Proceedings of the 2025 7th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2025)

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Improvement of Carbon Emission Assessment Algorithm for the Full Life Cycle: The Case of Wind-Storage Power Stations

Authors
Fujian Huang1, Haotao Huang1, Weigao Liang1, Mengya Yin2, 3, *, Weihao Chen2, 3
1Guangzhou Power Supply Bureau of Guangdong Grid Co., Guangzhou, 510520, China
2Guangdong Provincial Academy of Building Research Group Co., Ltd., Guangzhou, 510500, China
3Guangdong Jianke Innovation Technology Research Institute Co., Ltd, Zhongshan, 528403, China
*Corresponding author. Email: ymy445225248@163.com
Corresponding Author
Mengya Yin
Available Online 16 December 2025.
DOI
10.2991/978-94-6463-902-5_19How to use a DOI?
Keywords
wind-storage power stations; full life cycle; carbon emission assessment; carbon emission factor; BP neural network
Abstract

Accurately evaluating the full life cycle carbon emissions of wind - storage power stations is vital for sustainable development amid the “Carbon Peaking and Neutrality Goals”. Unlike partial assessments, full life cycle ones are more complex and uncertain due to the need to cover all phases’ carbon emissions influenced by multiple factors, leading to vague boundaries and intricate evaluation processes. To tackle these issues, this study proposes an enhanced carbon emission assessment algorithm. It clarifies system boundaries and allows dynamic adjustments based on actual conditions. The algorithm incorporates carbon emission factors, combines them with a BP algorithm, and dynamically adjusts network structures and weights. This improves adaptability and prediction accuracy. Experimental results show it can control assessment errors within 3kgCO₂, offering an effective way to assess the life - cycle carbon emissions of wind - storage power stations and aiding carbon - neutrality efforts.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 7th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2025)
Series
Advances in Engineering Research
Publication Date
16 December 2025
ISBN
978-94-6463-902-5
ISSN
2352-5401
DOI
10.2991/978-94-6463-902-5_19How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Fujian Huang
AU  - Haotao Huang
AU  - Weigao Liang
AU  - Mengya Yin
AU  - Weihao Chen
PY  - 2025
DA  - 2025/12/16
TI  - Improvement of Carbon Emission Assessment Algorithm for the Full Life Cycle: The Case of Wind-Storage Power Stations
BT  - Proceedings of the 2025 7th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2025)
PB  - Atlantis Press
SP  - 192
EP  - 206
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-902-5_19
DO  - 10.2991/978-94-6463-902-5_19
ID  - Huang2025
ER  -