A novel compositional data model for predicting the energy consumption structures of Europe, Japan, and China

The analysis and prediction of the energy consumption structure provide an important basis for promoting the optimization of the energy consumption structure, energy saving, and emission reduction. The structure data of energy consumption can reflect the proportion of various energy consumptions and...

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Bibliographic Details
Published in:Environment, development and sustainability development and sustainability, 2023-10, Vol.25 (10), p.11673-11698
Main Authors: Xiao, Xinping, Li, Xue
Format: Article
Language:English
Subjects:
Autocorrelation
Autoregressive moving-average models
Earth and Environmental Science
Ecology
Economic Geology
Economic Growth
Emissions control
Energy conservation
Energy consumption
Environment
Environmental Economics
Environmental Management
Mathematical models
Optimization
Parameter estimation
Sustainable Development
Transformation
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Summary:The analysis and prediction of the energy consumption structure provide an important basis for promoting the optimization of the energy consumption structure, energy saving, and emission reduction. The structure data of energy consumption can reflect the proportion of various energy consumptions and belong to component data. In this study, an autoregressive moving average model of component data (CDARMA) based on simplex space and its algebraic system is established to study the energy consumption structure. First, various mathematical concepts in simplex space are presented to lay a theoretical modeling foundation. Second, the autocorrelation and partial autocorrelation coefficients of the component data are defined, and the CDARMA model in the simplex space is established. The parameters are estimated using least squares. Third, the energy consumption structure data of Europe, Japan, and China are used to verify the effectiveness of the proposed model. And the results are compared with other four models under eight kinds of transformation. Overall, the new model has a better fitting effect, prediction effect, and stability than the compared models. Lastly, the CDARMA model is used to predict the energy consumption structure of the three regions in 2019–2025 to provide a reference for the adjustment of the energy structure.
ISSN:1387-585X
1573-2975
DOI:10.1007/s10668-022-02547-5