Study on the Assessment Method of Carbon Emission Reduction Potential in Electricity Transmission and Distribution Project Construction

With power transmission and distribution projects as the object, this paper defines the carbon emission reduction potential, constructs a carbon reduction potential calculation model, and studies specific procedures of data collection, modeling, and solution. It applies the K-means algorithm for clustering, which can identify processes with significant carbon emission reduction potential through analysis for optimized management. It selects sectional works including substation installation works and civil construction works from the two typical power transmission and distribution projects in China for model application and case studies. The study results show that the carbon emission reduction of the two works are 70.248 kg CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2e</inf> and 127.998 kg CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2e</inf>, respectively, with emission reduction potential of 23.97% and 48.57%, respectively.

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Publication Details

Published
2025-01-10
DOI
https://doi.org/10.1109/citsc64390.2025.00028
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.00

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article

Study on the Assessment Method of Carbon Emission Reduction Potential in Electricity Transmission and Distribution Project Construction

Rui Liu, Xiaofeng Wang, Chao Liu, Jie Wen et al.
Environmental Impact and Sustainability
article

Study on the Assessment Method of Carbon Emission Reduction Potential in Electricity Transmission and Distribution Project Construction

Rui Liu, Xiaofeng Wang, Chao Liu, Jie Wen, Bo Miao, Xiaofa Zhou
article en

Abstract

With power transmission and distribution projects as the object, this paper defines the carbon emission reduction potential, constructs a carbon reduction potential calculation model, and studies specific procedures of data collection, modeling, and solution. It applies the K-means algorithm for clustering, which can identify processes with significant carbon emission reduction potential through analysis for optimized management. It selects sectional works including substation installation works and civil construction works from the two typical power transmission and distribution projects in China for model application and case studies. The study results show that the carbon emission reduction of the two works are 70.248 kg CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2e</inf> and 127.998 kg CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2e</inf>, respectively, with emission reduction potential of 23.97% and 48.57%, respectively.

State Grid Corporation of China
Openalex Percentile: Top 94%
Environmental Impact and Sustainability
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