A novel multivariate grey model of energy consumption under carbon trading background and its application

Abstract

Climate warming and the energy crisis have been high-profile issues today, and carbon trading is considered one of the essential means to solve the problem. Carbon trading cannot ignore the impact on energy consumption and carbon emissions. Therefore, it is beneficial to develop a low-carbon economy to scientifically predict the trend of energy consumption and make timely investment decisions and policies in carbon trading. Based on the modelling mechanism of energy economy and the grey forecasting model, this paper studies the dynamic relationship among energy consumption, carbon emissions, economic growth, and carbon trading price and then constructs a grey prediction model of energy consumption driven by carbon trading. The least-square method and recursive mathematical method were used to obtain the model’s parameter estimation and corresponding time formula, respectively. In the end, we apply the model to the energy consumption in China, and three experimental results reveal that the prediction performance of the novel model is significantly better than the existing four grey models. And it is predicted that the energy consumption of coal in China will increase by 15.3118% in 2025, which can provide an essential reference for the energy structure adjustment and environmental policymaking in China.