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Integrated reliability evaluation of transportation self-consistent energy system architecture configuration schemes based on reliability engineering and data uncertainty

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  • Huang, Hongxin
  • Hu, Liqun
  • Xu, Xianfeng
  • Han, Zhenqiang

Abstract

To advance the development of renewable energy within transportation spaces, this paper establishes an evaluation index system and method for the technical performance of transportation self-consistent energy system (TSCES) architectures during the planning phase. The evaluation index system includes five primary indicators: reliability, availability, maintainability, safety, and resilience, alongside twelve secondary indicators. The method combines Latin hypercube sampling and simultaneous backtracking scenario reduction to generate uncertain data scenarios. The CRITIC-entropy weighting method and AHP method are employed for comprehensive weighting of evaluation indicators. A case study and sensitivity analysis is conducted. Results indicate that evaluation results from different operation modes exhibit similar trends. In the case study, for every 200 MWh reduction in installed capacity, the evaluation result decreases by approximately 0.12. The effects induced by equipment failure rates and repair rates demonstrate mutually counteractive characteristics. Considering the operating conditions of equipment, an architecture with diesel generators as backup power and off-grid operation exhibits the best technical performance. The proposed evaluation method integrates data scenarios and system architecture configurations, yielding more reasonable results compared to single historical data scenario assessments. The evaluation index system and method proposed in this paper provide comprehensive and effective technical performance evaluations of TSCES architectures.

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  • Huang, Hongxin & Hu, Liqun & Xu, Xianfeng & Han, Zhenqiang, 2025. "Integrated reliability evaluation of transportation self-consistent energy system architecture configuration schemes based on reliability engineering and data uncertainty," Renewable Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:renene:v:245:y:2025:i:c:s0960148125004434
    DOI: 10.1016/j.renene.2025.122781
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