1. Assessment of carbon emission reduction contribution of Chinese power grid enterprises based on MCS-GA-ELM method.
- Author
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Li, Jinchao, Sun, Zihao, and Lu, Shiqiang
- Subjects
ELECTRIC power distribution grids ,GREENHOUSE gas mitigation ,CARBON emissions ,MONTE Carlo method ,MACHINE learning - Abstract
To achieve China's "double carbon" goal, it is necessary to make quantitative evaluation of the power grid enterprises' contribution to carbon emission reduction. This paper analyzes the contribution of power grid enterprises to carbon emission reduction from three points: power generation side, power grid side, and user side. Then, PLS-VIP method is used to screen the key influencing factors of carbon emission reduction contribution of power grid enterprises from three aspects: consumption of clean energy emission reduction, reduction of line loss emission reduction, and substitution of electric energy. Based on GA-ELM combined machine learning algorithm, we establish an intelligent evaluation model of power grid enterprises' carbon emission reduction contribution. Furthermore, according to the distribution law of key influencing factors, this paper uses Monte Carlo simulation method to calculate the contribution of power grid enterprises to carbon emission reduction by scenario, so as to evaluate the contribution of power grid enterprises to carbon emission reduction. Finally, combined with the relevant data of power grid enterprises from 2003 to 2019, this paper makes an empirical study on the completion of carbon emission reduction contribution and the promotion path. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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