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Efficiency ranking of different types of power plants in Iran using super efficiency method

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  • Sojoodi, Sakineh
  • Dastmalchi, Laleh
  • Neshat, Hadi

Abstract

Nowadays, with the ever-increasing development of the communities, the demand for different forms of energy like electricity has drastically increased. Hence, attention to energy efficiency, especially electricity, seems necessary. Different approaches exist for calculating the efficiency and ranking decision-making units (DMUs), among which data envelopment analysis (DEA) and particularly super-efficiency (SE) method is of the most important ones. In this study, the efficiency of various types of thermal power plants (steam, gas and combined-cycle) has been measured in Iran from 2011 to 2019 using three SE models which are introduced by Anderson-Peterson [1]; Lin-Chen [2] and Li, Jahanshahloo and Khodabakhshi [3]. The efficiency ranking of different types of power plants in three different super-efficiency methods is almost similar. Comparison of the efficiency of combined cycle, steam and gas power plants shows that combined cycle power plants are more efficient than other power plants and gas power plants have the lowest efficiency. An examination of the efficiency score of power plants over time shows that the efficiency of combined cycle power plants has improved over time, while in other power plants this has not happened and some have experienced a reduction in efficiency.

Suggested Citation

  • Sojoodi, Sakineh & Dastmalchi, Laleh & Neshat, Hadi, 2021. "Efficiency ranking of different types of power plants in Iran using super efficiency method," Energy, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:energy:v:233:y:2021:i:c:s0360544221013529
    DOI: 10.1016/j.energy.2021.121104
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    References listed on IDEAS

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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Zhu, Joe, 1996. "Robustness of the efficient DMUs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 90(3), pages 451-460, May.
    3. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    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. Lee, Hsuan-Shih & Zhu, Joe, 2012. "Super-efficiency infeasibility and zero data in DEA," European Journal of Operational Research, Elsevier, vol. 216(2), pages 429-433.
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    Cited by:

    1. Lin, Boqiang & Xie, Yongjing, 2022. "Analysis on operational efficiency and its influencing factors of China’s nuclear power plants," Energy, Elsevier, vol. 261(PA).
    2. Yunyao Li & Yanji Ma, 2022. "Research on Industrial Innovation Efficiency and the Influencing Factors of the Old Industrial Base Based on the Lock-In Effect, a Case Study of Jilin Province, China," Sustainability, MDPI, vol. 14(19), pages 1-23, October.
    3. Wang, Ying & Deng, Xiangzheng & Zhang, Hongwei & Liu, Yujie & Yue, Tianxiang & Liu, Gang, 2022. "Energy endowment, environmental regulation, and energy efficiency: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 177(C).

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