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  • Zhang, Li  (3)
  • Zhang, Yunpeng  (3)
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  • 1
    Online Resource
    Online Resource
    AIP Publishing ; 2022
    In:  Journal of Renewable and Sustainable Energy Vol. 14, No. 3 ( 2022-05-01)
    In: Journal of Renewable and Sustainable Energy, AIP Publishing, Vol. 14, No. 3 ( 2022-05-01)
    Abstract: The current–voltage (I–V) equation in the equivalent circuit model of the photovoltaic (PV) module is implicit, and the dependence of model parameters on environmental conditions is uncertain, which causes inconvenience in output performance prediction. In this paper, a novel method based on the power-law model (PLM) is proposed to predict the I–V characteristics and output power of PV modules under varying operating conditions. The relationship between parameters in the PLM and manufacturer datasheet information is established. The irradiance and temperature dependences of shape parameters in PLM are obtained and investigated thoroughly. Due to inherent simplicity and explicit expression of PLM, the proposed method predicts the I–V characteristics and output power without using any iterative process, which reduces the computational complexity. The proposed method is validated by different types PV modules and under a wide range of environmental conditions. Comparing with traditional methods based on a single-diode model, the proposed method has better agreements with experimental results in all irradiance and temperature intervals. The accuracy and effectiveness are verified both in short-term and long-term output power prediction. The proposed method is simple and suitable to predict the actual output properties of PV modules under varying operating conditions.
    Type of Medium: Online Resource
    ISSN: 1941-7012
    Language: English
    Publisher: AIP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 2444311-6
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    AIP Publishing ; 2023
    In:  Journal of Renewable and Sustainable Energy Vol. 15, No. 3 ( 2023-05-01)
    In: Journal of Renewable and Sustainable Energy, AIP Publishing, Vol. 15, No. 3 ( 2023-05-01)
    Abstract: In traditional methods, electrical property estimation of photovoltaic (PV) modules is achieved through two steps. First, a certain condition (usually standard testing condition, STC) is selected as the reference condition, and the physical parameters under the reference condition are extracted from current–voltage data points. Second, physical parameters under varying operating conditions are obtained by transforming equations, and the electrical properties of the PV modules are estimated. In this paper, the influence of different reference conditions on the accuracy of performance estimation is studied. The estimation results using different reference conditions are compared to obtain the error distribution pattern, which has essential reference significance for the selection of reference conditions in practical applications. In addition, a method of the selecting reference condition is proposed. A new objective function is proposed by considering three key operating points for each I–V curve under different operating conditions, which balances accuracy and computational complexity. A large amount of experimental data for different types of PV modules are used to validate the effectiveness and accuracy of the proposed method. In comparison with the traditional methods using STC as the reference condition and existing method in Matlab/Simulink, the results obtained by the proposed method exhibit better accuracy. It can be further used to estimate the output power of PV system under varying operating conditions.
    Type of Medium: Online Resource
    ISSN: 1941-7012
    Language: English
    Publisher: AIP Publishing
    Publication Date: 2023
    detail.hit.zdb_id: 2444311-6
    Location Call Number Limitation Availability
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  • 3
    In: Energy Reports, Elsevier BV, Vol. 8 ( 2022-11), p. 13859-13875
    Type of Medium: Online Resource
    ISSN: 2352-4847
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2814795-9
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