A novel nonlinear grey multivariate prediction model based on energy structure and its application to energy consumption

Abstract

Energy consumption can effectively reflect not only the regional economic and industrial structure but also the regional energy utilization efficiency. Effective analysis of energy consumption structures and further scientific understanding of energy consumption are crucial to the formulation of energy development and utilization policies. This paper establishes a nonlinear differential equation for the diversified development of oil-gas, coal, and other energy sources for energy conservation, consumption reduction, and optimization of energy structure and establishes a nonlinear grey multivariate prediction model for energy structure using the differential equation and grey difference information. Specifically, the relationships among several differential functions in the system are analyzed, and specific modeling steps are given. By solving the parameter estimates and time response functions of the model, the consumption of oil-gas and other energy sources can be predicted simultaneously, and the novel model's effectiveness is demonstrated from three different perspectives. The results show that the novel model can effectively predict the consumption of oil-gas and other energy sources as well as the price and consumption of coal in China from 2021 to 2026, and its prediction results can provide effective information for maintaining a sustainable state of the energy system and formulating reasonable and effective control measures.