基于非随机样本的煤电平均碳足迹量化方法

doi:10.11930/j.issn.1004-9649.202510069

中国电力 ›› 2026, Vol. 59 ›› Issue (2): 71-80.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

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

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. 中电联电力发展研究院有限公司，北京　100162
4. 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

收稿日期:2025-10-24 修回日期:2025-12-31 发布日期:2026-03-04 出版日期:2026-02-28
作者简介:
王志轩（1955），男，高级工程师（教授级），从事电力环保低碳发展等研究，E-mail：wangzhixuan@cec.org.cn
张晶杰（1973），女，通信作者，正高级经济师，从事能源电力发展、节能减排法规政策等研究，E-mail：zhangjingjie@cec.org.cn
基金资助:
智能电网重大专项（2030）资助项目（2025ZD0807900）。

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

WANG Zhixuan¹(), ZHANG Jingjie¹(), SHI Lina¹, FENG Tianfeng², WANG Chenlong¹^,³, DU Xinxin¹^,⁴, LEI Yuwei¹, GU Erxue⁵

1. China Electricity Council, Beijing 100761, China
2. Electric Power Marketing Company of National Energy Group, Beijing 100011, China
3. Electric Power Development Research Institute Co., Ltd. of China Electricity Council, Beijing 100162, China
4. China Huadian Engineering Co., Ltd., Beijing 100160, China
5. National Institute of Clean-and-Low-Carbon Energy, Beijing 102211, China

Received:2025-10-24 Revised:2025-12-31 Online:2026-03-04 Published:2026-02-28
Supported by:
This work is supported by Smart Grid National Science and Technology Major Proiect (No.2025ZD0807900).

摘要/Abstract

摘要：

为解决全国或某地区的燃煤机组单位发电量平均碳足迹量化中面临的代表性机组选取难题，给全国煤电碳足迹平均因子量化提供科学支撑，研究聚焦煤电碳足迹非随机样本对总体的代表性分析方法很有必要。煤电作为中国电力行业碳排放主导来源（占比约88%），因装机规模大、影响因素复杂，通过代表性样本分析总体特征成为可行路径。首先，明确煤电碳足迹核心环节为煤炭燃烧（占93.0%）与煤炭获取（占6.5%），合计贡献超99%碳排放，煤耗水平与电煤碳排放因子是影响碳足迹的本质因素；然后，提出基于已有百余个量化样本构建代表性新样本的3类方法，包括通过关键参数一致性验证间接证明代表性、按多维度分层补充缺失样本、加权重抽样匹配总体分布等；最后，基于现有数据组合生成171个样本数据集，其发电煤耗（286.9 g/(kW·h)）、单位热值含碳量（26.39 t/TJ）与1964个电厂组成的总体对应指标（286.7 g/(kW·h)、26.28 t/TJ）偏差仅为–0.07%、–0.415%，验证了所提方法的有效性。

关键词: 燃煤发电, 碳足迹, 非随机样本, 数理分析

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 influencing 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 1964 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.

Key words: coal-fired power generation, carbon footprint, non-random samples, mathematical analysis

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.

WANG Zhixuan, ZHANG Jingjie, SHI Lina, FENG Tianfeng, WANG Chenlong, DU Xinxin, LEI Yuwei, GU Erxue. Method for quantifying the average carbon footprint of coal-fired power based on non-random samples[J]. Electric Power, 2026, 59(2): 71-80.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202510069

https://www.electricpower.com.cn/CN/Y2026/V59/I2/71

图/表 5

图 1 典型燃煤发电碳足迹量化边界示意

Fig.1 Quantification boundary of carbon footprint for typical coal-fired power generation

图 2 碳足迹试算机组在生命周期阶段各类别排放占比（含基建设备）

Fig.2 Proportion of various categories of emissions in the life cycle stage of the power units (including the infrastructure equipment) for carbon footprint calculation

图 3 方差贡献率分析

Fig.3 Analysis of variance contribution rate

图 4 根据燃煤机组环境统计数据测算得到的分布特征

Fig.4 Distribution characteristics obtained through calculation based on environmental statistical data of coal-fired units

表 1 非随机样本选取与总体特征参数的对比

Table 1 Comparison between non-random sample selection and population characteristic parameters

特征值	样本（171个）	总体（1964个）
发电煤耗/(g·(kW·h)^–1)	286.9	286.7
煤耗标准差/(g·(kW·h)^–1)	2.06	1.12
单位热值含碳量/(t·TJ^–1)	26.39	26.28
单位热值含碳量标准差/(t·TJ^–1)	0.41	0.20

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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

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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

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