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Optimized Rolling Grey Model for Electricity Consumption and Power Generation Prediction of China.

Authors :
Miaomiao Wang
Qingwen Luo
Lulu Kuang
Xiaoxi Zhu
Source :
IAENG International Journal of Applied Mathematics. Dec2019, Vol. 49 Issue 4, p577-587. 11p. 1 Diagram, 9 Charts, 9 Graphs.
Publication Year :
2019

Abstract

As the largest developing country in the world, China is currently facing the contradiction between power supply shortage and demand growth. Almost three quarters of the electricity supply of China is derived from thermal power (mainly coal combustion). A proper projection of electricity consumption is helpful to deduce China's dependence on coal as a source of energy and thus will be helpful for the health of the environment. Therefore, it is necessary for the government to accurately predict the electricity demand. This paper employs both rolling mechanism and differential evolution algorithm to improve the prediction accuracy of the original grey model. Then, data from the China Federation of Electric Power Industry Development and Environmental Resources Department was adopted as database to test both the efficiency and accuracy of the improved prediction model. Experimental results show that the proposed model clearly outperforms the original grey model with regard to prediction accuracy. In addition, the future electricity consumption and power generation of China have been forecasted until 2025. The results will be useful to guide the electricity supply planning of the power department to promote the balance of power supply and demand. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19929978
Volume :
49
Issue :
4
Database :
Academic Search Index
Journal :
IAENG International Journal of Applied Mathematics
Publication Type :
Academic Journal
Accession number :
139920304