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

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.(c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Scientific prediction of regional energy is of practical significance for rational control of energy supply. In this paper, the grey relational analysis and the FGM(1,1) model are used to analyze the samples, and a new grey multi-variable AGMC(1,N) model is used to study 13 provinces (cities) in 7 different regions of China. The results show that energy consumption in Central China will decrease in the short term, while it will continue to rise in the other regions.