2005—2035年全国电网碳排放因子的计算与预测

doi:10.3969/j.issn.2097-0706.2024.03.009

综合智慧能源 ›› 2024, Vol. 46 ›› Issue (3): 72-78.doi: 10.3969/j.issn.2097-0706.2024.03.009

2005—2035年全国电网碳排放因子的计算与预测

魏夕凯¹^,²(), 谭效时¹, 林明³, 程俊杰⁴, 向可祺¹, 丁书欣³

1.中国船舶集团有限公司第七一四研究所，北京 100020
2.中国人民大学环境学院，北京 100872
3.广船国限公司，广州 511466
4.江苏科技大学船舶与海洋工程学院，江苏镇江 212100

收稿日期:2023-09-12 修回日期:2023-10-08 发布日期:2023-10-27 出版日期:2024-03-25
作者简介:魏夕凯（1999），男，工程师，硕士，从事电力碳排放核算、产品碳足迹等方面的研究，wxk7140732@163.com。
基金资助:
工业与信息化部高技术船舶科研项目(CBZ1N21-1)

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. 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:2023-10-27 Published:2024-03-25
Supported by:
High-tech Ship Research Project of the Ministry of Industry and Information Technology(CBZ1N21-1)

摘要/Abstract

摘要：

为解决全国电网碳排放因子数据更新滞后、计算方法不明确等问题，提出一种基于联合国政府间气候变化专门委员会（IPCC）碳核算法的全国电网碳排放因子计算方法。IPCC碳核算法涵盖了火力发电的25种能源。首先，计算2005—2022年全国电网碳排放因子；其次，通过对比全国电网碳排放因子的计算结果与官方公布数据，检验该方法的准确性，两者平均偏差仅为1.45%；最后，在基准情景、低碳情景和强化情景下，对2023—2035年的碳排放因子进行预测。2035年碳排放因子在3种情景中分别下降至0.506 4，0.480 7，0.443 8 kg/（kW·h），电力低碳化水平持续提高。该计算方法具有较高的准确性，可动态反映我国电力结构的现状及变化趋势，为准确评估企业用电实际碳排放提供有力支撑。

关键词: 全国电网, 碳排放因子, 碳排放量, 新能源, 情景预测, 碳强度

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

中图分类号:

TK01：TM7

魏夕凯, 谭效时, 林明, 程俊杰, 向可祺, 丁书欣. 2005—2035年全国电网碳排放因子的计算与预测[J]. 综合智慧能源, 2024, 46(3): 72-78.

WEI Xikai, TAN Xiaoshi, LIN Ming, CHENG Junjie, XIANG Keqi, DING Shuxin. Calculation and prediction of carbon emission factors for the national power grid from 2005 to 2035[J]. Integrated Intelligent Energy, 2024, 46(3): 72-78.

