电碳耦合机制下多元主体综合成本分析

doi:10.11930/j.issn.1004-9649.202404029

摘要/Abstract

摘要：

电碳耦合交易是未来发展的趋势。构建计及电碳耦合不同主体的发电成本计算模型有利于发电主体制定决策以及电力交易机构监管市场的可靠运行。通过全寿命周期法分析电碳耦合下多元电力市场主体的成本构成，提出电碳耦合机制下以火电为代表的传统能源机组和以光伏为代表的新能源机组的综合成本核算方法。基于河北省南网自然禀赋，进行市场主体的综合成本计算及灵敏度分析，并量化电碳耦合机制对不同机组综合成本的变化情况。结果表明，火电机组的综合成本对碳排放因子变化高度敏感，而光伏机组的综合成本则主要受运行费用和发电利用小时数的影响。研究可为进一步完善电价机制和市场化制度、加速机组改造和促进能源结构转型提供参考。

关键词: 电力市场, 碳市场, 综合成本, 新型电力系统, 全生命周期法

Abstract:

Under the dual carbon vision, the electricity-carbon coupling trading is a development trend in the future. Constructing a generation cost calculation model considering the electricity-carbon coupling of different market entities is beneficial for the decision-making of power generation entities and for the reliable operation of the market under the supervision of power trading institutions. By analyzing the cost structure of multiple power market entities under the electricity-carbon coupling with the life cycle method, a comprehensive cost accounting method for the traditional energy units represented by thermal power and the new energy units represented by photovoltaic under the electricity-carbon coupling mechanism is proposed. Based on the southern power grid of Hebei Province, the comprehensive cost of the market entities is calculated and sensitivity analysis is carried out, and the impacts of the electricity-carbon coupling mechanism on the comprehensive costs of different power units are quantified. The rusults show that the comprehensive cost of the thermal power units is highly sensitive to changes in carbon emission factors, while the comprehensive cost of photovoltaic units is mainly affected by operating costs and power generation utilization hours. This study can provide a references for further improving the electricity price mechanism and market-oriented system, accelerating unit transformation, and promoting energy structure transformation.

Key words: electricity market, carbon market, comprehensive cost, new power system, life cycle method

王艳阳, 李建朝, 刘景青, 唐程, 王剑涛, 卢锦玲, 任惠. 电碳耦合机制下多元主体综合成本分析[J]. 中国电力, 2025, 58(6): 180-189.

WANG Yanyang, LI Jianzhao, LIU Jingqing, TANG Cheng, WANG Jiantao, LU Jinling, REN Hui. Comprehensive Cost Analysis of Multiple Entities under the Coupling Mechanism of Electricity and Carbon[J]. Electric Power, 2025, 58(6): 180-189.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202404029

https://www.electricpower.com.cn/CN/Y2025/V58/I6/180

图/表 15

图 1 电碳耦合市场成员关系

Fig.1 Member relationships in the electricity carbon coupling market

表 1 成本计算模型

Table 1 Cost calculation models

成本计算模型	使用场景	适用对象	特点
全生命周期LCOE^[5]	电能量市场	各种发电方式	—
系统平准化度电成本SLCOE^[13]	电能量市场	可再生能源发电	考虑可再生能源的平衡成本
综合平准化度电成本CLCOE^[6]	电碳耦合市场	可再生能源发电	考虑绿色发电补贴

图 2 综合成本分析方法示意

Fig.2 Schematic diagram of comprehensive cost analysis method

图 3 2023年碳交易挂牌均价（样本值）及拟合曲线（理论值）

Fig.3 Average listing price (sample value) of carbon trading in 2023 and fitting curve (theoretical value)

表 2 混合高斯分布参数

Table 2 Mixed Gaussian distribution parameters

高斯分布参数	${x_1}$	${x_2}$	$ {x_3} $
加权系数值$ {\beta _k} $	0.6940	0.2085	0.0976
期望$\mu $	0.3249	–2.7769	4.4461
均方差$\sigma $	1.3831	4.4976	1.5982

图 4 碳价偏差值频数分布及概率密度曲线

Fig.4 Frequency distribution and probability density curve of carbon price deviation values

图 5 2023—2053年碳价预测值

Fig.5 Carbon price forecast for 2023-2053

表 3 机组基础参数

Table 3 Basic parameters of the unit

项目	火电	光伏
初始比投资/(元·kW^–1)	4526.1	5703.3
寿命/年	30	25
年折旧费用/(元·kW^–1)	143.3	228.13
年运行费用/(元·kW^–1)	57.0	48
改造费用/(元·kW^–1)	0	0
燃料价格/(元·t^–1)	734	0
残值率/%	5	0
附加费用/(元·kW^–1)	0	40.8
发电利用小时数/h	4379	1182
碳排放因子/(t·(MW·h)^–1)	0.96	0

