A Dynamic Carbon Emission Flow Method Based on Source-to-Load Power Delivery Matrix

This paper presents a dynamic carbon emission flow calculation model based on source-to-load power delivery matrix for the allocation of carbon emission responsibility in power systems. Traditional methods of network loss allocation, which separately attribute losses to generators or loads, fail to capture the full complexity of power systems. To address this, a model is proposed where network losses are dynamically allocated between generators and loads based on energy transfer proportions. Reverse power flow tracking is used to construct a lossless network, attributing network losses to the generators initially. A matrix-based method is then applied to calculate the energy transfer from generators to loads, dynamically reallocating part of the network losses to the load side. The proposed method significantly improves the fairness and efficiency of carbon emission responsibility allocation. Validation through an IEEE 14-bus system case study demonstrates the model’s ability to accurately track and allocate carbon flows, supporting the low-carbon transition of power systems.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/icei63732.2024.10917141
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
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A Dynamic Carbon Emission Flow Method Based on Source-to-Load Power Delivery Matrix

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Electric and Hybrid Vehicle Technologies
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A Dynamic Carbon Emission Flow Method Based on Source-to-Load Power Delivery Matrix

Zhipeng Liu, Chunli Zhou, Lidan Chen, Ming Yu, Jianhua Gong, Qiuyun Lu, Meng Jin, Zhen Pan
article en

Abstract

This paper presents a dynamic carbon emission flow calculation model based on source-to-load power delivery matrix for the allocation of carbon emission responsibility in power systems. Traditional methods of network loss allocation, which separately attribute losses to generators or loads, fail to capture the full complexity of power systems. To address this, a model is proposed where network losses are dynamically allocated between generators and loads based on energy transfer proportions. Reverse power flow tracking is used to construct a lossless network, attributing network losses to the generators initially. A matrix-based method is then applied to calculate the energy transfer from generators to loads, dynamically reallocating part of the network losses to the load side. The proposed method significantly improves the fairness and efficiency of carbon emission responsibility allocation. Validation through an IEEE 14-bus system case study demonstrates the model’s ability to accurately track and allocate carbon flows, supporting the low-carbon transition of power systems.

University of Macau (MO), Guangzhou Maritime College (CN), City University of Macau (MO), China Southern Power Grid (China) (CN)
Openalex Percentile: Top 69%
Electric and Hybrid Vehicle Technologies
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