图/表 5

表1

表2

图1

图2

图3

参考文献 40

[1]	张森林. “双碳”背景下优化调整电网碳排放因子的思考[J]. 中国电力企业管理, 2022(22):62-65.
[2]	陈健华, 孙亮, 陈亮, 等. 国内外企业温室气体排放核算标准的比较分析[J]. 气候变化研究进展, 2016, 12(6):545-553.
	CHEN Jianhua, SUN Liang, CHEN Liang, et al. The comparative analysis on the national and international greenhouse gas emission accounting standards for the enterprise[J]. Climate Change Research, 2016, 12(6):545-553.
[3]	招景明, 李经儒, 潘峰, 等. 电力碳排放计量技术现状及展望[J]. 电测与仪表, 2023, 60(3):1-8.
	ZHAO Jingming, LI Jingru, PAN Feng, et al. Current status and future prospects of electricity carbon emission measurement technology[J]. Electrical Measurement and Instrumentation, 2023, 60(3):1-8.
[4]	马翠梅, 李士成, 葛全胜. 省级电网温室气体排放因子研究[J]. 资源科学, 2014, 36(5):1005-1012.
	MA Cuimei, LI Shicheng, GE Quansheng. Greenhouse gas emission factors for grid electricity for Chinese provinces[J]. Resource Science, 2014, 36(5):1005-1012.
[5]	宁礼哲, 张哲, 蔡博峰, 等. 2020年中国区域和省级电网温室气体排放因子研究[J]. 环境工程, 2023, 41(3):222-228.
	NING Lizhe, ZHANG Zhe, CAI Bofeng, et al. Research on China's regional and provincial electricity GHG emission factors in 2020[J]. Environmental Engineering, 2023, 41(3):222-228.
[6]	侯萍, 王洪涛, 张浩, 等. 用于组织和产品碳足迹的中国电力温室气体排放因子[J]. 中国环境科学, 2012, 32(6):961-967.
	HOU Ping, WANG Hongtao, ZHANG Hao, et al. Greenhouse gas emission factors from China's electricity sector for organizational and product carbon footprint[J]. China Environmental Science, 2012, 32(6):961-967.
[7]	张时聪, 王珂, 徐伟. 建筑碳排放标准化计算的电力碳排放因子取值研究[J]. 建筑科学, 2023, 39(2):46-57.
	ZHANG Shicong, WANG Ke, XU Wei. Study on the value of electricity emission factor for standardized calculation of building carbon emission[J]. Building Science, 2023, 39(2):46-57.
[8]	王少华, 王俊霞, 张荣荣. 全国碳市场正式上线运行[J]. 生态经济, 2021, 37(9):9-12.
	WANG Shaohua, WANG Junxia, ZHANG Rongrong. The national carbon market has been officially launched and put into operation[J]. Ecological Economy, 2021, 37 (9): 9-12.
[9]	惠婧璇. 欧盟“Fit for 55”一揽子气候立法提案解读及应对建议[J]. 中国能源, 2021, 43(11):9-14.
	HUI Jingxuan. Interpretation and response suggestions for the EU's "Fit for 55" climate legislation package[J]. Energy of China, 2021, 43(11):9-14.
[10]	刘阳, 刘继春, 杨语嫣. 考虑欧盟碳边境调节机制的碳-电融合市场各主体决策行为研究[J]. 电网技术, 2023, 47 (8):3111-3122.
	LIU Yang, LIU Jichun, YANG Yuyan. Research on the decision-making behavior of various entities in the carbon electricity integration market considering the EU's carbon border regulation mechanism[J]. Power System Technology, 2023, 47(8):3111-3122.
[11]	尚楠, 陈政, 冷媛. 电碳市场背景下典型环境权益产品衔接互认机制及关键技术[J/OL]. 中国电机工程学报:1-19(2023-03-17)[2023-09-11]. http://kns.cnki.net/kcms/detail/11.2107.TM.20230316.1116.006.html.
	SHANG Nan, CHEN Zheng, LENG Yuang. Mutual recognition mechanism and key technologies of typical environmental interest products in power and carbon markets[J/OL]. Proceedings of the CSEE:1-19(2023-03-17)[2023-09-11]. http://kns.cnki.net/kcms/detail/11.2107.TM.20230316.1116.006.html.
[12]	刘志强, 赵毅, 潘荔. 中外火电节能减排效率分析与比较[J]. 热力发电, 2021, 50(3):9-18.
	LIU Zhiqiang, ZHAO Yi, PAN Li. Analysis and comparison of energy saving efficiency and emission reduction efficiency of thermal power between China and foreign countries[J]. Thermal Power Generation, 2021, 50(3): 9-18.
[13]	国家发展和改革委员会. “十四五”可再生能源发展规划[EB/OL].(2022-06-01)[2023-09-11]. https://www.ndrc.gov.cn/xwdt/tzgg/202206/P020220601502009073293.pdf.
[14]	国家发展和改革委员会. 关于做好2016、2017年度碳排放报告与核查及排放监测计划制定工作的通知[EB/OL].(2017-12-04) [2023-09-11]. https://www.gov.cn/xinwen/2017-12/15/content_5247303.htm.
[15]	生态环境部. 关于做好2022年企业温室气体排放报告管理相关重点工作的通知[EB/OL].(2023-03-05) [2023-09-11]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk06/202203/t20220315_971468.html.
[16]	生态环境部. 关于做好2023—2025年发电行业企业温室气体排放报告管理有关工作的通知[EB/OL].(2023-02-07)[2023-09-11]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk06/202302/t20230207_1015569.html.
[17]	The emissions & generation resource integrated database for 2012 technical support document[R]. US Environmental Protection Agency, 2012.
[18]	National greenhouse and energy reporting system measurement: Technical guidelines for the estimation of greenhouse gas emissions by facilities in Australia[R]. The Department of Industry,Innovation, Change Climate, Science, Research and Tertiary Education, 2013.
[19]	National inventory report 1990—2011: Greenhouse gas sources and sinks in Canada[R]. The Canadian Government's Submission to the UN Framework Convention on Climate Change, 2013.
[20]	2013 government GHG conversion factors for company reporting: Methodology paper for emission factors[R]. London: Department for Environment, Food and Rural Affairs, 2013.
[21]	Ministry for the Environment. Guidance for voluntary corporate greenhouse gas reporting: Data and methods for the 2011 calendar year[R]. Wellington: Ministry for the Environment, 2012.