图 6 电碳耦合机制下发电主体综合成本计算结果

Fig.6 Calculation results of comprehensive cost for power generation entities under the electricity carbon coupling mechanism

图 7 火电及光伏机组综合成本随碳排放因子基准值变化曲线

Fig.7 Curve of comprehensive cost of thermal power and photovoltaic units changing with the benchmark value of the carbon emission factor

表 4 燃料价格及碳排放因子的灵敏度

Table 4 Sensitivity of fuel prices and carbon emission factors

燃料价格/(元·t^–1)	碳排放因子/ (t·(MW·h)^–1)	燃料价格灵敏度	碳排放因子灵敏度
750	0.98	0.582	2.204
700	0.96	0.610	2.309
650	0.94	0.642	2.424
600	0.92	0.677	2.552
550	0.90	0.715	2.693

图 8 燃料价格及碳排放因子对火电机组综合成本的影响

Fig.8 The impact of fuel prices and carbon emission factors on the comprehensive cost of thermal power units

表 5 火电机组碳减排改造相关参数

Table 5 Parameters related to carbon reduction renovation of thermal power units

项目	改造前	改造后
改造费用/(元·kW^–1)	0	3618
厂用电率/%	4.8	24.11
年运行费用/(元·kW^–1)	57	260.24
碳排放因子/(t·(MW·h)^–1)	0.96	0.2671

表 6 运行费用与发电利用小时数的灵敏度

Table 6 Sensitivity of operating costs and power generation utilization hours

年运行费用/ (元·kW^–1)	发电利用小时数/h	年运行费用灵敏度	发电利用小时数灵敏度
48	1182	0.188	1.371
46	1249	0.191	1.374
44	1316	0.195	1.378
42	1383	0.199	1.382
40	1450	0.203	1.385

图 9 运行费用及发电利用小时数对光伏机组综合成本的影响

Fig.9 The impact of operating costs and power generation utilization hours on the comprehensive cost of PV units

