An optimal production planning model of coal-fired power industry in China: Considering the process of closing down inefficient units and developing CCS technologies

National Development and Reform Commission and National Energy Administration have launched a series of policies on closing down small coal-power units, in order to reduce energy consumption and pollutant emissions. However, it is hard to change current situation in the short term since coal is still the domain source of power generation in China. Aiming at efficiently closing down the small power units, to create a power generation planning model with minimized costs needs to take both economic and technical aspects into account. In this paper, eight types of coal-fired generators are classified into three categories: Inefficient units; Efficient units; and Low-carbon units. This paper has developed a power generation planning model under multiple constraint conditions such as coal-power demand, total installed capacity, and carbon capture etc. Also, the model involves variable costs of CCS technology and contingency payments at the same time. This paper has applied the power generation planning model into China’s coal-fired power industry research during the period from 2016 to 2030. The results show that because the coal-power demand ends up with a drop following a rise, the total costs thereby shows a same trend. During the planning period, the fuel costs and the operation and maintenance costs decrease most obviously. Given the installed capacity, compared with the increase in the number of efficient units, the number of inefficient units shows a gradual decrease. The number of low-carbon units displays a slight increase. Since low-carbon units can capture and store 90% of their carbon emissions, the total carbon emissions from coal-fired power industry have significantly been reduced in their operation year. Thus, it is imperative to develop high efficiency and low-carbon units as they will be the major contributors to the sustainable development of the coal-fired power industry.

[1]  Erdong Zhao,et al.  Can China realize its carbon emission reduction goal in 2020: From the perspective of thermal power development , 2014 .

[2]  Wenjia Cai,et al.  China׳s carbon mitigation strategies: Enough? , 2014 .

[3]  H Mirzaesmaeeli,et al.  A multi-period optimization model for energy planning with CO(2) emission consideration. , 2010, Journal of environmental management.

[4]  Ziwei Mao,et al.  Analysis of carbon tax for CO2 mitigation in China's power sector by modeling , 2010, 2010 International Conference on Advances in Energy Engineering.

[5]  Michael C. Georgiadis,et al.  A mid-term, market-based power systems planning model , 2016 .

[6]  Frank Jotzo,et al.  China Carbon Pricing Survey 2013 , 2013 .

[7]  Zhixuan Wang,et al.  Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions , 2014 .

[8]  Efstratios N. Pistikopoulos,et al.  A spatial multi-period long-term energy planning model: A case study of the Greek power system , 2014 .

[9]  Hana Gerbelová,et al.  Electricity decarbonisation pathways for 2050 in Portugal: A TIMES (The Integrated MARKAL-EFOM System) based approach in closed versus open systems modelling , 2014 .

[10]  Bao-Jun Tang,et al.  Initial carbon quota allocation methods of power sectors: a China case study , 2016, Natural Hazards.

[11]  Xing Zhang,et al.  An interval full-infinite mixed-integer programming method for planning municipal energy systems - A case study of Beijing , 2011 .

[12]  Yi-Ming Wei,et al.  Technology roadmap study on carbon capture, utilization and storage in China. , 2013 .

[13]  Yi-Ming Wei,et al.  A multi-period power generation planning model incorporating the non-carbon external costs: A case study of China , 2016 .

[14]  J. K. Banuro,et al.  Power generation capacity planning under budget constraint in developing countries , 2017 .

[15]  Nikolaos E. Koltsaklis,et al.  A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints , 2015 .

[16]  Ying Li,et al.  The implications of CO2 price for China’s power sector decarbonization , 2015 .

[17]  Peter Viebahn,et al.  Prospects of carbon capture and storage (CCS) in India’s power sector – An integrated assessment , 2014 .

[18]  Guohe Huang,et al.  Planning regional energy system in association with greenhouse gas mitigation under uncertainty , 2011 .

[19]  Paula Varandas Ferreira,et al.  Generation expansion planning with high share of renewables of variable output , 2017 .

[20]  Liu Jian,et al.  Study on the Strategy of Energy Conservation and Emissions Reduction of Chinese Foundry Industry During the 12th Five-Year Plan Period , 2013 .

[21]  Yasumasa Fujii,et al.  Long-term scenario analysis of nuclear energy and variable renewables in Japan's power generation mix considering flexible power resources , 2015 .

[22]  Lei Du,et al.  Study on carbon capture and storage (CCS) investment decision-making based on real options for China's coal-fired power plants , 2016 .

[23]  Jinhua Cheng,et al.  Carbon reduction cost estimating of Chinese coal-fired power generation units: A perspective from national energy consumption standard , 2016 .

[24]  D. Georgakellos,et al.  Incorporating life cycle external cost in optimization of the electricity generation mix , 2014 .

[25]  Fan,et al.  Chinese Cultural Industry Highlights Belt-patterned Development in the 13th Five Year Plan , 2016 .

[26]  Can Wang,et al.  An uncertainty analysis of subsidy for carbon capture and storage (CCS) retrofitting investment in China's coal power plants using a real-options approach , 2016 .

[27]  Zheng Li,et al.  A multi-region load dispatch model for the long-term optimum planning of China’s electricity sector , 2017 .

[28]  Pei Liu,et al.  A multi-region optimization planning model for China's power sector , 2015 .

[29]  M. Liszka,et al.  Comparison of IGCC (integrated gasification combined cycle) and CFB (circulating fluidized bed) cogeneration plants equipped with CO2 removal , 2013 .

[30]  Zheng Li,et al.  A multi-period modelling and optimization approach to the planning of China's power sector with consideration of carbon dioxide mitigation , 2012, Comput. Chem. Eng..