[22]	刘昱良, 李姚旺, 周春雷, 等. 电力系统碳排放计量与分析方法综述[J/OL]. 中国电机工程学报:1-16(2023-06-27)[2023-09-11]. http://ifgga391f4815d8064db7sncxp90xkwwcq6x65.fhaz.libproxy.ruc.edu.cn/10.13334/j.0258-8013.pcsee.223452.
	LIU Yuliang, LI Yaowang, ZHOU Chunlei, et al. Overview of carbon measurement and analysis methods in power systems[J/OL]. Proceedings of the CSEE:1-16(2023-06-27)[2023-09-11]. http://ifgga391f4815d8064db7sncxp90xkwwcq6x65.fhaz.libproxy.ruc.edu.cn/10.13334/j.0258-8013.pcsee.223452.
[23]	HAWKES A D. Estimating marginal CO₂ emissions rates for national electricity systems[J]. Energy Policy, 2010, 38(10): 5977-5987. doi: 10.1016/j.enpol.2010.05.053
[24]	KHAN I, JACK M W, STEPHENSON J. Analysis of greenhouse gas emissions in electricity systems using time-varying carbon intensity[J]. Journal of Cleaner Production, 2018,184:1091-1101.
[25]	汪军, 程敏, 陈颖雯, 等. 汽车制造企业温室气体排放核算和参数因子研究[J]. 中国汽车, 2022(7):8-16.
	WANG Jun, CHENG Min, CHEN Yingwen, et al. Research on greenhouse gas emission accounting and emission factors and other parameters in the automobile manufacturing[J]. China Auto, 2022(7): 8-16.
[26]	李业辉, 包维瀚, 周特, 等. 基于碳排放流迭代算法的分布式碳表系统(二):系统设计与验证[J]. 电网技术, 2023, 47(7): 2682-2695.
	LI Yehui, BAO Weihan, ZHOU Te, et al. Distributed carbon meter system based on iterative calculation of carbon emission flow(II): System design and validation[J]. Power System Technology, 2023, 47(7):2682-2695.
[27]	惠婧璇, 朱松丽. 全国碳排放权交易市场下电解铝行业基准线法研究[J]. 气候变化研究进展, 2022, 18(3):366-372.
	HUI Jingxuan, ZHU Songli. Study on the benchmark method of China's electrolytic aluminum sector under national carbon emission trading market[J]. Climate Change Research, 2022, 18(3):366-372.
[28]	孟庆成, 胡垒, 李明健, 等. 建筑废弃物拆除阶段碳排放及碳补偿分析[J]. 环境工程, 2023, 41(7):45-52.
	MENG Qingcheng, HU Lei, LI Mingjian, et al. Analysis of carbon emission and carbon compensation in demolition of abandoned buildings[J]. Environmental Engineering, 2023, 41(7): 45-52.
[29]	国家统计局. 2022年国民经济和社会发展统计公报[EB/OL].(2023-02-28)[2023-09-11]. https://www.gov.cn/xinwen/2023-02/28/content_5743623.htm.
[30]	国家发展和改革委员会. 关于开展“十二五”单位国内生产总值二氧化碳排放降低目标责任考核评估的通知[EB/OL].(2016-12-01)[2023-09-11]. https://www.ccchina.org.cn/archiver/ccchinacn/UpFile/Files/Default/20160525170606757785.pdf.
[31]	张博庭. 我国水电的发展与能源革命电力转型[J]. 水力发电学报, 2020, 39(8):69-78.
	ZHANG Boting. Hydropower development, electric power transformation and energy revolution in China[J]. Journal of Hydroelectric Engineering, 2020, 39(8):69-78.
[32]	韩冬, 方红卫, 严秉忠, 等. 2013年中国水电发展现状[J]. 水力发电学报, 2014, 33(5): 1-5.
	HAN Dong, FANG Hongwei, YAN Bingzhong, et al. China's hydropower status in 2013[J]. Journal of Hydroelectric Engineering, 2014, 33(5): 1-5.
[33]	李雷, 郭焱, 于复坤. 中国光伏产业“十二五”发展回顾与当前瓶颈分析[J]. 中外能源, 2016, 21(11):21-29.
	LI Lei, GUO Yan, YU Fukun. A review of China's photovoltaic industry in twelfth Five-Year Plan period and bottlenecks currently faced[J]. Sino-Global Energy, 2016, 21(11):21-29.
[34]	徐刚磊. 新形势下西南大型水电可持续发展机制的探讨[J]. 华电技术, 2021, 43(5): 80-85.
	XU Ganglei. Discussion on sustainable development of large hydropower projects in southwestern China under new situation[J]. Huadian Technology, 2021, 43(5): 80-85.
[35]	张金平, 周强, 王定美, 等. 太阳能光热发电技术及其发展综述[J]. 综合智慧能源, 2023, 45(2): 44-52. doi: 10.3969/j.issn.2097-0706.2023.02.006
	ZHANG Jinping, ZHOU Qiang, WANG Dingmei, et al. Review on solar thermal power generation technologies and their development[J]. Integrated Intelligent Energy, 2023, 45(2): 44-52. doi: 10.3969/j.issn.2097-0706.2023.02.006
[36]	任东明. “十三五”可再生能源发展展望[J]. 科技导报, 2016, 34(1):133-138.
	REN Dongming. Outlook for renewable energy development of 13th Five Year Plan[J]. Science & Technology Review, 2016, 34(1):133-138.
[37]	张忠华, 李春山, 胡杰, 等. 东北地区碳排放现状分析与“双碳”目标下新能源发展建议[J]. 东北电力技术, 2022, 43(8):1-5.
	ZHANG Zhonghua, LI Chunshan, HU Jie, et al. Analysis of current situation of carbon emission and suggestions on new energy development under dual-carbon goal in northeast China[J]. Northeast Electric Power Technology, 2022, 43(8):1-5.
[38]	舒印彪, 张丽英, 张运洲, 等. 我国电力碳达峰、碳中和路径研究[J]. 中国工程科学, 2021, 23(6):1-14.
	SHU Yinbiao, ZHANG Liying, ZHANG Yunzhou, et al. Carbon peak and carbon neutrality path for China's power industry[J]. Strategic Study of CAE, 2021, 23(6):1-14.
[39]	王丽娟, 张剑, 王雪松, 等. 中国电力行业二氧化碳排放达峰路径研究[J]. 环境科学研究, 2022, 35(2):329-338.
	WANG Lijuan, ZHANG Jian, WANG Xuesong, et al. Pathway of carbon emission peak in China's electric power industry[J]. Research of Environmental Sciences, 2022, 35(2):329-338.
[40]	李萍, 杨红义, 刘琳, 等. “碳中和”目标下中国核电发展[J]. 节能技术, 2023, 41(1):10-15.
	LI Ping, YANG Hongyi, LIU Lin, et al. Development of nuclear power in China under carbon neutrality target[J]. Energy Conservation Technology, 2023, 41(1):10-15.