参考文献 39

1	何伊慧, 管霖, 王彤, 等. 南方电网新型电力系统规划建设的量化评估与分析[J]. 南方电网技术, 2024, 18 (10): 40- 53.
	HE Yihui, GUAN Lin, WANG Tong, et al. Quantitative evaluation and analysis of planning and construction of the new power system in China southern power grid[J]. Southern Power System Technology, 2024, 18 (10): 40- 53.
2	邓盛盛, 陈皓勇, 肖东亮, 等. 考虑碳市场交易的寡头电力市场均衡分析[J]. 南方电网技术, 2024, 18 (1): 143- 152.
	DENG Shengsheng, CHEN Haoyong, XIAO Dongliang, et al. Equilibrium analysis of oligopoly electricity market considering carbon market trading[J]. Southern Power System Technology, 2024, 18 (1): 143- 152.
3	徐若晨, 张江涛, 刘明义, 等. 电化学储能及抽水蓄能全生命周期度电成本分析[J]. 电工电能新技术, 2021, 40 (12): 10- 18. DOI
	XU Ruochen, ZHANG Jiangtao, LIU Mingyi, et al. Analysis of life cycle cost of electrochemical energy storage and pumped storage[J]. Advanced Technology of Electrical Engineering and Energy, 2021, 40 (12): 10- 18. DOI
4	刘阳, 滕卫军, 谷青发, 等. 规模化多元电化学储能度电成本及其经济性分析[J]. 储能科学与技术, 2023, 12 (1): 312- 318.
	LIU Yang, TENG Weijun, GU Qingfa, et al. Scaled-up diversified electrochemical energy storage LCOE and its economic analysis[J]. Energy Storage Science and Technology, 2023, 12 (1): 312- 318.
5	蓝澜, 刘强, 陈梓, 等. 新能源比传统能源成本更高吗?——基于LCOE方法的中国风电与火电成本比较[J]. 西部论坛, 2013, 23 (3): 66- 72.
	LAN Lan, LIU Qiang, CHEN Zi, et al. Is the cost of renewable energy higher than traditional energy?——comparison of the cost between wind power and heat power in China based on LCOE[J]. West Forum, 2013, 23 (3): 66- 72.
6	聂洪光, 刘尚奇, 莫建雷. 补贴“退坡” 背景下可再生能源发电激励政策及发展路径研究: 基于拓展的平准化度电成本模型[J]. 中国地质大学学报(社会科学版), 2022, 22 (6): 66- 81.
	NIE Hongguang, LIU Shangqi, MO Jianlei. Incentive policies and development path of China’s renewable energy power under the background of declining subsidy: a study using comprehensive levelized cost of electricity (CLCOE) model[J]. Journal of China University of Geosciences (Social Sciences Edition), 2022, 22 (6): 66- 81.
7	吴琪, 赵宣茗, 张佳诚, 等. 促进新能源消纳的电-碳市场耦合激励型出清机制[J]. 电力建设, 2023, 44 (12): 14- 27. DOI
	WU Qi, ZHAO Xuanming, ZHANG Jiacheng, et al. Electricity-carbon market coupling incentive clearing mechanism to promote consumption of new energy[J]. Electric Power Construction, 2023, 44 (12): 14- 27. DOI
8	LI Z H, FANG T, CHEN C. Research on environmental cost fromthe perspective of coal-fired power plant[J]. Polish Journal of Environmental Studies, 2021, 30 (2): 1695- 1705. DOI
9	贾亚雷, 王继选, 韩中合, 等. 基于LCA的风力发电、光伏发电及燃煤发电的环境负荷分析[J]. 动力工程学报, 2016, 36 (12): 1000- 1009.
	JIA Yalei, WANG Jixuan, HAN Zhonghe, et al. Analysis on environmental load of wind, PV and coal-fired power generation based on life cycle assessment[J]. Journal of Chinese Society of Power Engineering, 2016, 36 (12): 1000- 1009.
10	张慧敏, 李晏, 冯天天, 等. 碳中和背景下跨省电力交易空间结构及影响因素研究[J]. 智慧电力, 2022, 50 (11): 56- 61. DOI
	ZHANG Huimin, LI Yan, FENG Tiantian, et al. Spatial structure and influencing factors of inter-provincial power transaction under carbon neutralization[J]. Smart Power, 2022, 50 (11): 56- 61. DOI
11	吴鸿亮, 刘羽霄, 张宁, 等. 南方电网西电东送中的碳交易模型及其效益分析[J]. 电网技术, 2017, 41 (3): 745- 751.
	WU Hongliang, LIU Yuxiao, ZHANG Ning, et al. Carbon trading models and benefit analysis in CSG west-to-east power transmission[J]. Power System Technology, 2017, 41 (3): 745- 751.
12	董福贵, 郗来昊, 孟子航. 考虑碳交易的电力现货市场出清多阶段优化模型研究[J]. 电网技术, 2024, 48 (1): 79- 96.
	DONG Fugui, CHI Laihao, MENG Zihang. Multi-stage optimization model for electricity spot market clearing considering carbon trading[J]. Power System Technology, 2024, 48 (1): 79- 96.
13	CHONG S J, WU J, CHANG I S. Cost accounting and economic competitiveness evaluation of photovoltaic power generation in China: based on the system levelized cost of electricity[J]. Renewable Energy, 2024, 222, 119940. DOI
14	王蕊. 我国碳金融市场中碳交易价格的影响因素分析: 基于面板分位数模型[D]. 西安: 西北大学, 2021.
	WANG Rui. The research on the infulence factors of carbon emission price in China-empirical study based on the panel quantile model[D]. Xi’an: Northwest University, 2021.
15	王娜. 基于大数据的碳价预测[J]. 统计研究, 2016, 33 (11): 56- 62.
	WANG Na. Forecasting of carbon price based on big data[J]. Statistical Research, 2016, 33 (11): 56- 62.
16	秦全德, 黄兆荣, 黄凯珊. 一种基于局部回归的多尺度碳市场价格预测模型研究[J]. 运筹与管理, 2022, 31 (1): 107- 114.
	QIN Quande, HUANG Zhaorong, HUANG Kaishan. A multi-scale carbon price forecasting model withLocal regression approach[J]. Operations Research and Management Science, 2022, 31 (1): 107- 114.
17	DONG H W, HU Y, YANG Y H, et al. A multi-strategy integration prediction model for carbon price[J]. Energies, 2023, 16 (12): 4613. DOI
