Title :
Study of daily peak load forecasting by structured representation on genetic algorithms for function fitting
Author :
Kato, S. ; Yukita, K. ; Goto, Y. ; Ichiyanagi, K.
Author_Institution :
Aichi Inst. of Technol., Japan
Abstract :
In recent years, electric power systems have become more and more complex and large-scale. Therefore, we thought that electric power demand forecasting is required. This paper presents a method of a daily peak load forecasting by STROGANOFF (structured representation on genetic algorithms for non-linear function fitting). The STROGANOFF is a hierarchical technique of multiple regression analysis method and GA-based search strategy. The proposed method is demonstrated by using the data of Chubu district in Japan.
Keywords :
genetic algorithms; load forecasting; power consumption; power system planning; statistical analysis; Japan; STROGANOFF method; daily peak load forecasting; electric power system; genetic algorithms; multiple regression analysis method; nonlinear function fitting; power demand forecasting; search strategy; Data handling; Demand forecasting; Equations; Genetic algorithms; Large-scale systems; Load forecasting; Power generation economics; Power systems; Regression analysis; Weather forecasting;
Conference_Titel :
Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES
Print_ISBN :
0-7803-7525-4
DOI :
10.1109/TDC.2002.1176854
