Research on carbon emission accounting of SF 6 electrical equipment based on improved random forest algorithm

Wenwei Zhu, Baichong Pan, Weixian Che and Chenghao Xu

International Journal of Energy Technology and Policy, 2024, vol. 19, issue 1/2, 135-153

Abstract: Due to the large convergence error and high interference coefficient of carbon emissions accounting, research on carbon emission accounting of SF₆ electrical equipment based on improved random forest algorithm is proposed. Firstly, the arc extinguishing characteristics and insulation performance of SF₆ electrical equipment are determined. Then, the differences in the decomposition of substances in SF₆ electrical equipment under various conditions are analysed, and differential optical absorption spectroscopy is used to determine the carbon emission equivalent of the equipment. Finally, the OOB error estimation algorithm is introduced to build an improved random forest algorithm model, and the nonlinear activation function is used to determine the synapse strength, and the information function is used to adjust the convergence value of accounting error to complete the carbon emissions accounting. The results indicate that the proposed method can reduce the convergence value of accounting errors and the interference coefficient of accounting results.

Keywords: SF 6 electrical equipment; carbon emissions; accounting; arc extinguishing characteristics; OOB error estimation; non-linear activation function. (search for similar items in EconPapers)
Date: 2024
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