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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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Abstract

A framework for the reliability evaluation of grid-connected photovoltaic (PV) systems with intermittent faults is proposed using dynamic Bayesian networks (DBNs). 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.

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Authors and Affiliations

  1. China University of Petroleum, Qingdao, Shandong, China

    Baoping Cai, Yonghong Liu, Zengkai Liu & Yuanjiang Chang

  2. Southwest Jiaotong University, Chengdu, Sichuan, China

    Lei Jiang

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  1. Baoping Cai
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  2. Yonghong Liu
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  3. Zengkai Liu
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Correspondence to Baoping Cai .

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Cai, B., Liu, Y., Liu, Z., Chang, Y., Jiang, L. (2020). A Framework for the Reliability Evaluation of Grid-Connected Photovoltaic Systems in the Presence of Intermittent Faults. In: Bayesian Networks for Reliability Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-6516-4_2

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