能源	折算标准煤系数	标准煤碳排放系数/（t·t^-1）
原煤	0.714 3 t/t	2.64
洗精煤	0.900 0 t/t	2.64
其他洗煤	0.285 7 t/t	2.64
型煤	0.600 0 t/t	2.64
煤矸石	0.285 7 t/t	2.64
焦煤	0.971 4 t/t	2.64
焦炉煤气	6.143 0 t/万m³	2.64
高炉煤气	1.286 0 t/万m³	2.64
转炉煤气	2.714 0 t/万m³	2.64
其他煤气	3.570 1 t/万m³	2.64
其他焦化产品	1.300 0 t/t	2.64
热力	0.034 1 t/GJ	2.64
原油	1.428 6 t/t	2.08
汽油	1.471 4 t/t	2.08
煤油	1.471 4 t/t	2.08
柴油	1.457 1 t/t	2.08
燃料油	1.428 6 t/t	2.08
石脑油	1.500 0 t/t	2.08
石油焦	1.091 8 t/t	2.08
液化石油气	1.200 0 t/t	2.08
炼厂干气	1.714 3 t/t	2.08
其他石油制品	1.571 4 t/t	2.08
天然气	12.143 0 t/万m³	1.63
液化天然气	1.757 2 t/t	1.63
其他能源	—	2.64

年份	碳排放因子
年份	官方公布数据/ [kg·（kW·h）^-1]	本文计算数据/ [kg·（kW·h）^-1]	偏差/%
2015	0.610 1	0.621 5	1.87
2016	0.605 3	0.603 6	0.27
2017	0.600 4	0.595 8	0.76
2018	0.595 6	0.589 1	1.08
2019	0.590 7	0.577 1	2.30
2020	0.585 9	0.567 4	3.14
2021	0.581 0	0.568 8	2.10
2022	0.570 3	0.569 8	0.09

2005—2035年全国电网碳排放因子的计算与预测

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

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