IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i1p504-d717144.html
   My bibliography  Save this article

Total Factor Energy Efficiency of China’s Thermal Power Industry

Author

Listed:
  • Ying Feng

    (School of Economics & Management, Northwest University, Xi’an 710069, China
    Business College, Northwest University of Political Science and Law, No.1 Xuefu Avenue, Guodu Education and Technology Industrial Zone, Chang An District, Xi’an 710122, China)

  • Ching-Cheng Lu

    (Department of Economics, Soochow University, No.56, Sec. 1, Kueiyang St., Taipei City 10048, Taiwan)

  • I-Fang Lin

    (Department of Economics, Soochow University, No.56, Sec. 1, Kueiyang St., Taipei City 10048, Taiwan)

  • An-Chi Yang

    (Department of Economics, Soochow University, No.56, Sec. 1, Kueiyang St., Taipei City 10048, Taiwan)

  • Po-Chun Lin

    (Chung-Hua Institution for Economic Research, No.75, Changhsing St., Taipei 10672, Taiwan)

Abstract

Coal-based thermal power generation has long been the main source of power generation in the mainland of China. The efficiency of power generation is an important factor that determines the energy conservation and emission reduction as well as the sustainable development of the power industry in China. By comparing the regional differences of 30 provinces in the mainland from 2013 to 2017, this study uses the Super-DDF model and the TFEE to comprehensively evaluate the energy efficiency of thermal power generation. Empirical results: Overall efficiency: eastern efficiency (1.181) is the highest, followed by western (0.956), central (0.951) and northeastern (0.926). Total factor energy efficiency: eastern efficiency (0.923) is the highest, followed by western (0.754), central (0.742) and northeastern (0.710). The government and power industry managers should fully consider the regional differences in the field of thermal power generation when formulating policies so as to improve the power efficiency and promote the green development of power industry in China. Based on the analysis results, although the coal-fired power industry is more mature than other alternative energy industries, the expansion of thermal power generation cannot be considered if CO 2 emissions are to be reduced. Additionally, the market share and competitiveness of the local power industry can be increased based on the different conditions of the resource endowments of each region.

Suggested Citation

  • Ying Feng & Ching-Cheng Lu & I-Fang Lin & An-Chi Yang & Po-Chun Lin, 2022. "Total Factor Energy Efficiency of China’s Thermal Power Industry," Sustainability, MDPI, vol. 14(1), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:1:p:504-:d:717144
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/1/504/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/1/504/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ke Wang & Zhifu Mi & Yi‐Ming Wei, 2019. "Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA‐Based Materials Balance Approach," Journal of Industrial Ecology, Yale University, vol. 23(2), pages 389-401, April.
    2. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    3. 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.
    4. 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).
    5. Chen, Bin & Jin, Yingmei, 2020. "Adjusting productivity measures for CO2 emissions control: Evidence from the provincial thermal power sector in China," Energy Economics, Elsevier, vol. 87(C).
    6. Sözen, Adnan & Alp, Ihsan & Özdemir, Adnan, 2010. "Assessment of operational and environmental performance of the thermal power plants in Turkey by using data envelopment analysis," Energy Policy, Elsevier, vol. 38(10), pages 6194-6203, October.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ya Wu & Yin Liu & Minglong Zhang, 2023. "How Does Digital Finance Affect Energy Efficiency?—Characteristics, Mechanisms, and Spatial Effects," Sustainability, MDPI, vol. 15(9), pages 1-24, April.

    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. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    2. 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).
    3. Chu, Junfei & Shao, Caifeng & Emrouznejad, Ali & Wu, Jie & Yuan, Zhe, 2021. "Performance evaluation of organizations considering economic incentives for emission reduction: A carbon emission permit trading approach," Energy Economics, Elsevier, vol. 101(C).
    4. Chin‐wei Huang & Hsiao‐Yin Chen, 2023. "Using nonradial metafrontier data envelopment analysis to evaluate the metatechnology and metafactor ratios for the Taiwanese hotel industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 1904-1919, June.
    5. 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).
    6. 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).
    7. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Impact of emission regulation policies on Chinese power firms’ reusable environmental investments and sustainable operations," Energy Policy, Elsevier, vol. 108(C), pages 163-177.
    8. Jindal, Abhinav & Nilakantan, Rahul, 2021. "Falling efficiency levels of Indian coal-fired power plants: A slacks-based analysis," Energy Economics, Elsevier, vol. 93(C).
    9. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    10. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    11. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    12. Liang Chun Lu & Yung-ho Chiu & Shih-Yung Chiu & Tzu-Han Chang, 2022. "Do Forests help environmental development of Cities in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6602-6629, May.
    13. Haoran Zhao & Huiru Zhao & Sen Guo, 2018. "Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    14. Lynes, Melissa & Brewer, Brady & Featherstone, Allen, 2016. "Greenhouse Gas Emissions Effect on Cost Efficiencies of U.S. Electric Power Plants," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235890, Agricultural and Applied Economics Association.
    15. 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).
    16. Weibin Lin & Bin Chen & Lina Xie & Haoran Pan, 2015. "Estimating Energy Consumption of Transport Modes in China Using DEA," Sustainability, MDPI, vol. 7(4), pages 1-15, April.
    17. Sedef E. Kara & Mustapha D. Ibrahim & Sahand Daneshvar, 2021. "Dual Efficiency and Productivity Analysis of Renewable Energy Alternatives of OECD Countries," Sustainability, MDPI, vol. 13(13), pages 1-14, July.
    18. Yu, Yu & Wang, Derek D. & Li, Shanling & Shi, Qinfen, 2016. "Assessment of U.S. firm-level climate change performance and strategy," Energy Policy, Elsevier, vol. 92(C), pages 432-443.
    19. Irmak Acarlar & Harun Kınacı & Vadoud Najjari, 2014. "A New Measure for Detecting Influential DMUs in DEA," Journal of Optimization, Hindawi, vol. 2014, pages 1-7, October.
    20. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.

    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:gam:jsusta:v:14:y:2022:i:1:p:504-:d:717144. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.