DocumentCode :
1652211
Title :
Middle-long Power Load Forecasting Based on Genetic Algorithm
Author :
Dongxiao, Niu ; Jinchao, Li ; Jinying, Li ; Da, Liu
Author_Institution :
North China Electr. Power Univ., Beijing
fYear :
2007
Firstpage :
790
Lastpage :
793
Abstract :
Middle-long forecasting of electric power is the guarantee for the healthy development of the electric industry. In this paper, several forecasting methods are measured by several indexes, and then the entropy method is used to form a comprehensive index to set up the object function of genetic algorithm. Next the genetic algorithm is used to calculate the weight of every forecasting method. At last, we get the final result by adding all the results of every forecasting method. Example in this paper shows that this method will improve the accuracy of middle-long forecasting of electric power and decrease the forecasting risk.
Keywords :
electricity supply industry; genetic algorithms; load forecasting; comprehensive index; electric industry; entropy method; genetic algorithm; middle-long electric power load forecasting; object function; Economic forecasting; Energy management; Entropy; Genetic algorithms; Industrial economics; Load forecasting; Power generation economics; Predictive models; Entropy; Error index; Genetic algorithm; Power load forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
Type :
conf
DOI :
10.1109/CHICC.2006.4347372
Filename :
4347372
Link To Document :
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