DocumentCode
2930201
Title
Med-long term system structure forecasting of power consumption based on grey derived model
Author
Wu Yichun ; Cheng Zhenying ; Li Miao
Author_Institution
Training Center of Anhui Electr. Power Corp., Hefei, China
fYear
2013
fDate
15-17 Nov. 2013
Firstpage
142
Lastpage
146
Abstract
Med-long term load forecasting is the basis of power system planning. According to the characteristics and changing rules of the different types of electricity load and different demand side management strategies on them, electricity load structure forecasting for the research on power development and planning is very necessary. Based on the grey theory, this paper proposes a med-long term load structure forecasting model in which the system state equations and grey dynamic model group about various types of electricity load are established, in terms of the system dominant factors and associated factors determined by the grey correlative degree analysis method, and are solved to realize the med-long term structure forecasting of power consumption by means of the GM (1, N, x (0)) model derived from GM (1, N) model. The power consumption of actual grid is predicted in medium and long term in a case study utilizing the proposed model. The prediction results are analyzed and compared with the observed values of power consumption, which verifies the validity and practicality of the established med-long term load forecasting model.
Keywords
grey systems; load forecasting; power consumption; electricity load; grey correlative degree analysis method; grey derived model; grey dynamic model; med-long term load forecasting; med-long term system structure forecasting; power consumption; power system planning; system dominant factors; system state equations; Electricity; Forecasting; Industries; Load modeling; Mathematical model; Power demand; Predictive models; derived model; load structure forecasting; med-long term; power system planning;
fLanguage
English
Publisher
ieee
Conference_Titel
Grey Systems and Intelligent Services, 2013 IEEE International Conference on
Conference_Location
Macao
ISSN
2166-9430
Print_ISBN
978-1-4673-5247-5
Type
conf
DOI
10.1109/GSIS.2013.6714759
Filename
6714759
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