Browse > Article
http://dx.doi.org/10.5207/JIEIE.2007.21.7.061

Various Models of Fuzzy Least-Squares Linear Regression for Load Forecasting  

Song, Kyung-Bin (숭실대학교 전기공학부)
Publication Information
Journal of the Korean Institute of Illuminating and Electrical Installation Engineers / v.21, no.7, 2007 , pp. 61-67 More about this Journal
Abstract
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.
Keywords
Load Forecasting; Fuzzy Least-Squares Linear Regression;
Citations & Related Records
연도 인용수 순위
  • Reference
1 윤용범외 3인, '전력수급계획 및 운용해석 종합시스템 개발에 관한 연구', 한국전력공사 전력연구원, Technical Report, TR.94YJ15.J1998.89, 1998년 12월
2 S. Rahman, and R. Bhatnagar, 'An Expert System Based Algorithm for Short-Term Load Forecast', IEEE Transactions on Power Systems, Vol. 3, No. 1, pp 50-55, 1987
3 A. G. Bakirtzis, V. Petridis, S. J. Kiartzis, M. C. Alexiadis, and A. H. Maissis, 'A Neural Network Short Term Load Forecasting Model for the Greek Power System', IEEE Transactions on Power Systems, Vol. 11, No. 2, pp. 858-863, May 1996   DOI   ScienceOn
4 R. Lamedica, A. Prudenzi, M. S, M. Caciotta, and V. Orsolini Cencelli, 'A Neural Network GBased Technique For Short-Term Forecasting of Anomalous Load Periods', IEEE Transactions on Power Systems, Vol. 11, No. 4, pp. 1749-1756, November 1996   DOI   ScienceOn
5 R. Campo and P. Ruiz, 'Adaptive Weather-Sensitive Short- Term Load Forecast,' IEEE Trans. on PWRS, Vol. PWRS-2, No.3, pp.592-600, Aug., 1987
6 Hiroyuki Mori, Hidenori Kobayashi, 'Optimal Fuzzy Inference for Short-Term Load Forecasting', IEEE Transactions on Power Systems, Vol. 11, No. 1, February 1996
7 구본석, 백영식, 송경빈, '퍼지 최소자승 선형회귀분석 알고리즘을 이용한 특수일의 전력수요예측', 대한전기학회 추계학술대회 논문집, pp. 51-53, 2001년 11월
8 김광호,'특수일 전력수요예측을 위한 퍼지 전문가시스템의 개발', 전기학회 논문지 47권, 제7호, pp. 886-891, 1998년 7월
9 D.H. Hong, S.H. Lee and H.Y. Do, 'Fuzzy Linear Regression Data Using Shape Preserving Operations', Fuzzy Sets and Systems, Vol 122, pp. 513-526, September 2001   DOI   ScienceOn
10 D.H. Hong and H.Y. Do and J.K. Song 'Fuzzy least-squares linear regression analysis using shape preserving operations', Fuzzy Sets and Systems Vol. 90, pp. 307-316, September 1997   DOI   ScienceOn
11 T. M. Peng, N. F. Hubele and G. G. Karady, 'An Adaptive Neural Network approach to One-Week Ahead Forecasting', IEEE Transactions on Power Systems, Vol. 8, pp. 1195-1203, August 1993   DOI   ScienceOn
12 K.H. Kim, J.K. Park, K.J. Hwang and S.H. Kim, 'Implementation of Hybrid Short-term Load Forecasting System Using Artificial Neural Networks and Fuzzy Expert Systems, 'IEEE Transactions on Power Systems, Vol. 10, No. 3, pp. 1534-1539, August 1995   DOI   ScienceOn
13 김광호, 황갑주, 박종근, 김성학, '단기전력 수요예측 전문가 시스템의 개발', 전기학회 논문지 47권, 3호, pp. 284-290, 1998년 3월
14 K.H. Kim 'Short- Term Load Forecasting for Special Days in Anomalous Load Conditions Using Neural Networks and Fuzzy Inference Method', IEEE Transactions on Power Systems, Vol. 15, No. 2, pp.559-565, May 2000   DOI   ScienceOn
15 D.H. Hong and H.Y. Do, 'Fuzzy Systems Reliability Analysis By The Use of Tw(the weakest t-norm ) on Fuzzy Number Arithmetic Operations', Fuzzy Sets and Systems Vol. 90, pp. 307-316, September 1997   DOI   ScienceOn
16 조현호, 백영식, 송경빈, 홍덕헌, '퍼지 선형회귀분석 알고리즘을 이용한 특수일 전력수요예측', 대한 전기학회 하계학술대회 논문집, pp. 298-300, 2000년 7월