IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v138y2021ics1364032120308467.html
   My bibliography  Save this article

Sources of inefficient power generation by coal-fired thermal power plants in China: A metafrontier DEA decomposition approach

Author

Listed:
  • Eguchi, Shogo
  • Takayabu, Hirotaka
  • Lin, Chen

Abstract

China is the world's largest CO2 emitting country, and coal-fired thermal power generation accounted for over 50% of the total electricity generation in China in 2015. This study reports the changes in the power generation efficiency of coal-fired thermal power plants in China from 2009 to 2011 and elucidates how the differences in the production scale of the power plants and regional heterogeneity affect the power generation efficiency. We propose a metafrontier data envelopment analysis (DEA) decomposition framework to investigate the sources of inefficiency in power generation. The results suggest that, on average, the power generation efficiency of large-scale power plants is 13% higher than that of small-scale power plants. Although operational inefficiency is the main source of inefficiency in eastern and central China, the technology gap - the differences in the quality of coal consumed for electricity production and in the equipment of the power plants among regions - is the main source of inefficiency in western China. This study uses the results of the framework to discuss the scrapping policies for coal-fired thermal power plants in China. For large-scale power plants in western China, the components of inefficiency vary and, thus, policymakers should consider scrapping thermal power plants based not only on the level of inefficiency but also on their components.

