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Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach

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  • Alizadeh, Reza
  • Gharizadeh Beiragh, Ramin
  • Soltanisehat, Leili
  • Soltanzadeh, Elham
  • Lund, Peter D.

Abstract

To evaluate the performance of complex electricity generation systems, a new dynamic network-based data envelopment analysis (DNDEA) approach is presented. Past data envelopment analysis (DEA) studies on energy system efficiency have often ignored the dynamics of each process of the system individually. Here a network-based DEA method is built, which considers the interrelationships of the operations to determine the efficacy of the system. For assessing the performance over successive periods, with time-based dependencies between the successive periods, a dynamic DEA (DDEA) model is proposed. In DDEA, a linear combination of the efficiencies in successive periods is used as the complement of the system. The network-based and dynamic features of the created model enable measuring the performance of each sub-system process and the entire system in multi-period planning horizons simultaneously. These features make the DEA model identify changes in system efficiencies so much better than the current approaches. The created model is comprehensively implemented in the Iranian electricity sector using real data. Based on the findings, the efficiencies of power generation and transmission sectors are decreasing while the distribution performance is increasing. The proposed model could be applied to electricity generation systems in other countries as well.

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  • Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
  • Handle: RePEc:eee:eneeco:v:91:y:2020:i:c:s0140988320302346
    DOI: 10.1016/j.eneco.2020.104894
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    2. Maghsoud Amiri & Mohammad Hashemi-Tabatabaei & Mohammad Ghahremanloo & Mehdi Keshavarz-Ghorabaee & Edmundas Kazimieras Zavadskas & Arturas Kaklauskas, 2021. "Evaluating Life Cycle of Buildings Using an Integrated Approach Based on Quantitative-Qualitative and Simplified Best-Worst Methods (QQM-SBWM)," Sustainability, MDPI, vol. 13(8), pages 1-28, April.
    3. Pritpal Singh & Gurdeep Singh & G. P. S. Sodhi, 2022. "Data envelopment analysis based optimization for improving net ecosystem carbon and energy budget in cotton (Gossypium hirsutum L.) cultivation: methods and a case study of north-western India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2079-2119, February.
    4. Suzer, Ahmet Esat & Atasoy, Vehbi Emrah & Ekici, Selcuk, 2021. "Developing a holistic simulation approach for parametric techno-economic analysis of wind energy," Energy Policy, Elsevier, vol. 149(C).
    5. Ziwei Xiao & Chunxiao Zhang, 2021. "Construction of Meteorological Simulation Knowledge Graph Based on Deep Learning Method," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    6. Mohammad Rasouli & Demosthenis Teneketzis, 2021. "Economizing the Uneconomic: Markets for Reliable, Sustainable, and Price Efficient Electricity," Sustainability, MDPI, vol. 13(8), pages 1-38, April.
    7. Alizadeh, Reza & Lund, Peter D. & Soltanisehat, Leili, 2020. "Outlook on biofuels in future studies: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    8. Danzhu Wang & Lingyun Zhou & Huimin Zhang & Xiaokang Liang, 2021. "A Bi-Level Model for Green Freight Transportation Pricing Strategy Considering Enterprise Profit and Carbon Emissions," Sustainability, MDPI, vol. 13(12), pages 1-20, June.

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