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Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework

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  • Yang, Zaoli
  • Shang, Wen-Long
  • Zhang, Haoran
  • Garg, Harish
  • Han, Chunjia

Abstract

Popularizing green distribution transformers is a viable way to reduce power loss and environmental pollution and improve energy conversion and transmission efficiency, which has become the trend of power equipment manufacturing and market demand. However, due to conflicting multi-criteria and goals and factors, higher standards are required for green distribution transformer manufacturing. High standard manufacturing makes many manufacturers shoddy the internal components of green distribution transformers, resulting in disorderly competition in the market, which poses great challenges to the users' choice of transformers and the government's quality supervision. This paper proposes a cloud-based q-rung orthopair fuzzy multi-criteria framework for assessing the green distribution transformer manufacturing process from the perspective of conflicting relationships between criteria. It is applied to rank order four green transformer manufacturers in China based on the twelve mono-criteria under four categories of resource and energy utilization, production process and equipment, environmental coordination, green technology innovation, and their overall performance ranking results. Our analysis revealed that resource and energy utilization and green technology innovation is the motivating factors to improve the quality of green distribution transformer manufacturing and expert recognition, and the production process and equipment and environmental coordination are the inducing factors that reduce the quality of green distribution transformer manufacturing and the recognition of experts. These findings provide the demanders and government quality inspection departments with guidelines on the selection and evaluation of green distribution transformers, also identify the direction for the manufacturers to improve the technology and optimize the production of green distribution transformers.

Suggested Citation

  • Yang, Zaoli & Shang, Wen-Long & Zhang, Haoran & Garg, Harish & Han, Chunjia, 2022. "Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework," Applied Energy, Elsevier, vol. 311(C).
    • Handle: RePEc:eee:appene:v:311:y:2022:i:c:s0306261922001520
    DOI: 10.1016/j.apenergy.2022.118687
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    3. Yang, Zaoli & Ahmad, Salman & Bernardi, Andrea & Shang, Wen-long & Xuan, Jin & Xu, Bing, 2023. "Evaluating alternative low carbon fuel technologies using a stakeholder participation-based q-rung orthopair linguistic multi-criteria framework," Applied Energy, Elsevier, vol. 332(C).
    4. Qiao, Dongdong & Wei, Xuezhe & Fan, Wenjun & Jiang, Bo & Lai, Xin & Zheng, Yuejiu & Tang, Xiaolin & Dai, Haifeng, 2022. "Toward safe carbon–neutral transportation: Battery internal short circuit diagnosis based on cloud data for electric vehicles," Applied Energy, Elsevier, vol. 317(C).
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    6. Fangxu Gui & Heng Chen & Xinyue Zhao & Peiyuan Pan & Cheng Xin & Xue Jiang, 2024. "Enhancing Economic Efficiency: Analyzing Transformer Life-Cycle Costs in Power Grids," Energies, MDPI, vol. 17(3), pages 1-21, January.
    7. Liu, Qingchen & Li, Hongchang & Shang, Wen-long & Wang, Kun, 2022. "Spatio-temporal distribution of Chinese cities’ air quality and the impact of high-speed rail," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    8. Raghunathan Krishankumar & Arunodaya Raj Mishra & Pratibha Rani & Fausto Cavallaro & Kattur Soundarapandian Ravichandran, 2023. "A Novel Integrated q-Rung Fuzzy Framework for Biomass Location Selection with No Apriori Weight Choices," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    9. Hongxin Yu & Yaohui Jiang & Zhaowen Zhang & Wen-Long Shang & Chunjia Han & Yuanjun Zhao, 2022. "The impact of carbon emission trading policy on firms’ green innovation in China," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    10. Zeb, Aurang & Ahmad, Waseem & Asif, Muhammad & Simic, Vladimir & Senapati, Tapan & Hou, Muzhou, 2024. "Optimizing decision-making in electric power system selection: A generalized approach based on Hamacher aggregation operators for q-rung orthopair fuzzy soft sets," Applied Energy, Elsevier, vol. 367(C).

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