Data-Driven Demand-Side Carbon Emission Accounting for Residential Users

Chun Wang; E. Libo; Xiao Liu; Binrong Zhang; Yuxiong Huang; Gengfeng Li

doi:10.1109/EI259745.2023.10512822

Data-Driven Demand-Side Carbon Emission Accounting for Residential Users

Chun Wang
, E. Libo
, Xiao Liu
, Binrong Zhang
, Yuxiong Huang
, Gengfeng Li

School of Electrical Engineering

Xi'an Jiaotong University
Shandong Electric Power Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Demand-side carbon reduction plays a crucial role in achieving carbon neutrality. However, implementing carbon reduction measures for residential users poses several challenges including individual dispersion, data availability, and quantitative assessment of carbon emissions. Presently, research on demand-side carbon reduction primarily focuses on large users in industrial and commercial sectors, while the research on carbon emission accounting methods for residential users remains insufficient. To address this gap, this paper proposes a data-driven approach for carbon emission accounting specifically tailored to residential users, based on carbon emission flow theory. Specifically, this paper firstly introduces the traditional method of calculating carbon emissions from electricity consumption and its limitations. Secondly, it proposes a method for calculating carbon emissions from residential electricity consumption based on real-time carbon emission coefficient. Then, the calculation method of real-time carbon emission coefficient is introduced based on the theory of carbon emission flow analysis. Finally, calculations and analysis are conducted on the IEEE 118-bus system to demonstrate the effectiveness of this method.

Original language	English
Title of host publication	2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2246-2251
Number of pages	6
ISBN (Electronic)	9798350345094
DOIs	https://doi.org/10.1109/EI259745.2023.10512822
State	Published - 2023
Event	7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023 - Hangzhou, China Duration: 15 Dec 2023 → 18 Dec 2023

Publication series

Name	2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023

Conference

Conference	7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023
Country/Territory	China
City	Hangzhou
Period	15/12/23 → 18/12/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

carbon emission
carbon neutrality
data-driven
demand-side
power flow tracing
residential users

Access to Document

10.1109/EI259745.2023.10512822

Cite this

Wang, C., Libo, E., Liu, X., Zhang, B., Huang, Y., & Li, G. (2023). Data-Driven Demand-Side Carbon Emission Accounting for Residential Users. In 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023 (pp. 2246-2251). (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EI259745.2023.10512822

@inproceedings{cda7121f5da948359046a16a1301db82,

title = "Data-Driven Demand-Side Carbon Emission Accounting for Residential Users",

abstract = "Demand-side carbon reduction plays a crucial role in achieving carbon neutrality. However, implementing carbon reduction measures for residential users poses several challenges including individual dispersion, data availability, and quantitative assessment of carbon emissions. Presently, research on demand-side carbon reduction primarily focuses on large users in industrial and commercial sectors, while the research on carbon emission accounting methods for residential users remains insufficient. To address this gap, this paper proposes a data-driven approach for carbon emission accounting specifically tailored to residential users, based on carbon emission flow theory. Specifically, this paper firstly introduces the traditional method of calculating carbon emissions from electricity consumption and its limitations. Secondly, it proposes a method for calculating carbon emissions from residential electricity consumption based on real-time carbon emission coefficient. Then, the calculation method of real-time carbon emission coefficient is introduced based on the theory of carbon emission flow analysis. Finally, calculations and analysis are conducted on the IEEE 118-bus system to demonstrate the effectiveness of this method.",

keywords = "carbon emission, carbon neutrality, data-driven, demand-side, power flow tracing, residential users",

author = "Chun Wang and E. Libo and Xiao Liu and Binrong Zhang and Yuxiong Huang and Gengfeng Li",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023 ; Conference date: 15-12-2023 Through 18-12-2023",

year = "2023",

doi = "10.1109/EI259745.2023.10512822",

language = "英语",

series = "2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2246--2251",

booktitle = "2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023",

}

Wang, C, Libo, E, Liu, X, Zhang, B, Huang, Y & Li, G 2023, Data-Driven Demand-Side Carbon Emission Accounting for Residential Users. in 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023, Institute of Electrical and Electronics Engineers Inc., pp. 2246-2251, 7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023, Hangzhou, China, 15/12/23. https://doi.org/10.1109/EI259745.2023.10512822

Data-Driven Demand-Side Carbon Emission Accounting for Residential Users. / Wang, Chun; Libo, E.; Liu, Xiao et al.
2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 2246-2251 (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Data-Driven Demand-Side Carbon Emission Accounting for Residential Users

AU - Wang, Chun

AU - Libo, E.

AU - Liu, Xiao

AU - Zhang, Binrong

AU - Huang, Yuxiong

AU - Li, Gengfeng

PY - 2023

Y1 - 2023

N2 - Demand-side carbon reduction plays a crucial role in achieving carbon neutrality. However, implementing carbon reduction measures for residential users poses several challenges including individual dispersion, data availability, and quantitative assessment of carbon emissions. Presently, research on demand-side carbon reduction primarily focuses on large users in industrial and commercial sectors, while the research on carbon emission accounting methods for residential users remains insufficient. To address this gap, this paper proposes a data-driven approach for carbon emission accounting specifically tailored to residential users, based on carbon emission flow theory. Specifically, this paper firstly introduces the traditional method of calculating carbon emissions from electricity consumption and its limitations. Secondly, it proposes a method for calculating carbon emissions from residential electricity consumption based on real-time carbon emission coefficient. Then, the calculation method of real-time carbon emission coefficient is introduced based on the theory of carbon emission flow analysis. Finally, calculations and analysis are conducted on the IEEE 118-bus system to demonstrate the effectiveness of this method.

AB - Demand-side carbon reduction plays a crucial role in achieving carbon neutrality. However, implementing carbon reduction measures for residential users poses several challenges including individual dispersion, data availability, and quantitative assessment of carbon emissions. Presently, research on demand-side carbon reduction primarily focuses on large users in industrial and commercial sectors, while the research on carbon emission accounting methods for residential users remains insufficient. To address this gap, this paper proposes a data-driven approach for carbon emission accounting specifically tailored to residential users, based on carbon emission flow theory. Specifically, this paper firstly introduces the traditional method of calculating carbon emissions from electricity consumption and its limitations. Secondly, it proposes a method for calculating carbon emissions from residential electricity consumption based on real-time carbon emission coefficient. Then, the calculation method of real-time carbon emission coefficient is introduced based on the theory of carbon emission flow analysis. Finally, calculations and analysis are conducted on the IEEE 118-bus system to demonstrate the effectiveness of this method.

KW - carbon emission

KW - carbon neutrality

KW - data-driven

KW - demand-side

KW - power flow tracing

KW - residential users

UR - https://www.scopus.com/pages/publications/85194142612

U2 - 10.1109/EI259745.2023.10512822

DO - 10.1109/EI259745.2023.10512822

M3 - 会议稿件

AN - SCOPUS:85194142612

T3 - 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023

SP - 2246

EP - 2251

BT - 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023

Y2 - 15 December 2023 through 18 December 2023

ER -

Wang C, Libo E, Liu X, Zhang B, Huang Y, Li G. Data-Driven Demand-Side Carbon Emission Accounting for Residential Users. In 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 2246-2251. (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023). doi: 10.1109/EI259745.2023.10512822

Data-Driven Demand-Side Carbon Emission Accounting for Residential Users

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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