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Benefit Evaluation of Carbon Reduction in Power Transmission and Transformation Projects Based on the Modified TOPSIS-RSR Method

Author

Listed:
  • Yinan Wang

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Heng Chen

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Shuyuan Zhao

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Lanxin Fan

    (School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China)

  • Cheng Xin

    (State Grid Economic and Technical Research Institute Ltd., Beijing 102209, China)

  • Xue Jiang

    (Economic and Technical Research Institute of State Grid Liaoning Electric Power Co., Shenyang 110015, China)

  • Fan Yao

    (Economic and Technical Research Institute of State Grid Chongqing Electric Power Co., Chongqing 404100, China)

Abstract

In order to fully achieve energy saving goals, it is necessary to establish a comprehensive evaluation system for carbon reduction in transmission and transformation projects. Subsequently, weights were assigned to these indicators using a combination of the fuzzy analytical hierarchy process (FAHP) and the entropy weight method (EWM) through both subjective and objective methods. Finally, the ultimate weights were obtained by applying the principle of minimum information. During the construction of the evaluation model, the rank–sum ratio (RSR) method was introduced into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for approximating ideal solution ranking. And the Euclidean distance in TOPSIS was replaced with standardized Euclidean distance, effectively avoiding evaluation discrepancies caused by different dimensions. The modified TOPSIS-RSR method was utilized to evaluate and rank power transmission and transformation projects in four regions. By comparing the test values of the two models, the superiority of the enhanced model was confirmed. Furthermore, the GM (1,1) model is used to predict the electricity sales volume of the optimal ranking area. This evaluation model can also be applied to the benefit evaluation of carbon reduction benefits in power transmission and transformation projects in other regions.

Suggested Citation

  • Yinan Wang & Heng Chen & Shuyuan Zhao & Lanxin Fan & Cheng Xin & Xue Jiang & Fan Yao, 2024. "Benefit Evaluation of Carbon Reduction in Power Transmission and Transformation Projects Based on the Modified TOPSIS-RSR Method," Energies, MDPI, vol. 17(12), pages 1-23, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2988-:d:1416707
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    References listed on IDEAS

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    1. Lei, Xu & Xin-gang, Zhao, 2023. "The synergistic effect between Renewable Portfolio Standards and carbon emission trading system: A perspective of China," Renewable Energy, Elsevier, vol. 211(C), pages 1010-1023.
    2. Zare Banadkouki, Mohammad Reza, 2023. "Selection of strategies to improve energy efficiency in industry: A hybrid approach using entropy weight method and fuzzy TOPSIS," Energy, Elsevier, vol. 279(C).
    3. Na Chen & Zeshui Xu & Meimei Xia, 2015. "The ELECTRE I Multi-Criteria Decision-Making Method Based on Hesitant Fuzzy Sets," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 621-657.
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    1. Yong Cui & Jian Zheng & Wenying Wu & Kun Xu & Desen Ji & Tian Di, 2024. "Framework and Outlooks of Multi-Source–Grid–Load Coordinated Low-Carbon Operational Systems Considering Demand-Side Hierarchical Response," Energies, MDPI, vol. 17(23), pages 1-20, December.

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