An optimized grey model for predicting non-renewable energy consumption in China
Jianlong Guo1,2, Lifeng Wu3, Yali Mu1,2
1College of Economics and Management, Nanjing Forestry University, Nanjing, 210037, China.
Heliyon
|July 24, 2023
Summary
China
Area of Science:
- Energy economics
- Environmental science
- Forecasting modeling
Background:
- China's high non-renewable energy consumption poses challenges to carbon neutrality goals.
- Accurate forecasting of energy consumption is crucial for sustainable development.
Purpose of the Study:
- To develop a novel grey model for predicting non-renewable energy consumption in China.
- To enhance prediction accuracy by introducing adjustable information weights and optimizing parameters.
Main Methods:
- Modification of the traditional grey model by incorporating two information weight adjustment parameters.
- Utilization of an intelligent optimization algorithm to determine optimal model parameters.
- Validation of the model's feasibility through three distinct case studies.
Main Results:
- Forecasts indicate a continued accelerated growth in oil and natural gas consumption.
- Oil consumption is projected to exceed 37 EJ and natural gas consumption 22 EJ by 2026.
- Oil consumption is expected to increase by nearly 24% and natural gas by over 60% compared to 2021 levels, while coal consumption growth will slow and stabilize.
Conclusions:
- The proposed grey model effectively predicts non-renewable energy consumption trends in China.
- Accelerated growth in oil and natural gas demand highlights the need for strategic energy planning.
- Stabilizing coal consumption suggests a potential shift in China's energy structure.
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