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<p>Due to the harmful pollution caused by the consumption of fossil fuels with high pollution, there is a great desire to use fossil fuels with low pollution and renewable energies. In this sense, it is recommended to replace polluted fuels with less polluting fuels in industrial sectors. In this contribution, the production process in the electricity industry is considered as a two-stage process with production and distribution sections in the presence of undesirable outputs and expandable inputs from both stages. A novel data envelopment analysis (DEA) model along with a bootstrap DEA procedure have been developed to estimate the technical efficiency, bias and bias-corrected efficiency scores of production entities along with the optimal values of reducible and expandable inputs and outputs. The network DEA model presented in this paper enables the calculation of individual network component performance within a unified framework, as well as the performance of the entire network. To perform sensitivity analysis of the efficiency with respect to the inputs and outputs, a robustness analysis is proposed. To demonstrate the applicability of the proposed model, we apply it to real-life data on 21 fossil-fueled power plants.</p>

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A data-driven procedure for performance analysis in fossil-fuelled power plants with environmental factors: a data envelopment analysis approach

  • 期刊论文

  • 发表日期：

    2026年3月27日

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  • Alireza Amirteimoori,
  • Amir Hossein Yadollahi,
  • Reza Kazemi Matin

摘要

Due to the harmful pollution caused by the consumption of fossil fuels with high pollution, there is a great desire to use fossil fuels with low pollution and renewable energies. In this sense, it is recommended to replace polluted fuels with less polluting fuels in industrial sectors. In this contribution, the production process in the electricity industry is considered as a two-stage process with production and distribution sections in the presence of undesirable outputs and expandable inputs from both stages. A novel data envelopment analysis (DEA) model along with a bootstrap DEA procedure have been developed to estimate the technical efficiency, bias and bias-corrected efficiency scores of production entities along with the optimal values of reducible and expandable inputs and outputs. The network DEA model presented in this paper enables the calculation of individual network component performance within a unified framework, as well as the performance of the entire network. To perform sensitivity analysis of the efficiency with respect to the inputs and outputs, a robustness analysis is proposed. To demonstrate the applicability of the proposed model, we apply it to real-life data on 21 fossil-fueled power plants.