Dynamic Accounting Model and Method for Carbon Emissions on the Power Grid Side

Author:

He Hengjing12,Zhou Shangli12,Zhang Leping12,Zhao Wei12,Xiao Xia3ORCID

Affiliation:

1. Digital Grid Research Institute, China Southern Power Grid, Guangzhou 510663, China

2. Guangdong Provincial Key Laboratory of Digital Grid Technology, Guangzhou 510663, China

3. School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430070, China

Abstract

Currently, in China’s power grid, the accounting of carbon emissions has shortcomings such as unclear accounting boundaries, slow updating of carbon emission factors (EFs), and a lack of spatiotemporal characteristics. In this study, a dynamic accounting model for carbon emission was constructed based on carbon flow theory and the QIO (Quasi-Input-Output) model using the transmission side, the substation side, and the distribution side as accounting nodes. By utilizing the electricity metering data and carbon EF on the input side of the node, the total carbon emissions flowing into the node could be calculated. Furthermore, based on the electricity metering data on the output side of the node, the carbon emissions and carbon EF flowing out of the node could be calculated. The accounting results of carbon emissions and carbon EF are characterized by flexibility and dynamicity in both spatial and temporal dimensions. Finally, the practicality of the method has been demonstrated through a substation node. The accounting model has a positive impact on accurate carbon emission accounting for the power grid, better tracing of carbon emissions, and effective user guidance on active carbon emission reduction.

Funder

Digital Grid Research Institute, China Southern Power Grid

Guangdong Provincial Key Laboratory of Digital Grid Technology

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference24 articles.

1. Deep learning in energy modeling: Application in smart buildings with distributed energy generation;Nabavi;IEEE Access,2021

2. Research and Benefit Analysis of Low-carbon Demand Response Mechanism in Power System Based on Carbon Emission Flow;Li;Chin. J. Electr. Eng.,2022

3. Hourly-based greenhouse gas emissions of electricity-cases demonstrating possibilities for households and companies to de-crease their emissions;Mattinen;J. Clean. Prod.,2017

4. Mechanism study and benefit analysis on power system low carbon demand response based on carbon emission flow;Li;Proc. CSEE,2022

5. Eggleston, H.S., Buendia, L., Miwa, K., Ngara, T., and Tanabe, K. (2006). 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC National Greenhouse Gas Inventories Programme.

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