Journal of Thermal Science

, Volume 28, Issue 2, pp 184–194 | Cite as

Multi-Objective Optimization for China’s Power Carbon Emission Reduction by 2035

  • Jianjun Wu
  • Guihua TangEmail author
  • Run WangEmail author
  • Sun Yanwei


Low carbon transformation plays an important role in promoting the energy production and consumption revolution. Currently, the power sector of China still faces a series of challenges, such as the overcapacity of coal-fired power, the renewable energy consumption, the new constraints of carbon-emissions, and fragmented power planning. This study develops a multi-objective optimization model to predict the future trend of China power structure by 2035. The key factors such as network, power, load and storage are taken into account. Besides, the technical feasibility, economic rationality and social acceptable constraints are also fully considered. Through planning and optimization, the premise of low carbon transformation is to ensure the continuity of existing policies for removing inefficient assets, and the core is to develop and utilize non-fossil energy on a large scale. Specifically, the capacity of coal-fired power will be attained in the peak in 2025, and the factor will also transfer from main power supplier to main power and energy supplier. Before 2025, the clean replacement of incremental power installation will be completed. In 2035, 92% of new investment comes from non-fossil energy. The economy and competitiveness of wind power and PV (Photovoltaic) power generation are continuously increasing. By 2020, the coal-fired power and the wind power in eastern of China will be parity firstly. In 2025, the cost of PV and wind power will be the same. Furthermore, the evaluation dimension of modern power system with clean, low-carbon, safety and high efficiency are innovatively constructed, and the index system target of 2035 is quantitatively analyzed and prospected.


power sector carbon emission reduction optimization energy outlook comprehensive evaluation 


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This work was supported by the National Key Research and Development Program of China under grant number 2017YFB0601803.


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Copyright information

© Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Lab of Urban Environment and Health, Institute of Urban EnvironmentChinese Academy of SciencesXiamenChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.MOE Key Laboratory of Thermo-Fluid Science and EngineeringXi’an Jiaotong UniversityXi’anChina
  4. 4.Hubei UniversityWuhanChina
  5. 5.Geography & Spatial Information Techniques Department of Ningbo UniversityNingboChina

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