Unit-level cost-benefit analysis for coal power plants retrofitted with biomass co-firing at a national level by combined GIS and life cycle assessment
Unit-level cost-benefit analysis for coal power plants retrofitted with biomass co-firing at a national level by combined GIS and life cycle assessment
复制标题
结合GIS和生命周期评估对国家级生物质混烧燃煤电厂进行机组级成本效益分析
DOI:
10.1016/j.apenergy.2021.116494
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发表时间:
2021-03
期刊:
影响因子:
11.2
通讯作者:
Wang Can
中科院分区:
文献类型:
--
作者:
Li Jin;Wang Rui;Li Haoran;Nie Yaoyu;Song Xinke;Li Mingyu;Shi Mai;Zheng Xinzhu;Cai Wenjia;Wang Can
To avoid the irreversible impact of global climate change on human society, many countries have recently put forward ambitious goals to accelerate the low-carbon transition of energy systems. Among low-carbon measures, retrofitting existing coal power plants with biomass co-firing is regarded as a promising cost-efficient option to mitigate greenhouse gas and air pollutant emissions. However, the life-cycle economic cost or environmental benefit of this coal-to-biomass retrofit is not identical for various types of power plants in different regions. To facilitate a more efficient biomass utilization strategy in an energy system, it is necessary to carry out a large-scale and high-resolution cost-benefit assessment for the co-firing of biomass and coal in retrofitted plants. Taking China as an example, this study utilized a bottom-up approach and geographic information system, combined with the latest available datasets, to develop a unit-level cost-benefit analysis framework for the coal-to-biomass transition. The results indicate that the coal-to-biomass retrofit costs US$18.3–73.0 for each ton of carbon reduction, and US$21.6–806.5 for each kg of SO2reduction, at a 25% blending ratio. Installed capacity, operating year, and transportation distance are important influencing factors of cost-benefit heterogeneity. The priority of power unit retrofitting in terms of carbon reductions mainly depends on the cost preference, while that for SO2reduction is mainly determined by benefit preference. The analytical framework proposed in this study can be used in other countries to formulate an efficient biomass development strategy.
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DOI:
10.1002/bbb.2034
发表时间:
2019-07
期刊:
Biofuels
影响因子:
--
作者:
L. Cutz;G. Berndes;F. Johnsson
通讯作者:
L. Cutz;G. Berndes;F. Johnsson
影响因子:
11.1
作者:
I. Andrić;N. Jamali-Zghal;M. Santarelli;B. Lacarrière;O. L. Corre
通讯作者:
I. Andrić;N. Jamali-Zghal;M. Santarelli;B. Lacarrière;O. L. Corre
影响因子:
9
作者:
Changbo Wang;Lixiao Zhang;Yuan Chang;Mingyue Pang
通讯作者:
Changbo Wang;Lixiao Zhang;Yuan Chang;Mingyue Pang
影响因子:
11.2
作者:
J. Miedema;R. Benders;H. Moll;Frank Pierie
通讯作者:
J. Miedema;R. Benders;H. Moll;Frank Pierie
影响因子:
8.7
作者:
Basu, Prabir;Butler, James;Leon, Mathias A.
通讯作者:
Leon, Mathias A.