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β - Casein 의 이차구조에 관한 chaotropic Salts 의 영향
송경빈,Srinivasan Damodaran ( Kyung Bin Song,Srinivasan Damodaran ) 생화학분자생물학회 1992 BMB Reports Vol.25 No.5
To elucidate the effect of chaotropic salts on the conformation of β-casein, CD studies of β-casein at various NaC1O₄ concentrations were performed. Addition of NaC1O₄ up to 1 M caused the increase of β-sheet content from 15 to 35% due to alteration of water structure. Reversibility experiments indicate that increased secondary structure of β-casein in the presence of chaotropic salt might be a form of non-classic sheet-like structure.
전력수요예측을 위한 다양한 퍼지 최소자승 선형회귀 모델
송경빈,Song, Kyung-Bin 한국조명전기설비학회 2007 조명·전기설비학회논문지 Vol.21 No.7
전력수요예측은 전력계통의 운용을 위해 필수적이다. 따라서 다양한 방법이 제시되어 왔으며, 특히 특수일의 수요예측은 평일과 구분되며, 부하 패턴을 축출하기에 충분한 자료 확보가 어려워 예측 오차가 크게 나타난다. 본 논문에서는 특수일의 부하예측 정확도를 개선하기 위해 퍼지 최소자승 선형회귀 모델을 분석한다. 4종류의 퍼지 최소자승 선형회귀 모델에 대해 분석과 사례연구를 통하여 가장 정확한 모델을 제시한다. The load forecasting has been an important part of power system Accordingly, it has been proposed various methods for the load forecasting. The load patterns of the special days is quite different than those of ordinary weekdays. It is difficult to accurately forecast the load of special days due to the insufficiency of the load patterns compared with ordinary weekdays, so we have proposed fuzzy least squares linear regression algorithm for the load forecasting. In this paper we proposed four models for fuzzy least squares linear regression. It is separated by coefficients of fuzzy least squares linear regression equation. we compared model of H1 with H4 and prove it H4 has accurately forecast better than H1.
송경빈(Song, Kyung-Bin) 대한전기학회 2022 전기의 세계 Vol.71 No.10
대한전기학회는 탄소중립의 필요성에 공감하여 2022년에 탄소중립 발전 방향을 제시하기 위해 백서를 발간할 예정이다. 백서는 탄소중립을 원활히 달성하는 과정에서 발생하는 피해와 부작용을 예방하고 최소화할 수 있는 사회 및 기술기반 구축에 기여할 것으로 예상된다. 대한전기학회의 탄소중립 발전 방향은 학회 회원 및 산학연 전문가의 의견을 수렴하여 제시될 예정이다.
송경빈(Kyung-Bin Song) 대한전기학회 2014 전기학회논문지 Vol.63 No.4
Short-term load forecasting(STLF) for electric power demand is essential for stable power system operation and efficient power market operation. We improved STLF method by using hourly temperature as an input data. In order to using hourly temperature to STLF algorithm, we calculated temperature-electric power demand sensitivity through past actual data and combined this sensitivity to exponential smoothing method which is one of the STLF method. The proposed method is verified by case study for a week. The result of case study shows that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.
평일 단기전력수요 예측을 위한 최적의 지수평활화 모델 계수 선정
송경빈(Kyung-Bin Song),권오성(Oh-Sung Kwon),박정도(Jeong-Do Park) 대한전기학회 2013 전기학회논문지 Vol.62 No.2
Short term load forecasting for electric power demand is essential for stable power system operation and efficient power market operation. High accuracy of the short term load forecasting can keep the power system more stable and save the power market operation cost. We propose an optimal coefficient selection method for exponential smoothing model in short term load forecasting on weekdays. In order to find the optimal coefficient of exponential smoothing model, load forecasting errors are minimized for actual electric load demand data of last three years. The proposed method are verified by case studies for last three years from 2009 to 2011. The results of case studies show that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.
송경빈(Kyung-Bin Song),임종훈(Jong-Hun Lim) 대한전기학회 2013 전기학회논문지 Vol.62 No.12
Short-term load forecasting for Chusok and New Year"s consecutive holidays is very difficult, due to the irregular characteristics compared with ordinary weekdays and insufficient holidays historical data. During consecutive holidays of New Year and Chusok, most of industries reduce their operation rates and their electrical load levels. The correlation between businesses" operation rates and their loads during consecutive holidays of New Year and Chusok is analysed and short-term load forecasting algorithm for consecutive holidays considering businesses" operation rates of industries is proposed. Test results show that the proposed method improves the accuracy of short-term load forecasting over fuzzy linear regression method.
송경빈(Kyung-Bin Song) 대한전기학회 2010 전기학회논문지 Vol.59 No.6
Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.