An evaluation of low-carbon collaborative emission reduction effect of new energy wind and solar power generation based on set pair analysis

In order to overcome the problems of poor accuracy and poor evaluation of emission reduction effects, this article introduces set pair analysis to evaluate the low-carbon collaborative emission reduction effect of new energy solar power generation. Firstly, an evaluation index system is constructed. Then, the subjective weight of the indicators is calculated using the intuitive fuzzy analytic hierarchy process, the objective weight is calculated using the entropy weight method and the comprehensive weight value of the indicators is calculated using game theory. Finally, the emission reduction effect evaluation function is constructed using set pair analysis theory, and the evaluation level is determined using confidence to obtain the final evaluation result. The results show that the evaluation accuracy of the method in this paper can reach 99.5%, and this method can accurately evaluate the low-carbon collaborative emission reduction effect of new energy wind power generation.

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Publication Details

Journal
International Journal of Global Energy Issues
Published
2025-01-01
DOI
https://doi.org/10.1504/ijgei.2025.147242
Primary Topic
Regional Development and Environment
Type
article
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article

An evaluation of low-carbon collaborative emission reduction effect of new energy wind and solar power generation based on set pair analysis

Liu Ke-li, Peidong He, Xiaojun Li, Xiaoxiao Yang et al.
International Journal of Global Energy Issues
Regional Development and Environment
article

An evaluation of low-carbon collaborative emission reduction effect of new energy wind and solar power generation based on set pair analysis

Liu Ke-li, Peidong He, Xiaojun Li, Xiaoxiao Yang, Shijiong Yuan
article en

Abstract

In order to overcome the problems of poor accuracy and poor evaluation of emission reduction effects, this article introduces set pair analysis to evaluate the low-carbon collaborative emission reduction effect of new energy solar power generation. Firstly, an evaluation index system is constructed. Then, the subjective weight of the indicators is calculated using the intuitive fuzzy analytic hierarchy process, the objective weight is calculated using the entropy weight method and the comprehensive weight value of the indicators is calculated using game theory. Finally, the emission reduction effect evaluation function is constructed using set pair analysis theory, and the evaluation level is determined using confidence to obtain the final evaluation result. The results show that the evaluation accuracy of the method in this paper can reach 99.5%, and this method can accurately evaluate the low-carbon collaborative emission reduction effect of new energy wind power generation.

International Journal of Global Energy IssuesVol. 47(4/5)
State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 76%
Regional Development and Environment
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