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Feasibility of Photovoltaic Module Single-Diode Model Fitting to the Current–Voltage Curves Measured in the Vicinity of the Maximum Power Point for Online Condition Monitoring Purposes

Author

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  • Heidi Kalliojärvi

    (Electrical Engineering Unit, Tampere University, P.O. Box 692, 33101 Tampere, Finland)

  • Kari Lappalainen

    (Electrical Engineering Unit, Tampere University, P.O. Box 692, 33101 Tampere, Finland)

  • Seppo Valkealahti

    (Electrical Engineering Unit, Tampere University, P.O. Box 692, 33101 Tampere, Finland)

Abstract

Photovoltaic system condition monitoring can be performed via single-diode model fitting to measured current–voltage curves. Model parameters can reveal cell aging and degradation. Conventional parameter identification methods require the measurement of entire current–voltage curves, causing interruptions in energy production. Instead, partial curves measured near the maximum power point offer a promising option for online condition monitoring. Unfortunately, measurement data reduction affects fitting and diagnosis accuracy. Thus, the optimal selection of maximum power point neighbourhoods used for fitting requires a systematic analysis of the effect of data selection on the fitted parameters. To date, only one published article has addressed this issue with a small number of measured curves using symmetrically chosen neighbourhoods with respect to the maximum power. Moreover, no study has determined single-diode fit quality to partial curves constructed via other principles, e.g., as a percentage of the maximum power point voltage. Such investigation is justified since the voltage is typically the inverter reference quantity. Our work takes the study of this topic to a whole new scientific level by systematically examining how limiting the current–voltage curve measuring range to maximum power point proximity based on both power and voltage affects single-diode model parameters. An extensive dataset with 2400 measured curves was analysed, and statistically credible results were obtained for the first time. We fitted the single-diode model directly to experimental curves without measuring outdoor conditions or using approximations. Our results provide clear guidance on how the choices of partial curves affect the fitting accuracy. A significant finding is that the correct selection of maximum power point neighbourhoods provides promising real-case online aging detection opportunities.

Suggested Citation

  • Heidi Kalliojärvi & Kari Lappalainen & Seppo Valkealahti, 2022. "Feasibility of Photovoltaic Module Single-Diode Model Fitting to the Current–Voltage Curves Measured in the Vicinity of the Maximum Power Point for Online Condition Monitoring Purposes," Energies, MDPI, vol. 15(23), pages 1-21, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9079-:d:989525
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    References listed on IDEAS

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    1. Garrigós, Ausias & Blanes, José M. & Carrasco, José A. & Ejea, Juan B., 2007. "Real time estimation of photovoltaic modules characteristics and its application to maximum power point operation," Renewable Energy, Elsevier, vol. 32(6), pages 1059-1076.
    2. Toledo, F.J. & Blanes, José M., 2016. "Analytical and quasi-explicit four arbitrary point method for extraction of solar cell single-diode model parameters," Renewable Energy, Elsevier, vol. 92(C), pages 346-356.
    3. Toledo, F.J. & Blanes, José M. & Garrigós, Ausiàs & Martínez, José A., 2012. "Analytical resolution of the electrical four-parameters model of a photovoltaic module using small perturbation around the operating point," Renewable Energy, Elsevier, vol. 43(C), pages 83-89.
    4. Bastidas-Rodriguez, J.D. & Franco, E. & Petrone, G. & Ramos-Paja, C.A. & Spagnuolo, G., 2017. "Quantification of photovoltaic module degradation using model based indicators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 101-113.
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    Cited by:

    1. Li, Baojie & Hansen, Clifford W. & Chen, Xin & Diallo, Demba & Migan-Dubois, Anne & Delpha, Claude & Jain, Anubhav, 2024. "A robust I–V curve correction procedure for degraded photovoltaic modules," Renewable Energy, Elsevier, vol. 224(C).
    2. Lappalainen, Kari & Piliougine, Michel & Valkealahti, Seppo & Spagnuolo, Giovanni, 2024. "Photovoltaic module series resistance identification at its maximum power production," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 224(PA), pages 50-62.

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