Forecasting China’s carbon emissions trading volume by an improved weighted grey power model

ABSTRACT

China’s carbon emissions trading volume has been increasing rapidly since the online trading system was officially launched in July 2021. China’s annual carbon emissions trading volume is 246 million tons in 2021, 1.74 times that of 2020. To study this uncertain market, this study proposes an improved weighted Hausdorf fractional discrete grey power model (WDGPM) to predict the market size of China’s emissions trading volume. The WDGPM’s discrete structure avoids complex integral calculation, which improves the calculation efficiency and accuracy. The proposed WDGPM model includes an interactive power structure term that performs well in the nonlinear prediction task. Furthermore, a new information parameter is introduced to construct the weight function of the weighted least squares method, which distinguishes the temporal differences of observations. A sparrow search algorithm is used to optimize the two hyperparameters of the WDGPM model. Numerical examples show the effectiveness of the proposed method, with forecast results indicating that the proposed WDGPM has higher accuracy than other competitive algorithms. The expected trading volume of China’s emissions trading market is projected to reach 466.84 million tons in 2025, with an annual growth rate of 17%, which is 1.9 times that of 2021.

KEYWORDS:

• Carbon emissions trading
• grey model
• forecast
• weighted least squares method
• sparrow search algorithm

Acknowledgements

This work was supported by projects of the National Natural Science Foundation of China (72071111, 71801127).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data and models used during the study appear in the submitted article.

Declarations

The authors declare that they have no conflict of interest.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [71801127].

Notes on contributors

Xinying Xie

Xinying Xie was born in September 1998. Since 2021, she has been pursuing a graduate degree at Changzhou University. His research interests include econometrics, energy policy, and data analysis.

Lianyi Liu

Lianyi Liu was born in June 1996. In 2021, he received a master's degree from Hebei University of Engineering. Then, he entered Nanjing University of Aeronautics and Astronautics to study for a doctorate. His research interests include grey system theory, uncertainty analysis theory, and predictive modeling techniques.