Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

December 18, 2023


Pages


DOI

Article

A Whole-Segment Carbon Measurement Approach for Energy Systems Incorporating Knowledge Mapping Techniques

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Authors

Qiang Li Affiliation:
State Grid Information & Telecommunication Group Co., Ltd, Beijing, 102200, China.
, Juanyu Liu Affiliation:
Tianjin Richsoft Electric Power Information Technology Co., Ltd., Tianjin, 300300, China.
, Laidong Zhang Affiliation:
Tianjin Richsoft Electric Power Information Technology Co., Ltd., Tianjin, 300300, China.
, Xinyue Li Affiliation:
Tianjin Richsoft Electric Power Information Technology Co., Ltd., Tianjin, 300300, China.
, Junting Luo Affiliation:
Tianjin Richsoft Electric Power Information Technology Co., Ltd., Tianjin, 300300, China.
, Sijue Wang Affiliation:
Tianjin Richsoft Electric Power Information Technology Co., Ltd., Tianjin, 300300, China.
and Shuwang Han Affiliation:
Tianjin Richsoft Electric Power Information Technology Co., Ltd., Tianjin, 300300, China.


Abstract

As the current carbon measurement method makes it difficult to reflect the time-space variability of carbon emission factors, it leads to the inability to clarify the carbon emission responsibility of grid-side losses. In this paper, starting from the internal power system, based on the power system carbon emission flow analysis theory and knowledge graph technology, a trend-tracking analytical algorithm based on the node conductivity matrix operation is proposed to solve the complex power allocation relationship between each generating unit and each node load, and between each generating unit and the line network loss. On the basis of this algorithm, the carbon flow tracking model of the whole power system is established according to the conversion relationship between the current and the carbon flow, and the analytical expressions of the carbon emission distribution among the power generation side, the load side and the line loss are obtained by combining with matrix operation, so as to measure the carbon emission measurement results of the whole power system and to provide data references for the responsibility sharing of carbon emission. Finally, simulation verification is carried out based on the actual system operation and load data for C city. The total amount of carbon emissions from electricity consumption is 98.8 million tCO2 when C city is used as the minimum spatial scale, while the total amount of carbon emissions from electricity consumption is 67.9 million tCO2, 14.0 million tCO2, 16.9 million tCO2, and the total amount of the three regions is 98.8 million tCO2, which is consistent with that calculated when C city is used as the minimum spatial scale. The calculation results are consistent in real-time. The carbon measurement method proposed in this paper can obtain higher spatial resolution carbon measurement results for electricity consumption.


Keywords

Power system, Whole-link carbon measurement, Knowledge graph, Trend tracking algorithm, Node conductivity matrix, 03B20


Citation

Li, Q., Liu, J., Zhang, L., Li, X., Luo, J., Wang, S., & Han, S. (2023). A whole-segment carbon measurement approach for energy systems incorporating knowledge mapping techniques. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01537

Published by: Engineering Journals

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