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A Layered Fault Tree Model for Reliability Evaluation of Smart Grids

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  • Guopeng Song

    (School of Information System and Management, National University of Defense Technology, Changsha 410073, China)

  • Hao Chen

    (School of Information System and Management, National University of Defense Technology, Changsha 410073, China)

  • Bo Guo

    (School of Information System and Management, National University of Defense Technology, Changsha 410073, China)

Abstract

The smart grid concept has emerged as a result of the requirement for renewable energy resources and application of new techniques. It is proposed as a practical future form of power distribution system. Evaluating the reliability of smart grids is of great importance and significance. Focusing on the perspective of the consumers, this paper proposes a layered fault tree model to distinguish and separate two different smart grid power supply modes. Revised importance measures for the components in the fault tree are presented considering load priority, aiming to find the weak parts of the system and to improve the design and using. A corresponding hierarchical Monte Carlo simulation procedure for reliability evaluation is proposed based on the layered fault tree model. The method proposed in this paper is tested on a case of reliability assessment for the Future Renewable Electric Energy Delivery and Management (FREEDM) system. The proposed technique can be applicable to other forms of smart grids.

Suggested Citation

  • Guopeng Song & Hao Chen & Bo Guo, 2014. "A Layered Fault Tree Model for Reliability Evaluation of Smart Grids," Energies, MDPI, vol. 7(8), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:8:p:4835-4857:d:38661
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    References listed on IDEAS

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    1. Luca Ardito & Giuseppe Procaccianti & Giuseppe Menga & Maurizio Morisio, 2013. "Smart Grid Technologies in Europe: An Overview," Energies, MDPI, vol. 6(1), pages 1-31, January.
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    Cited by:

    1. Gisliany Alves & Danielle Marques & Ivanovitch Silva & Luiz Affonso Guedes & Maria da Guia da Silva, 2019. "A Methodology for Dependability Evaluation of Smart Grids," Energies, MDPI, vol. 12(9), pages 1-23, May.
    2. Federica Cucchiella & Idiano D’Adamo & Paolo Rosa, 2015. "Industrial Photovoltaic Systems: An Economic Analysis in Non-Subsidized Electricity Markets," Energies, MDPI, vol. 8(11), pages 1-16, November.
    3. Zheng, Junjun & Okamura, Hiroyuki & Pang, Taoming & Dohi, Tadashi, 2021. "Availability importance measures of components in smart electric power grid systems," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
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    5. Jinchao Li & Tianzhi Li & Liu Han, 2018. "Research on the Evaluation Model of a Smart Grid Development Level Based on Differentiation of Development Demand," Sustainability, MDPI, vol. 10(11), pages 1-25, November.
    6. Huiru Zhao & Nana Li, 2016. "Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods," Sustainability, MDPI, vol. 8(2), pages 1-22, January.
    7. Zhou, Jian-Lan & Lei, Yi & Chen, Yang, 2019. "A hybrid HEART method to estimate human error probabilities in locomotive driving process," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 80-89.
    8. Kuei-Hu Chang, 2022. "A novel reliability calculation method under neutrosophic environments," Annals of Operations Research, Springer, vol. 315(2), pages 1599-1615, August.
    9. Enrique Personal & Antonio García & Antonio Parejo & Diego Francisco Larios & Félix Biscarri & Carlos León, 2016. "A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems," Energies, MDPI, vol. 9(12), pages 1-30, December.
    10. Hossam A. Gabbar & Yahya Koraz, 2017. "Risk Assessment of Micro Energy Grid Protection Layers," Energies, MDPI, vol. 10(8), pages 1-19, August.

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