Forecasting China’s electricity demand up to 2030: a linear model selection system
Journal of Modelling in Management
ISSN: 1746-5664
Article publication date: 14 September 2018
Issue publication date: 15 October 2018
Abstract
Purpose
Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.
Design/methodology/approach
With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.
Findings
The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.
Originality/value
Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.
Keywords
Acknowledgements
The authors gratefully acknowledge the financial supports from the National Natural Science Foundation of China (Grant Nos. 71601020 and 71521002), the National Key R&D Program (Grant No. 2016YFA0602603), the China Postdoctoral Science Foundation (Grant No. 2016M590052) as well as the Science and Technology Project of State Grid Corporation Headquarters (Grant No. YD71-16-014). The authors would like to extend special thanks to the editor and the anonymous reviewers for their constructive comments and suggestions for improving the quality of this article.
Citation
Zhu, X., Yang, S., Lin, J., Wei, Y.-M. and Zhao, W. (2018), "Forecasting China’s electricity demand up to 2030: a linear model selection system", Journal of Modelling in Management, Vol. 13 No. 3, pp. 570-586. https://doi.org/10.1108/JM2-11-2017-0117
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited