care>Cloth laundering and mending>Dwelling>Home management and Buying. (2) KBS's time-series data were analized as follows: a) Total household work time of '87 was declining gradually in weekday (34 minutes), sat. (41 minutes), sun (1 house and 2 minutes) compared with '81. b) The change of each province household work time: the time of cooking and sewing home management were declining gradually in its Mean time and its ratio of acters. The acter ratio of household worker in '81, '83, '85 was composed Cooking > Cleaning > Laundering > Home management > Buying > Child care > Sewing. In '87 was composed Cooking > Cleaning > Laundering > Buying > Home management > Child care > Sewing. c) The structure of household work time revealed some differences in each year and a day of the week.