18	王科, 李思阳. 中国碳市场回顾与展望(2022)[J]. 北京理工大学学报(社会科学版), 2022, 24 (2): 33- 42.
	WANG Ke, LI Siyang. China’s carbon market: reviews and prospects(2022)[J]. Journal of Beijing Institute of Technology (Social Sciences Edition), 2022, 24 (2): 33- 42.
19	王一蓉, 陈浩林, 林立身, 等. 考虑电力行业碳排放的全国碳价预测[J]. 中国电力, 2024, 57 (5): 79- 87.
	WANG Yirong, CHEN Haolin, LIN Lishen, et al. National carbon price prediction considering carbon emissions from the power industry[J]. Electric Power, 2024, 57 (5): 79- 87.
20	上海环境能源交易所[EB/OL]. https://www.cneeex.com/.
21	严涛, 江开忠, 姜新盈, 等. 基于高斯混合聚类采样的不平衡数据处理方法[J]. 计算机应用与软件, 2023, 40 (12): 305- 311. DOI
	YAN Tao, JIANG Kaizhong, JIANG Xinying, et al. Unbalanced data processing method based on Gaussian mixture clustering[J]. Computer Applications and Software, 2023, 40 (12): 305- 311. DOI
22	王强, 张津, 李上杨. 抗噪性高斯过程用于风电系统暂态电压稳定性的评估[J]. 南方电网技术, 2024, 18 (9): 126- 137.
	WANG Qiang, ZHANG Jin, LI Shangyang. Transient voltage stability assessment of wind power system based on noisy input multi-class gaussian process[J]. Southern Power System Technology, 2024, 18 (9): 126- 137.
23	李丹, 梁云嫣, 缪书唯, 等. 基于高斯混合聚类和改进条件变分自编码的多风电场功率日场景生成方法[J]. 中国电力, 2024, 57 (12): 17- 29.
	LI Dan, LIANG Yunyan, MIAO Shuwei, et al. Daily power scenario generation method for multiple wind farms based on Gaussian mixture clustering and improved conditional variational autoencoder[J]. Electric Power, 2024, 57 (12): 17- 29.
24	房玉杰, 张松, 刘晋, 等. 基于高斯混合模型的脚步声身份识别方法[J]. 计算机应用, 2021, 41 (S2): 221- 225.
	FANG Yujie, ZHANG Song, LIU Jin, et al. Footstep identification method based on Gaussian mixture model[J]. Journal of Computer Applications, 2021, 41 (S2): 221- 225.
25	RUAN L Y, YUAN M, ZOU H. Regularized parameter estimation in high-dimensional Gaussian mixture models[J]. Neural Computation, 2011, 23 (6): 1605- 1622. DOI
26	XIA R, ZHANG Q Y, DENG X Y. Multiscale Gaussian convolution algorithm for estimate of Gaussian mixture model[J]. Communications in Statistics - Theory and Methods, 2019, 48 (23): 5889- 5910. DOI
27	保定市-满城区建设热电厂二期项目[EB/OL]. (2023-11-01) [2023-12-27]. http://www.hebpi.com/xmk/403507.
28	石家庄市-经济技术开发区建设高速沿线分布式光伏项目[EB/OL]. (2023-12-26) [2023-12-27]. http://www.hebpi.com/xmk/414208.
29	陈巍, 江岳文. 碳-绿证-电量市场耦合交易优化研究[J]. 电网技术, 2023, 47 (6): 2273- 2287.
	CHEN Wei, JIANG Yuewen. Trading optimization of carbon-green certificate-electricity market coupling[J]. Power System Technology, 2023, 47 (6): 2273- 2287.
30	《2019-2020年全国碳排放权交易配额总量设定与分配实施方案 (发电行业)》[Z]. 2020.
31	MORRIS M D. Factorial sampling plans for preliminary computational experiments[J]. Technometrics, 1991, 33 (2): 161- 174. DOI
32	中矿(北京)煤炭产业景气指数研究课题组. 2022—2023年中国煤炭产业经济形势研究报告[J]. 中国煤炭, 2023, 49 (3): 2- 10.
	Research Group of Zhongkuang (Beijing) Coal Industry Prosperity Index. Research report on the economic situation of China’s coal industry from 2022 to 2023[J]. China Coal, 2023, 49 (3): 2- 10.
33	张彩庆, 史惠卿, 郑楠. 计及碳交易和碳税的碳捕集技术经济性研究[J]. 动力工程学报, 2023, 43 (6): 787- 795.
	ZHANG Caiqing, SHI Huiqing, ZHENG Nan. Techno-economic analysis of coal-fired plant integrated carbon capture and storage considering carbon trading and carbon tax[J]. Journal of Chinese Society of Power Engineering, 2023, 43 (6): 787- 795.
34	MORRIS J, KHESHGI H, PALTSEV S, et al. Scenarios for the deployment of carbon capture and storage in the power sector in a portfolio of mitigation options[J]. Climate Change Economics, 2021, 12 (1): 2150001. DOI
35	朱明亮. 中国电力能源替代经济性及路径研究[D]. 北京: 华北电力大学, 2021.
	ZHU Mingliang. Study on ecnomy and path of China’s electric power energy substitution[D]. Beijing: North China Electric Power University, 2021.
36	刘录清, 余云川, 高银霞. 基于实物期权的光伏电站项目LCOE分析[J]. 太阳能, 2023, (10): 12- 20.
	LIU Luqing, YU Yunchuan, GAO Yinxia. LCOE analysis of PV power station projects based on real options[J]. Solar Energy, 2023, (10): 12- 20.
37	全国各省市光伏电站最佳安装倾角、发电量、年有效利用小时数速查表[EB/OL](2021-8-24)[2023-12-27]https://guangfu.bjx.com.cn/news/20210824/1172006.shtml.
38	肖黎明. 设备衰减率对太阳能光伏发电利用小时数的影响分析[J]. 华电技术, 2017, 39 (12): 67- 69, 72, 76.
	XIAO Liming. Impact analysis of equipment attenuation rate to the PV power generating equipment availability hour[J]. Huadian Technology, 2017, 39 (12): 67- 69, 72, 76.
39	马月, 吕永刚, 吴琼, 等. 山地光伏电站光伏组件阴影遮挡技改方案的经济性分析[J]. 太阳能, 2023, (10): 69- 74.
	MA Yue, LYU Yonggang, WU Qiong, et al. Economic benefit analysis of shadow shading technology transformation for mountain PV power stations[J]. Solar Energy, 2023, (10): 69- 74.

