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Improve technical efficiency of China's coal-fired power enterprises: Taking a coal-fired-withdrawl context

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  • Li, Gao
  • Ruonan, Li
  • Yingdan, Mei
  • Xiaoli, Zhao

Abstract

In the process of energy transition, reference standards are needed to guide the orderly withdrawal of coal-fired power enterprises. This study applies stochastic frontier analysis to measure the technical efficiency, as the reference standard, based on data from all coal-fired power enterprises of a large Chinese power generation group from 2010 to 2015. Meanwhile, in order to make more specific policy recommendations, this paper provides a detailed analysis of the technical efficiency in three aspects: return to scale, operation hours, and regional characteristics. The empirical results show that the average technical efficiency of coal-fired power enterprises is 0.818, which still leaves room for improvement of about 20%; the industry shows slightly decreasing return to scale, which primarily results from enterprises with larger capacity but less operation hours; correlation between efficiency and operation hours varies widely among regions, with South and Northwest China in the greatest need of improving the generation assignment approach; finally, unit coal reduction and equity increase are important ways to improve technical efficiency, and older power enterprises and larger units have greater potential for high-quality power supply. The findings will serve as a reference for policy makers to promote a more effective planning of coal-fired power industry in China.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:252:y:2022:i:c:s0360544222008829
    DOI: 10.1016/j.energy.2022.123979
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    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    8. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    9. 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.
    10. Lin, Jiang & Kahrl, Fredrich & Liu, Xu, 2018. "A regional analysis of excess capacity in China’s power systems," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt44j2w0d0, Department of Agricultural & Resource Economics, UC Berkeley.
    11. 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.
    12. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    13. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    14. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    15. David H. Bernstein & Christopher F. Parmeter, 2017. "Returns to Scale in Electricity Generation: Revisited and Replicated," Working Papers 2017-08, University of Miami, Department of Economics.
    16. 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.
    17. Wang, Yongpei & Yan, Weilong & Komonpipat, Supak, 2019. "How does the capacity utilization of thermal power generation affect pollutant emissions? Evidence from the panel data of China's provinces," Energy Policy, Elsevier, vol. 132(C), pages 440-451.
    18. Zhang, Ruchuan & Wei, Qian & Li, Aijun & Ren, LiYing, 2022. "Measuring efficiency and technology inequality of China's electricity generation and transmission system: A new approach of network Data Envelopment Analysis prospect cross-efficiency models," Energy, Elsevier, vol. 246(C).
    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. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    21. Sun, Kege & Wu, Libo, 2020. "Efficiency distortion of the power generation sector under the dual regulation of price and quantity in China," Energy Economics, Elsevier, vol. 86(C).
    22. Du, Limin & He, Yanan & Yan, Jianye, 2013. "The effects of electricity reforms on productivity and efficiency of China's fossil-fired power plants: An empirical analysis," Energy Economics, Elsevier, vol. 40(C), pages 804-812.
    23. 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).
    24. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    25. Ma, Chunbo & Zhao, Xiaoli, 2015. "China's electricity market restructuring and technology mandates: Plant-level evidence for changing operational efficiency," Energy Economics, Elsevier, vol. 47(C), pages 227-237.
    26. 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.
    27. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    28. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    29. 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).
    30. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    31. 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.
    32. Heleen Groenenberg & Kornelis Blok, 2002. "Benchmark-based emission allocation in a cap-and-trade system," Climate Policy, Taylor & Francis Journals, vol. 2(1), pages 105-109, March.
    33. 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.
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    More about this item

    Keywords

    Coal-fired power enterprises; Technical efficiency; Stochastic frontier analysis; China;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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