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Reliability evaluation of integrated energy systems based on smart agent communication

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  • Li, Gengfeng
  • Bie, Zhaohong
  • Kou, Yu
  • Jiang, Jiangfeng
  • Bettinelli, Mattia

Abstract

Reliability evaluation of Integrated Energy Systems (IESs) based on Smart Agent Communication (SAC) is studied in this paper. The typical structure and reliability evaluation modeling for IESs is firstly introduced. A new reliability evaluation approach is then presented, in which SAC based system reconfiguration is innovatively integrated into the reliability evaluation process. Based on this combination, state evaluation (key procedure of the reliability evaluation) along with system reconfiguration can be conducted autonomously in reliability evaluation. Algorithm and procedures of the system reconfiguration based on a decentralized agent communication algorithm (K−1 algorithm) is described. The system reconfiguration does not depend on global information of whole system, which can effectively improve reliability evaluation and modeling efficiency. The presented models and approaches are conducted on the multi-paradigm modeling and simulation platform-AnyLogic, and validated by extensive cases studies.

Suggested Citation

  • Li, Gengfeng & Bie, Zhaohong & Kou, Yu & Jiang, Jiangfeng & Bettinelli, Mattia, 2016. "Reliability evaluation of integrated energy systems based on smart agent communication," Applied Energy, Elsevier, vol. 167(C), pages 397-406.
    • Handle: RePEc:eee:appene:v:167:y:2016:i:c:p:397-406
    DOI: 10.1016/j.apenergy.2015.11.033
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    16. You Zhou & Chuan He, 2022. "A Review on Reliability of Integrated Electricity-Gas System," Energies, MDPI, vol. 15(18), pages 1-22, September.
    17. Su, Rui & Chen, Bin & Wang, Saige & Duan, Cuncun, 2024. "Energy technical resilience assessment based on complex network analysis – A case study of China," Applied Energy, Elsevier, vol. 364(C).
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    23. Qin, Peijia & Tan, Xianlin & Huang, Youbin & Pan, Mingming & Ouyang, Tiancheng, 2023. "Two-stage robust optimal scheduling framework applied for microgrids: Combined energy recovery and forecast," Renewable Energy, Elsevier, vol. 214(C), pages 290-306.
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