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A robust parametrization method of photovoltaic modules for enhancing one-diode model accuracy under varying operating conditions

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  • Li, Chenxi
  • Yang, Yongheng
  • Spataru, Sergiu
  • Zhang, Kanjian
  • Wei, Haikun

Abstract

Modeling the current-voltage (I–V) characteristics of photovoltaic (PV) modules is of importance for condition monitoring and fault diagnosis of PV arrays. The practicality of the one-diode model (ODM) is relying on the behaviors of parameter extraction and translation techniques. In this paper, a simple and robust dual-iteration algorithm is presented to extract the ODM parameters using only three points under limited conditions. These points can be easily obtained from both the datasheet and measurements, making the method universal and practical. Parameters under other unknown conditions are translated from the nearest acquired condition to make the proposed method applicable for various conditions. The modeling I–V curve obtained by the proposed method is in a close agreement with the field measurement, demonstrating its effectiveness to characterize the PV modules with different technologies. Moreover, three existing models are used to benchmark the accuracy of the proposed method. The comparison further confirms that the accuracy of the ODM has been enhanced especially at low irradiance using the proposed parameter translation method. Furthermore, a distance-weighted method is presented to reliably translate the parameters, whose superiority has been validated against measurements and the other four methods, thus being an effective output assessment for monitoring and diagnosis.

Suggested Citation

  • Li, Chenxi & Yang, Yongheng & Spataru, Sergiu & Zhang, Kanjian & Wei, Haikun, 2021. "A robust parametrization method of photovoltaic modules for enhancing one-diode model accuracy under varying operating conditions," Renewable Energy, Elsevier, vol. 168(C), pages 764-778.
    • Handle: RePEc:eee:renene:v:168:y:2021:i:c:p:764-778
    DOI: 10.1016/j.renene.2020.12.097
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    References listed on IDEAS

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    Cited by:

    1. Schuster, Christian Stefano & Koc, Mehmet & Yerci, Selcuk, 2022. "Analytic modelling of multi-junction solar cells via multi-diodes," Renewable Energy, Elsevier, vol. 184(C), pages 1033-1042.
    2. Li, Fuxiang & Wu, Wei, 2022. "Coupled electrical-thermal performance estimation of photovoltaic devices: A transient multiphysics framework with robust parameter extraction and 3-D thermal analysis," Applied Energy, Elsevier, vol. 319(C).
    3. Shen, Yu & He, Zengxiang & Xu, Zhen & Wang, Yiye & Li, Chenxi & Zhang, Jinxia & Zhang, Kanjian & Wei, Haikun, 2022. "Modeling of photovoltaic modules under common shading conditions," Energy, Elsevier, vol. 256(C).

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