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The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective


  • She, Zhen-Yu
  • Meng, Gang
  • Xie, Bai-Chen
  • O'Neill, Eoghan


To promote the development of the electricity trading market, China launched a new round of power system reform in 2015. Considering environmental and service factors, this study adopts a dynamic data envelopment analysis model with a network structure based on a slacks-based measure approach to evaluate the performance of the power system and its divisions in the 30 provincial-level administrative regions from 2011 to 2016. To better reflect the practical situation of the power system, we develop an improved network model which includes both free link and fixed link variables at the same time. This study further employs scenario analysis to investigate the effect of the unbundling reform on the power system and its divisions. It reaches the following conclusions: First, inter-regional transmission and environmental factors should be taken into account in evaluating the productive efficiency of the power system. Second, the separation of distribution from transmission has a positive impact on productive efficiency, and the effects of the unbundling reform on the power system differ significantly among divisions. Third, the introduction of an incomplete electricity trading market has a negative impact on the dynamic productive efficiency of the power system compared with the scenario without market reform, while complete market-oriented reform can improve dynamic productive efficiency and narrow the gap between regions. Nevertheless, a complete market reform has less influence on the efficiency than the changing power supply and demand situation caused by economic development.

Suggested Citation

  • She, Zhen-Yu & Meng, Gang & Xie, Bai-Chen & O'Neill, Eoghan, 2020. "The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective," Applied Energy, Elsevier, vol. 264(C).
  • Handle: RePEc:eee:appene:v:264:y:2020:i:c:s0306261920302294
    DOI: 10.1016/j.apenergy.2020.114717

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    References listed on IDEAS

    1. Christian Growitsch & Tooraj Jamasb & Michael Pollitt, 2009. "Quality of service, efficiency and scale in network industries: an analysis of European electricity distribution," Applied Economics, Taylor & Francis Journals, vol. 41(20), pages 2555-2570.
    2. Liu, Yaqin & Zhao, Guohao & Zhao, Yushan, 2016. "An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure," Energy Policy, Elsevier, vol. 96(C), pages 524-533.
    3. David M. Newbery, 2005. "Electricity liberalization in Britain: The quest for a satisfactory wholesale market design," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 43-70.
    4. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    5. Jorge E. Galán & Michael G. Pollitt, 2014. "Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities," Cambridge Working Papers in Economics 1423, Faculty of Economics, University of Cambridge.
    6. Mika Goto and Toshiyuki Sueyoshi, 2016. "Electricity market reform in Japan after Fukushima," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    7. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    8. Xie, Bai-Chen & Shang, Li-Feng & Yang, Si-Bo & Yi, Bo-Wen, 2014. "Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countrie," Energy, Elsevier, vol. 74(C), pages 147-157.
    9. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    10. Kaoru Tone & Miki Tsutsui, 2014. "Slacks-Based Network DEA," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 231-259, Springer.
    11. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.
    12. Zeng, Ming & Yang, Yongqi & Wang, Lihua & Sun, Jinghui, 2016. "The power industry reform in China 2015: Policies, evaluations and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 94-110.
    13. Paul L. Joskow, 2008. "Lessons Learned from Electricity Market Liberalization," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 9-42.
    14. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    15. Chen, Chien-Ming, 2009. "A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks," European Journal of Operational Research, Elsevier, vol. 194(3), pages 687-699, May.
    16. Tooraj Jamasb & Rabindra Nepal & Govinda R. Timilsina, 2017. "A Quarter Century Effort Yet to Come of Age: A Survey of Electricity Sector Reform in Developing Countries," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    17. 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.
    18. Hirofumi Fukuyama & William Weber, 2015. "Measuring Japanese bank performance: a dynamic network DEA approach," Journal of Productivity Analysis, Springer, vol. 44(3), pages 249-264, December.
    19. C S Sarrico, 2001. "Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(12), pages 1408-1409, December.
    20. Giannakis, Dimitrios & Jamasb, Tooraj & Pollitt, Michael, 2005. "Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks," Energy Policy, Elsevier, vol. 33(17), pages 2256-2271, November.
    21. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    22. Tao, Xueping & Wang, Ping & Zhu, Bangzhu, 2016. "Provincial green economic efficiency of China: A non-separable input–output SBM approach," Applied Energy, Elsevier, vol. 171(C), pages 58-66.
    23. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    24. Mahmoudabadi, Mohammad Zarei & Azar, Adel & Emrouznejad, Ali, 2018. "A novel multilevel network slacks-based measure with an application in electric utility companies," Energy, Elsevier, vol. 158(C), pages 1120-1129.
    25. Nepal, Rabindra & Jamasb, Tooraj & Sen, Anupama, 2018. "Small systems, big targets: Power sector reforms and renewable energy in small systems," Energy Policy, Elsevier, vol. 116(C), pages 19-29.
    26. 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.
    27. Ahmed, Tauqir & Bhatti, Arshad Ali, 2019. "Do power sector reforms affect electricity prices in selected Asian countries?," Energy Policy, Elsevier, vol. 129(C), pages 1253-1260.
    28. Fare, Rolf & Grosskopf, Shawna, 2000. "Network DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 35-49, March.
    Full references (including those not matched with items on IDEAS)


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