中国电网全生命周期碳排放及发电结构转型路径规划研究

doi:10.12006/j.issn.1673-1719.2023.177

摘要/Abstract

摘要：

为评估中国电网全生命周期碳排放强度并研究其转型达峰路径，首先提出全国和各地区电网全生命周期碳排放因子测算模型，测算历年全网全生命周期碳排放强度并分析其影响因素；其次利用情景分析法，分析不同电力转型情景下2022—2060年我国电网全生命周期碳排放量及其达峰情况。研究表明：(1) 2011—2021年我国发电结构转型取得一定成效，全网全生命周期碳排放因子由763.94 g/(kW·h)降至557.73 g/(kW·h)；但清洁能源发电减少的碳排放量无法平衡火电增加的碳排放量，全网全生命周期碳排放量仍以年均2.6%的速度增长，由36.1 亿t增至46.8 亿t。(2)发电结构清洁化和煤电减碳技术进步是降低全网全生命周期碳排放强度的重要举措。(3)快转型情景、基准情景、慢转型情景下我国电网全生命周期碳排放量可分别于2025、2027、2030年达峰，基准情景的碳排放量峰值为52.05 亿t，2060年碳排放量为15.78 亿t。

关键词: 碳达峰, 全生命周期, 碳排放因子, 发电结构, 情景分析法

Abstract:

To evaluate the lifecycle carbon emission intensity of the power industry and analyze its peak emission pathway, a calculation model for the national and regional power grid lifecycle carbon emission factors had been proposed, at the same time, the lifecycle carbon emission intensity of power over the years and its influencing factors had been measured. Then, using scenario analysis, the lifecycle carbon emissions and its peak situation of the power industry from 2022 to 2060 under different power transformation scenarios had been analyzed. The results show that: (1) From 2011 to 2021, China had achieved certain results in transforming its power generation structure. The lifecycle carbon emission factor of the national power grid decreased from 763.94 to 557.73 g/(kW·h). However, the reduction in carbon emissions from clean energy generation was unable to offset the increase in carbon emissions from thermal power, resulting in the lifecycle carbon emissions of the power industry still growing at an average annual rate of 2.6%, increasing from 3.61 Gt to 4.68 Gt. (2) The transition to cleaner power generation and advancement in decarbonization technologies for coal power are important measures to reduce the lifecycle carbon emission intensity of the power industry. (3) Under the fast transition scenario, the baseline scenario, and the slow transition scenario, China’s lifecycle carbon emissions from power industry can reach the peak in 2025, 2027 and 2030, respectively, and the baseline scenario will have a peak of 5.205 Gt carbon emissions and 1.578 Gt carbon emissions in 2060, which is lower than the carbon absorption capacity of China’s natural ecosystems.

Key words: Carbon peaking, Whole life cycle, Carbon emission factor, Power generation structure, Scenario analysis

田佩宁, 梁肖, 官雨捷, 赵义馨, 毛保华, 薛婷. 中国电网全生命周期碳排放及发电结构转型路径规划研究[J]. 气候变化研究进展, 2024, 20(1): 97-106.

TIAN Pei-Ning, LIANG Xiao, GUAN Yu-Jie, ZHAO Yi-Xin, MAO Bao-Hua, XUE Ting. Whole life cycle carbon emission and power generation structure transformation pathway planning of China’s power[J]. Climate Change Research, 2024, 20(1): 97-106.

图/表 11

表1 发电方式全生命周期的碳排放因子

Table 1 Carbon emission factors for the whole life cycle of each power generation method

图1 2011—2021年全网全生命周期碳排放因子、碳排放量和全国分方式发电量

Fig. 1 Carbon emission factors and carbon emissions of the whole life cycle of power in 2011-2021

图2 2021年各省发电结构及全生命周期碳排放因子注：1)坐标轴横轴为各省所属的区域电网名称；2)由于缺乏我国各省份火电细分方式（煤电、气电、油电、生物质发电）下的发电量统计数据，仅整理得到火电总发电量数据，同时考虑到我国气电、油电、生物质发电的发电量占比较低，仅分别为3.40%、0.02%、1.97%，影响较小，因此以煤电全生命周期碳排放因子作为火电全生命周期碳排放因子进行计算，这可能导致各省全生命周期碳排放因子的计算结果普遍偏大。

Fig. 2 Carbon emission factors of the whole life cycle of power in each province in 2021

图3 发电结构对全网全生命周期碳排放因子的影响注：水电、核电、气电、油电、生物质发电的发电量占比分别为16%、6%、4%、0%、2%。

Fig. 3 Impact of power generation structure on the whole life cycle carbon emission factors of power

图4 各发电方式全生命周期碳排放因子下降对全网全生命周期碳排放因子的影响

Fig. 4 The impact of the decline in the whole life cycle carbon emission factors of each power on the whole life cycle carbon emission factors of power

图5 2010—2060年人均发电量及总发电量

Fig. 5 Power generation per capita and total power generation from 2010 to 2060

表2 发电量占比年均变化率设置

Table 2 Generation structure scenario setting %

表3 煤电CCS技术发展水平设置

Table 3 Coal power CCS technology development level setting

表4 不同情景的发电量占比

Table 4 Generation structure of different scenarios %

图6 3种情景下全网全生命周期碳排放指标

Fig. 6 Life-cycle carbon emission indicators for power under 3 scenarios

表5 不同文献电力碳达峰结果对比

Table 5 Comparison of carbon peaking results for power from different literatures

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