[1]	叶小宁, 王彩霞, 时智勇, 步雨洛, 杨超, 吴思. 国外高比例新能源消纳分析及对中国新能源可持续发展的建议[J]. 中国电力, 2025, 58(6): 137-144.
[2]	刘姜伟, 陈亦平, 肖云鹏, 陈凯, 郭瑾程, 王建学. 水电参与电力市场研究综述[J]. 中国电力, 2025, 58(6): 156-171.
[3]	赵彤, 李雪松, 周浩, 丁羽, 杨斌, 王文涛, 王鹏. 基于动态碳排放强度的电碳市场耦合建模方法及市场优化机制分析[J]. 中国电力, 2025, 58(4): 31-43.
[4]	李健, 张钧, 韩新阳, 靳晓凌. 新型电力系统形态量化推演方法的总体框架与功能设计[J]. 中国电力, 2025, 58(3): 1-7, 97.
[5]	高志远, 庄卫金, 李峰, 于芳, 张鸿, 王艳, 夏旻. 调控领域人工智能应用的高复用性验证平台[J]. 中国电力, 2025, 58(3): 142-150.
[6]	朱瑞, 娄奇鹤, 靳晓凌, 刘畅. 适应新型电力系统的电网基建功能化投资结构演化研究[J]. 中国电力, 2024, 57(9): 194-204.
[7]	傅观君, 张富强, 夏鹏, 冯君淑, 张晋芳. 天然气发电在新型电力系统中的功能定位及发展前景研判[J]. 中国电力, 2024, 57(8): 67-74.
[8]	翟苏巍, 李银银, 杜凡, 李文云, 潘凯岩, 梁峻恺. 考虑海量分布式能源接入的配电网分布式无功控制策略[J]. 中国电力, 2024, 57(8): 138-144.
[9]	李碧君, 李威, 董希建. 新型电力系统中主控型安全稳定服务质量的在线评估[J]. 中国电力, 2024, 57(8): 168-181.
[10]	高政南, 姜楠, 陈启鑫, 徐江, 王海利, 辛力, 徐青贵. 德国电力市场能源转型建设及启示[J]. 中国电力, 2024, 57(6): 204-214.
[11]	王一蓉, 陈浩林, 林立身, 唐进. 考虑电力行业碳排放的全国碳价预测[J]. 中国电力, 2024, 57(5): 79-87.
[12]	李汶龙, 周云, 罗祾, 陈甜甜, 冯冬涵. 计及现货交易的电能量交易全环节用电碳责任分摊[J]. 中国电力, 2024, 57(5): 99-112.
[13]	李祥光, 谭青博, 李帆琪, 李旭东, 谭忠富. 电碳耦合对煤电机组现货市场结算电价影响分析模型[J]. 中国电力, 2024, 57(5): 113-125.
[14]	王雪, 刘林, 卓庆东, 张海鹏, 杨苓, 许方园, 曹雨晨. 基于虚拟惯量控制的新型电力系统功率差前馈振荡抑制方法[J]. 中国电力, 2024, 57(4): 68-76.
[15]	张宇, 魏新迟, 冯凯辉, 时珊珊, 孟子涵, 梁媛. 计及分布式光伏承载力的配电网侧独立储能充放电策略[J]. 中国电力, 2024, 57(4): 111-117.