DocumentCode :
2789515
Title :
Forecasting of fluctuations and turning points of power demand in China based on the maximum entropy method and ARMA model
Author :
Zhang Lizi ; Xu Limei
Author_Institution :
NCEPU Coll., China
fYear :
2010
fDate :
20-22 Sept. 2010
Firstpage :
1
Lastpage :
6
Abstract :
Influenced by the economic cycle, power demand in china shows some cyclical fluctuations, which is unhealthy for the development of national economy and production efficiency of electric power industry. Correctly forecasting the fluctuation rule of power demand and the turning points in China is helpful to make the corresponding strategy complied with the cycle. With the full consideration of power demand fluctuations, the paper establishes a forecasting model based on maximum entropy method and ARMA model: firstly, the paper makes a spectrum analysis on the growth rate of power demand and the major cycle of the cyclical fluctuations can be correspondingly obtained, then a periodic function which can reflect the fluctuation features is employed through the least square method; secondly, the paper establishes an ARMA model on the residual series which can be obtained by eliminating the periodic sequence from the original series; at last, the hybrid forecasting model is obtained by combining the periodic function and ARMA model. Experimental results show that the proposed model is effective and reasonable.
Keywords :
demand forecasting; electricity supply industry; least squares approximations; load forecasting; maximum entropy methods; ARMA model; electric power industry; fluctuations; hybrid forecasting model; least square method; maximum entropy method; power demand; turning points; Analytical models; Biological system modeling; Entropy; Fluctuations; Forecasting; Power demand; Predictive models; ARMA model; maximum entropy method; mid-long term load forecasting; power demand cycle; spectral density;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Critical Infrastructure (CRIS), 2010 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8080-7
Type :
conf
DOI :
10.1109/CRIS.2010.5617508
Filename :
5617508
Link To Document :
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