Integrated Intelligent Energy ›› 2024, Vol. 46 ›› Issue (3): 72-78.doi: 10.3969/j.issn.2097-0706.2024.03.009

• Low-carbon Technical Economy • Previous Articles     Next Articles

Calculation and prediction of carbon emission factors for the national power grid from 2005 to 2035

WEI Xikai1,2(), TAN Xiaoshi1, LIN Ming3, CHENG Junjie4, XIANG Keqi1, DING Shuxin3   

  1. 1. 714 Research Institute of China Shipbuilding Corporation Limited, Beijing 100020, China
    2. School of Environment & Natural Resources, Renmin University of China, Beijing 100872, China
    3. Guangzhou Shipbuilding International Company Limited, Guangzhou 511466, China
    4. School of Ship and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212100, China
  • Received:2023-09-12 Revised:2023-10-08 Online:2024-03-25 Published:2023-10-27
  • Supported by:
    High-tech Ship Research Project of the Ministry of Industry and Information Technology(CBZ1N21-1)

Abstract:

In the view of delayed data updates and inaccurate calculations on the carbon emission factor of the national power grid, a calculation method based on IPCC's carbon emission accounting method is proposed for the factor. IPCC's carbon emission accounting method can be employed on 25 kinds of fuels for power generation. First, carbon emission factors of the national power grid from 2005 to 2022 are obtained by the proposed methods. Then, the calculation results are compared with the official published data with an average deviation of 1.45%, which prove the accuracy of the algorithm. Finally, the emission factors from 2023 to 2035 are predicted under three scenarios, basic scenario, low-carbon scenario, and intensive carbon reduction scenario. In 2035, the emission factor decreased to 0.506 4, 0.480 7,and 0.443 8 kg/(kW·h) under the three scenarios,keeping the carbon emissions from power industry constantly low. As the proposed method has a high accuracy, it can dynamically reflect the current situation and development trend of China's power structure, and provide support for accurate evaluating on carbon emissions from electricity consumers.

Key words: national power grid, carbon emission factor, carbon emissions, renewable energy, scenario prediction, carbon intensity

CLC Number: