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基于非随机样本的煤电平均碳足迹量化方法

王志轩 张晶杰 石丽娜 冯田丰 王晨龙 杜歆欣 雷雨蔚 谷尔雪

中国电力2026,Vol.59Issue(2):71-80,10.
中国电力2026,Vol.59Issue(2):71-80,10.DOI:10.11930/j.issn.1004-9649.202510069

基于非随机样本的煤电平均碳足迹量化方法

Method for quantifying the average carbon footprint of coal-fired power based on non-random samples

王志轩 1张晶杰 1石丽娜 1冯田丰 2王晨龙 3杜歆欣 4雷雨蔚 1谷尔雪5

作者信息

  • 1. 中国电力企业联合会,北京 100761
  • 2. 国家能源集团电力营销公司,北京 100011
  • 3. 中国电力企业联合会,北京 100761||中电联电力发展研究院有限公司,北京 100162
  • 4. 中国电力企业联合会,北京 100761||中国华电科工集团有限公司,北京 100160
  • 5. 北京低碳清洁能源研究院,北京 102211
  • 折叠

摘要

Abstract

To address the challenge of selecting representative units for quantifying the average carbon footprint per unit of electricity generation of coal-fired units nationwide or in a specific region,and to provide scientific support for the quantification of the average carbon footprint factors of coal-fired power across the country,it is necessary for the research to focus on the representativeness analysis method of non-random samples for the overall carbon footprint of coal-fired power.As the dominant source of carbon emissions in China's power industry(accounting for approximately 88%),coal-fired power,due to its large installed capacity and complex in-fluencing factors,makes analyzing overall characteristics through representative samples a feasible approach.Firstly,it is clarified that the core links of coal-fired power carbon footprint are coal combustion(accounting for 93.0%)and coal acquisition(accounting for 6.5%),jointly contributing to over 99%of carbon emissions.The coal consumption level and the carbon emission factor of power coal are the essential factors affecting the carbon footprint.Secondly,three types of methods for constructing new representative samples based on over a hundred existing quantitative samples are proposed,including indirectly proving representativeness through consistency verification of key parameters,supplementing missing samples by multi-dimensional stratification,and conducting weighted resampling to match the overall distribution.Finally,171 sample datasets are generated by combining existing data.The deviations between their power generation coal consumption(286.9 g/(kW·h))and carbon content per unit calorific value(26.39 t/TJ)with the corresponding indicators of the overall population composed of 1 964 power plants(286.7 g/(kW·h)and 26.28 t/TJ)are only-0.07%and-0.415%,respectively,verifying the effectiveness of the proposed methods.

关键词

燃煤发电/碳足迹/非随机样本/数理分析

Key words

coal-fired power generation/carbon footprint/non-random samples/mathematical analysis

引用本文复制引用

王志轩,张晶杰,石丽娜,冯田丰,王晨龙,杜歆欣,雷雨蔚,谷尔雪..基于非随机样本的煤电平均碳足迹量化方法[J].中国电力,2026,59(2):71-80,10.

基金项目

智能电网重大专项(2030)资助项目(2025ZD0807900). This work is supported by Smart Grid National Science and Technology Major Proiect(No.2025ZD0807900). (2030)

中国电力

1004-9649

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