Sustainability-oriented prioritization of nuclear fuel cycle transitions in China: a holistic MCDM framework under uncertainties

Lei Wang, Ru Xing Gao, Hyo On Nam, Hong Jang, Won Il Ko, Chun Dong Zhang, Guo An Ye, Wen Heng Jing

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A sustainability-oriented assessment of the nuclear energy system can provide informative and convincing decision-making support for nuclear development strategies in China. In our previous study, four authentic nuclear fuel cycle (NFC) transition scenarios were proposed, featuring different development stages and exhibiting distinct environmental, economic, and technical characteristics. However, because of the multiple and often conflicting criteria embedded therein, determining the top-priority NFC alternative for a sustainability orientation remains challenging. To address this issue, this study proposed a novel hybrid multi-criteria decision-making framework comprising fuzzy AHP, PROMETHEE GAIA, and MOORA. Initially, an improved fuzzy AHP weighting model was developed to determine criteria weights under uncertainty and investigate the influence of various weight aggregation and defuzzification approaches. Subsequently, PROMETHEE GAIA was used to address conflicts among the criteria and prioritize alternatives on a visualized k-dimensional GAIA plane. As a result, the alternative for direct recycling PWR spent fuel in fast reactors is considered the most sustainable. Furthermore, a sensitivity analysis was conducted to examine the influence of criteria weight variation and validate the screening results. Finally, using MOORA, some significant optimization ideas and valuable insights were provided to support decision-makers in shaping nuclear development strategies.

Original languageEnglish
Article number158
JournalNuclear Science and Techniques/Hewuli
Volume35
Issue number9
DOIs
StatePublished - Sep 2024

Keywords

  • Fuzzy AHP
  • Nuclear energy systems
  • Nuclear fuel cycle
  • PROMETHEE GAIA

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