An optimized grey model for predicting non-renewable energy consumption in China

Abstract

The large amount of the non-renewable energy consumption in China brings certain challenges to the realization of carbon neutrality. This paper proposes a new grey model to predict the consumption of non-renewable energy in China. Based on the traditional grey model, the proposed model introduces two parameters to adjust the weight of information. Simultaneously, the intelligent optimization algorithm determines the optimal parameters. Three cases verify the feasibility of the model. The forecast results show that the amount of oil and natural gas consumption will continue to grow at a faster rate. By 2026, the amount of oil consumption will exceed 37 EJ (EJ) and natural gas consumption will exceed 22 EJ. Compared to 2021, oil consumption is up nearly 24%, and natural gas consumption is up more than 60%. While the consumption of coal will maintain a small up rate and gradually be leveled off.

Keywords

• Non-renewable energy consumption
• Compound accumulation model
• Disturbance boundary
• Time series forecasting