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Evaluation of Spatial and Temporal Distribution of Carbon Emissions in Power Grid Based on Cloud Theory

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Listed:
  • Pingzheng Tong

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Xue Cui

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Junlin Li

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Xuehan Dang

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Qiang Yu

    (Grid Planning and Construction Research Center, Yunnan Power Grid Co., Ltd., Kunming 650011, China)

Abstract

In order to clearly determine the carbon emission distribution of regions, lines or nodes in the power grid, this paper applies cloud theory to the evaluation of the distribution of carbon emissions in the power grid. Based on the theory of carbon emission flow in the whole life cycle, five indicators that can reflect the spatial and temporal distribution of carbon emissions are constructed from the two dimensions of space and time. Cloud theory is used to establish the standard cloud of the carbon emission distribution level to quantify the randomness and fuzziness of the data to be evaluated. The bilateral constraint cloud theory and data-driven cloud transformation are combined to construct five comprehensive standard clouds of excellent, good, medium, poor and inferior, which are used as the evaluation interval of the evaluation index of carbon emission distribution. The reverse cloud is used to convert multiple sets of data into cloud droplets. Through the similarity measurement algorithm based on cloud model overlap, the comprehensive evaluation level of carbon emission distribution state in the time dimension is determined. Taking the IEEE 39 system as the research object, the spatial and temporal distribution of carbon emissions is evaluated, and the rationality and effectiveness of the proposed model are verified. Finally, the influence of the new energy penetration rate and power supply structure on the carbon emission distribution of the power grid is discussed by using cloud computing. Based on this, the targeted carbon reduction strategies for different types of nodes and the method of measuring the optimal new energy penetration rate are proposed and can provide a decision-making reference for optimizing the carbon emissions of the power grid.

Suggested Citation

  • Pingzheng Tong & Xue Cui & Junlin Li & Xuehan Dang & Qiang Yu, 2024. "Evaluation of Spatial and Temporal Distribution of Carbon Emissions in Power Grid Based on Cloud Theory," Sustainability, MDPI, vol. 16(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9767-:d:1517134
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    References listed on IDEAS

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    1. Qin, Quande & Liu, Yuan & Huang, Jia-Ping, 2020. "A cooperative game analysis for the allocation of carbon emissions reduction responsibility in China's power industry," Energy Economics, Elsevier, vol. 92(C).
    2. Mingrun Tang & Ruoyang Li & Rujia Zhang & Shuxia Yang, 2024. "Research on New Electric Power System Risk Assessment Based on Cloud Model," Sustainability, MDPI, vol. 16(5), pages 1-19, February.
    3. Chong, Cheng Tung & Fan, Yee Van & Lee, Chew Tin & Klemeš, Jiří Jaromír, 2022. "Post COVID-19 ENERGY sustainability and carbon emissions neutrality," Energy, Elsevier, vol. 241(C).
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