Forecasting China's energy production and consumption based on a novel structural adaptive Caputo fractional grey prediction model

Abstract

China's total energy consumption and production ranks first in the world. However, China's energy structure is not perfect. Therefore, accurate prediction of future energy trends is of great significance for the Chinese government to adjust the energy structure. Therefore, this paper proposes a novel structural adaptive grey model FCSAGM(p, 1) with Caputo fractional derivative and a new Caputo fractional order accumulation generation operator. Through the comparison between optimization algorithms, Particle Swarm Optimization (PSO) is selected to optimize the parameters of the model. In particular, aiming at the problem of model reliability caused by the optimization algorithm, the robustness of the model is analyzed, and the results show that the model is stable and reliable. Finally, four actual cases of China's total energy consumption, China's total primary energy production, China's thermal power generation and China's hydropower generation are predicted; the prediction result shows that the new model has higher prediction accuracy than the other six grey models.