EconPapers    
Economics at your fingertips  
 

Application of a new grey multivariate forecasting model in the forecasting of energy consumption in 7 regions of China

Meng Wang, Wei Wang and Lifeng Wu

Energy, 2022, vol. 243, issue C

Abstract: Scientific prediction of regional energy is of practical significance for rational control of energy supply. In this paper, to further minimize the influence of subjective factors, the grey relational analysis and the FGM(1,1) model whose forecast results are affected by the fixed order are selected to analyze the samples. Then, a new grey multi-variable AGMC(1,N) model with better prediction performance is used to study 13 provinces (cities) in 7 different regions of China in detail. The results show that only the energy consumption in Central China will decrease in the short term. Energy consumption in the remaining 6 regions will continue to rise, and the energy consumption of East China, Northeast China, and Northwest China have a remarkable growth trend. It is important to provide reliable data to China's energy regulators and provide a reference for regional energy reform in the short term.

Keywords: Energy consumption; Influenced factor; Grey relation analysis; Adjacent accumulation; AGMC(1,N) model (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544221032734
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:243:y:2022:i:c:s0360544221032734

DOI: 10.1016/j.energy.2021.123024

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:243:y:2022:i:c:s0360544221032734