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Operational performance management of the power industry: a distinguishing analysis between effectiveness and efficiency

Author

Listed:
  • Ke Wang

    (Beijing Institute of Technology
    Beijing Institute of Technology
    Collaborative Innovation Center of Electric Vehicles in Beijing)

  • Chia-Yen Lee

    (National Cheng Kung University
    National Cheng Kung University)

  • Jieming Zhang

    (Beijing Institute of Technology
    Beijing Institute of Technology)

  • Yi-Ming Wei

    (Beijing Institute of Technology
    Beijing Institute of Technology
    Collaborative Innovation Center of Electric Vehicles in Beijing)

Abstract

The trend toward a more competitive electricity market has led to efforts by the electric power industry to develop advanced efficiency evaluation models that adapt to market behavior operations management. The promotion of the operational performance management of the electric power industry plays an important role in China’s efforts toward energy conservation, emission control and sustainable development. Traditional efficiency measures are not able to distinguish sales effects from productive efficiency and thus are not sufficient for measuring the operational performance of an electricity generation system for achieving its specific market behavior operations management goals, such as promoting electricity sales. Effectiveness measures are associated with the capacity of an electricity generation system to adjust its input resources that influence its electricity generation and, thus, the capacity to match the electricity demand. Therefore, the effectiveness measures complement the efficiency measures by capturing the sales effect in the operational performance evaluation. This study applies a newly developed data envelopment analysis-based effectiveness measurement to evaluate the operational performance of the electric power industry in China’s 30 provincial regions during the 2006–2010 periods. Both the efficiency and effectiveness of the electricity generation system in each region are measured, and the associated electricity sales effects and electricity reallocation effects are captured. Based on the results of the effectiveness measures, the alternative operational performance improvement strategies and potentials in terms of input resources savings and electricity generation adjustments are proposed. The empirical results indicate that the current interregional electricity transmission and reallocation efforts are effective in China overall, and a moderate increase in electricity generation with a view to improving the effect on sales is more crucial for improving effectiveness.

Suggested Citation

  • Ke Wang & Chia-Yen Lee & Jieming Zhang & Yi-Ming Wei, 2018. "Operational performance management of the power industry: a distinguishing analysis between effectiveness and efficiency," Annals of Operations Research, Springer, vol. 268(1), pages 513-537, September.
    • Handle: RePEc:spr:annopr:v:268:y:2018:i:1:d:10.1007_s10479-016-2189-1
    DOI: 10.1007/s10479-016-2189-1
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    Cited by:

    1. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    2. Yuan, Peng & Pu, Yuran & Liu, Chang, 2021. "Improving electricity supply reliability in China: Cost and incentive regulation," Energy, Elsevier, vol. 237(C).
    3. Chun Sun & Sheng Ang & Fangqing Wei & Dawei Wang & Feng Yang, 2024. "Supply–demand effectiveness: capturing the effects of supply and demand mismatches in operational performance measurement," Operational Research, Springer, vol. 24(2), pages 1-22, June.
    4. 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.
    5. Yujiao Xian & Ke Wang & Xunpeng Shi & Chi Zhang & Yi-Ming Wei & Zhimin Huang, 2018. "Carbon emissions intensity reduction target for China¡¯s power industry: An efficiency and productivity perspective," CEEP-BIT Working Papers 117, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    6. 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.
    7. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    8. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    9. Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
    10. Ke Wang & Jieming Zhang & Yi-Ming Wei, 2017. "Operational and environmental performance in China¡¯s thermal power industry: Taking an effectiveness measure as complement to an efficiency measure," CEEP-BIT Working Papers 100, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    11. Jules Raymond Kala & Didier Michael Kre & Armelle N’Guessan Gnassou & Jean Robert Kamdjoug Kala & Yves Melaine Akpablin Akpablin & Tiorna Coulibaly, 2022. "Assets management on electrical grid using Faster-RCNN," Annals of Operations Research, Springer, vol. 308(1), pages 307-320, January.
    12. Lee, Chia-Yen, 2018. "Mixed-strategy Nash equilibrium in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1013-1024.

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    More about this item

    Keywords

    China; Data envelopment analysis (DEA); Electricity generation system; Electricity reallocation; Electricity sales effect;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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