Suggested Citation

  • Eguchi, Shogo & Takayabu, Hirotaka & Lin, Chen, 2021. "Sources of inefficient power generation by coal-fired thermal power plants in China: A metafrontier DEA decomposition approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:rensus:v:138:y:2021:i:c:s1364032120308467
    DOI: 10.1016/j.rser.2020.110562
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032120308467
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2020.110562?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    2. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    3. Zhao, Xiaoli & Ma, Chunbo, 2013. "Deregulation, vertical unbundling and the performance of China's large coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 474-483.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Zhang, Yue-Jun & Hao, Jun-Fang & Song, Juan, 2016. "The CO2 emission efficiency, reduction potential and spatial clustering in China’s industry: Evidence from the regional level," Applied Energy, Elsevier, vol. 174(C), pages 213-223.
    6. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    7. Xie, Lunyu & Huang, Ying & Qin, Ping, 2018. "Spatial distribution of coal-fired power plants in China," Environment and Development Economics, Cambridge University Press, vol. 23(4), pages 495-515, August.
    8. Yang, Hongliang & Pollitt, Michael, 2010. "The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants," Energy Policy, Elsevier, vol. 38(8), pages 4440-4444, August.
    9. Zhou, Yan & Xing, Xinpeng & Fang, Kuangnan & Liang, Dapeng & Xu, Chunlin, 2013. "Environmental efficiency analysis of power industry in China based on an entropy SBM model," Energy Policy, Elsevier, vol. 57(C), pages 68-75.
    10. Kaneko, Shinji & Fujii, Hidemichi & Sawazu, Naoya & Fujikura, Ryo, 2010. "Financial allocation strategy for the regional pollution abatement cost of reducing sulfur dioxide emissions in the thermal power sector in China," Energy Policy, Elsevier, vol. 38(5), pages 2131-2141, May.
    11. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    12. Lam, Pun-Lee & Shiu, Alice, 2001. "A data envelopment analysis of the efficiency of China's thermal power generation," Utilities Policy, Elsevier, vol. 10(2), pages 75-83, June.
    13. Wang, Chunhua & Cao, Xiaoyong & Mao, Jie & Qin, Ping, 2019. "The changes in coal intensity of electricity generation in Chinese coal-fired power plants," Energy Economics, Elsevier, vol. 80(C), pages 491-501.
    14. Pun-Lee Lam & Alice Shiu, 2004. "Efficiency and Productivity of China's Thermal Power Generation," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 24(1), pages 73-93, February.
    15. Sun, Chuanwang & Liu, Xiaohong & Li, Aijun, 2018. "Measuring unified efficiency of Chinese fossil fuel power plants: Intermediate approach combined with group heterogeneity and window analysis," Energy Policy, Elsevier, vol. 123(C), pages 8-18.
    16. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    17. Long, Xingle & Sun, Mei & Cheng, Faxin & Zhang, Jijian, 2017. "Convergence analysis of eco-efficiency of China’s cement manufacturers through unit root test of panel data," Energy, Elsevier, vol. 134(C), pages 709-717.
    18. Long, Xingle & Zhao, Xicang & Cheng, Faxin, 2015. "The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures," Energy Policy, Elsevier, vol. 81(C), pages 61-66.
    19. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    20. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    21. K.R. Shanmugam & Praveen Kulshreshtha, 2005. "Efficiency analysis of coal-based thermal power generation in India during post-reform era," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 23(1), pages 15-28.
    22. Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    23. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    24. F. Wu & P. Zhou & D. Zhou, 2015. "Measuring Energy Congestion in Chinese Industrial Sectors: A Slacks-Based DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 479-494, October.
    25. Du, Limin & Mao, Jie, 2015. "Estimating the environmental efficiency and marginal CO2 abatement cost of coal-fired power plants in China," Energy Policy, Elsevier, vol. 85(C), pages 347-356.
    26. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    27. Mou, Dunguo, 2014. "Understanding China’s electricity market reform from the perspective of the coal-fired power disparity," Energy Policy, Elsevier, vol. 74(C), pages 224-234.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    30. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    31. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, November.
    32. Yu, Yanni & Qian, Tao & Du, Limin, 2017. "Carbon productivity growth, technological innovation, and technology gap change of coal-fired power plants in China," Energy Policy, Elsevier, vol. 109(C), pages 479-487.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nakaishi, Tomoaki & Takayabu, Hirotaka & Eguchi, Shogo, 2021. "Environmental efficiency analysis of China's coal-fired power plants considering heterogeneity in power generation company groups," Energy Economics, Elsevier, vol. 102(C).
    2. Shogo Eguchi, 2022. "CO 2 Reduction Potential from Efficiency Improvements in China’s Coal-Fired Thermal Power Generation: A Combined Approach of Metafrontier DEA and LMDI," Energies, MDPI, vol. 15(7), pages 1-19, March.
    3. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    4. Li, Gao & Ruonan, Li & Yingdan, Mei & Xiaoli, Zhao, 2022. "Improve technical efficiency of China's coal-fired power enterprises: Taking a coal-fired-withdrawl context," Energy, Elsevier, vol. 252(C).
    5. Nakaishi, Tomoaki, 2021. "Developing effective CO2 and SO2 mitigation strategy based on marginal abatement costs of coal-fired power plants in China," Applied Energy, Elsevier, vol. 294(C).
    6. Du, Limin & Lu, Yunguo & Ma, Chunbo, 2022. "Carbon efficiency and abatement cost of China's coal-fired power plants," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    8. Ya Chen & Wei Xu & Qian Zhou & Zhixiang Zhou, 2020. "Total Factor Energy Efficiency, Carbon Emission Efficiency, and Technology Gap: Evidence from Sub-Industries of Anhui Province in China," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    9. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    10. Seifert, Stefan & Cullmann, Astrid & von Hirschhausen, Christian, 2016. "Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector," Energy Economics, Elsevier, vol. 56(C), pages 9-19.
    11. Nakaishi, Tomoaki & Nagashima, Fumiya & Kagawa, Shigemi & Nansai, Keisuke & Chatani, Satoru, 2023. "Quantifying the health benefits of improving environmental efficiency: A case study from coal power plants in China," Energy Economics, Elsevier, vol. 121(C).
    12. Li, Ming-Jia & Tao, Wen-Quan, 2017. "Review of methodologies and polices for evaluation of energy efficiency in high energy-consuming industry," Applied Energy, Elsevier, vol. 187(C), pages 203-215.
    13. Xiangyu Teng & Danting Lu & Yung-ho Chiu, 2019. "Emission Reduction and Energy Performance Improvement with Different Regional Treatment Intensity in China," Energies, MDPI, vol. 12(2), pages 1-18, January.
    14. Li, Ying & Chiu, Yung-ho & Lin, Tai-Yu, 2019. "Coal production efficiency and land destruction in China's coal mining industry," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    15. Stefan Seifert & Astrid Cullmann & Christian von Hirschhausen, 2014. "Technical Efficiency and CO2 Reduction Potentials: An Analysis of the German Electricity Generating Sector," Discussion Papers of DIW Berlin 1426, DIW Berlin, German Institute for Economic Research.
    16. Takayabu, Hirotaka, 2020. "CO2 mitigation potentials in manufacturing sectors of 26 countries," Energy Economics, Elsevier, vol. 86(C).
    17. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Energy and Environmental Efficiency in Different Chinese Regions," Sustainability, MDPI, vol. 11(4), pages 1-26, February.
    18. Fan, Jing-Li & Zhang, Hao & Zhang, Xian, 2020. "Unified efficiency measurement of coal-fired power plants in China considering group heterogeneity and technological gaps," Energy Economics, Elsevier, vol. 88(C).
    19. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    20. Yu, Junqing & Zhou, Kaile & Yang, Shanlin, 2019. "Regional heterogeneity of China's energy efficiency in “new normal”: A meta-frontier Super-SBM analysis," Energy Policy, Elsevier, vol. 134(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:138:y:2021:i:c:s1364032120308467. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.