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清华大学学报(自然科学版)  2022, Vol. 62 Issue (4): 810-818    DOI: 10.16511/j.cnki.qhdxxb.2022.25.013
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城市能源系统碳达峰路径最优化
李忱息, 刘培, 李政
清华大学 能源与动力工程系, 北京 100084
Optimization of urban energy system development plans for controlling peak emissions
LI Chenxi, LIU Pei, LI Zheng
Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China
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摘要 为了响应2030年碳达峰和2060年碳中和的目标,我国各行业及区域均需要根据自身资源禀赋和未来发展预期对能源系统发展进行低碳规划。科学的规划可以在一定程度上降低碳减排的成本。该文建立了基于超结构建模方法的能源系统发展规划模型,可用于以碳达峰为目标的发展路径规划。该模型以区域能源系统结构及主要基础设施为规划起始点,综合考虑规划期内不同时间段上多种能源供应、转化、传输、储存、消费技术可能性及相互替代性,从而得到能源系统总成本最优的低碳发展技术路径。该文以某规模以上城市为例,对其2021—2035年间的能源系统发展路径进行了规划设计,将该市的碳排放峰值控制为1.79亿t,15年内累计减少二氧化碳排放共计1.5亿t。
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李忱息
刘培
李政
关键词 碳达峰能源系统优化建模    
Abstract:China seeks to reach peak emissions in 2030 and to be carbon neutral in 2060. All industries and regions in China need to develop low-carbon energy system development plans according to their own resources and development expectations to reduce the costs of carbon emission reductions. This paper presents an energy system development planning model based on the superstructure modeling method for planning how to control the emission peak goal. This model starts with the regional energy system structure and infrastructure. The model then considers various energy supply, transformation, transmission, and storage methods and possible changes in consumption technologies during different periods to obtain the best low-carbon development path with the optimal total energy system cost. This study then determines the best energy system development path from 2021 to 2035 for a typical city which controlled the peak carbon emissions to 179 million tons and reduced carbon emissions by 150 million tons within 15 years.
Key wordsemission peak    energy systems    optimization
收稿日期: 2021-09-24      出版日期: 2022-04-14
基金资助:刘培,副教授,E-mail:liu_pei@tsinghua.edu.cn
引用本文:   
李忱息, 刘培, 李政. 城市能源系统碳达峰路径最优化[J]. 清华大学学报(自然科学版), 2022, 62(4): 810-818.
LI Chenxi, LIU Pei, LI Zheng. Optimization of urban energy system development plans for controlling peak emissions. Journal of Tsinghua University(Science and Technology), 2022, 62(4): 810-818.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2022.25.013  或          http://jst.tsinghuajournals.com/CN/Y2022/V62/I4/810
  
  
  
  
  
  
  
  
  
  
  
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