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A framework for the reliability evaluation of grid-connected photovoltaic systems in the presence of intermittent faults

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  • Cai, Baoping
  • Liu, Yonghong
  • Ma, Yunpeng
  • Huang, Lei
  • Liu, Zengkai

Abstract

A framework for the reliability evaluation of grid-connected PV (photovoltaic) systems with intermittent faults is proposed using DBNs (dynamic Bayesian networks). A three-state Markov model is constructed to represent the state transition relationship of no faults, intermittent faults, and permanent faults for PV components. The model is subsequently fused into the DBNs. The reliability and availability of three simple PV systems with centralized, string, and multistring configurations, as well as a complex PV system, are analyzed through the proposed framework. The sequence of the degree of importance of PV components is investigated using mutual information. The effects of intermittent fault parameters, including the coefficients of intermittent fault, permanent fault, and intermittent repair, on the reliability and availability are explored. Results show that the reliability and availability of the PV system with centralized configuration rapidly decrease, compared with those of the PV systems with string and multistring configurations. The sequence of the degree of importance of PV components is DC/AC inverter, DC/DC converter, DC combiner, and PV module arranged from the largest to the smallest. The finding indicates that the DC/AC inverter should be given considerable attention to improve the reliability and availability and to prevent their possible failures.

Suggested Citation

  • Cai, Baoping & Liu, Yonghong & Ma, Yunpeng & Huang, Lei & Liu, Zengkai, 2015. "A framework for the reliability evaluation of grid-connected photovoltaic systems in the presence of intermittent faults," Energy, Elsevier, vol. 93(P2), pages 1308-1320.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1308-1320
    DOI: 10.1016/j.energy.2015.10.068
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    3. Belaout, A. & Krim, F. & Mellit, A. & Talbi, B. & Arabi, A., 2018. "Multiclass adaptive neuro-fuzzy classifier and feature selection techniques for photovoltaic array fault detection and classification," Renewable Energy, Elsevier, vol. 127(C), pages 548-558.
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    7. Sayed, A. & EL-Shimy, M. & El-Metwally, M. & Elshahed, M., 2020. "Impact of subsystems on the overall system availability for the large scale grid-connected photovoltaic systems," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    8. Pramod R. Sonawane & Sheetal Bhandari & Rajkumar Bhimgonda Patil & Sameer Al-Dahidi, 2023. "Reliability and Criticality Analysis of a Large-Scale Solar Photovoltaic System Using Fault Tree Analysis Approach," Sustainability, MDPI, vol. 15(5), pages 1-24, March.
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    10. A. Sayed & M. El-Shimy & M. El-Metwally & M. Elshahed, 2019. "Reliability, Availability and Maintainability Analysis for Grid-Connected Solar Photovoltaic Systems," Energies, MDPI, vol. 12(7), pages 1-18, March.
    11. Cai, Baoping & Liu, Yu & Fan, Qian, 2016. "A multiphase dynamic Bayesian networks methodology for the determination of safety integrity levels," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 105-115.
    12. Karngala, Arun Kumar & Singh, Chanan, 2023. "Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage," Applied Energy, Elsevier, vol. 344(C).
    13. Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2024. "Photovoltaic systems operation and maintenance: A review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).

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