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Development of centralized hybrid data envelopment analysis models to allocate emissions abatement for fossil fuel power plants during their current and replacement phases

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  • Yeh, Li-Ting

Abstract

Many countries have long relied on fossil fuel power plants to ensure a stable electricity supply. However, the issue of pollution emissions from these power plants has raised widespread concerns. Because heat, power generation, and pollution emissions are jointly produced by consuming fossil fuels, previous research has typically employed standard hybrid data envelopment analysis (DEA) models. Since the fossil fuel power plants are under centralized management, it is crucial for government decision-makers to optimize the overall efficiency of all power plants rather than solely considering the efficiency of a single power plant. Therefore, this study presents two centralized hybrid DEA models. By applying the models proposed in this study, Taiwanese decision-makers can form optimal allocation policies for pollution emissions abatement among their 56 fossil fuel power plants during both the current and replacement upgrade phases. The significant findings of this study are as follows: First, the proposed model can efficiently allocate pollution emissions abatement among current fossil fuel power plants. Second, the proposed model can be further expanded to determine which fossil fuel power plants should be prioritized for replacement and how to effectively allocate policies for reducing pollution emissions among the remaining power plants.

Suggested Citation

  • Yeh, Li-Ting, 2025. "Development of centralized hybrid data envelopment analysis models to allocate emissions abatement for fossil fuel power plants during their current and replacement phases," Energy Economics, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:eneeco:v:146:y:2025:i:c:s0140988325003469
    DOI: 10.1016/j.eneco.2025.108522
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