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Determination of the current–voltage characteristics of concentrator systems by using different adapted conventional techniques

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  • Almonacid, Florencia
  • Rodrigo, Pedro
  • Fernández, Eduardo F.

Abstract

The modelling of the current–voltage characteristics of HCPV (high concentrator photovoltaic) modules is fundamental for the design, monitoring and energy prediction of HCPV systems and power plants. However, the modelling of these devices is inherently different and more complex than that of conventional PV (photovoltaic) modules. Because of this, considerable efforts have been done to develop models tailored to the specific features of this technology. However, there is still a lack of studies and techniques concerning the modelling of the whole I–V curve of HCPV modules. In the present work, the possibility of obtaining the I–V curve of a HCPV module by applying common methods exploited in conventional PV technology by using the effective irradiance and cell temperature is analysed. In particular, the studied methods are: the single exponential model, the Blasser's method and the bilinear interpolation method. Every method has been adapted to be entirely function of the effective irradiance and cell temperature of the concentrator. Results show that all the methods present a good performance in the estimation of the I–V curve of a concentrator, with an average RMSE (root mean square error) ranging from 1.15% to 5.23%, and an average MBE (mean bias error) close to 0%.

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  • Almonacid, Florencia & Rodrigo, Pedro & Fernández, Eduardo F., 2016. "Determination of the current–voltage characteristics of concentrator systems by using different adapted conventional techniques," Energy, Elsevier, vol. 101(C), pages 146-160.
    • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:146-160
    DOI: 10.1016/j.energy.2016.01.082
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    References listed on IDEAS

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    1. Leloux, Jonathan & Lorenzo, Eduardo & García-Domingo, Beatriz & Aguilera, Jorge & Gueymard, Christian A., 2014. "A bankable method of assessing the performance of a CPV plant," Applied Energy, Elsevier, vol. 118(C), pages 1-11.
    2. Cotfas, D.T. & Cotfas, P.A. & Kaplanis, S., 2013. "Methods to determine the dc parameters of solar cells: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 588-596.
    3. Fernández, Eduardo F. & Almonacid, Florencia & Soria-Moya, Alberto & Terrados, Julio, 2015. "Experimental analysis of the spectral factor for quantifying the spectral influence on concentrator photovoltaic systems under real operating conditions," Energy, Elsevier, vol. 90(P2), pages 1878-1886.
    4. Fernández, Eduardo F. & Almonacid, Florencia & Garcia-Loureiro, Antonio J., 2015. "Multi-junction solar cells electrical characterization by neuronal networks under different irradiance, spectrum and cell temperature," Energy, Elsevier, vol. 90(P1), pages 846-856.
    5. Fernández, Eduardo F. & Almonacid, Florencia, 2014. "Spectrally corrected direct normal irradiance based on artificial neural networks for high concentrator photovoltaic applications," Energy, Elsevier, vol. 74(C), pages 941-949.
    6. Almonacid, F. & Rus, C. & Hontoria, L. & Fuentes, M. & Nofuentes, G., 2009. "Characterisation of Si-crystalline PV modules by artificial neural networks," Renewable Energy, Elsevier, vol. 34(4), pages 941-949.
    7. Rodrigo, P. & Fernández, E.F. & Almonacid, F. & Pérez-Higueras, P.J., 2014. "Review of methods for the calculation of cell temperature in high concentration photovoltaic modules for electrical characterization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 478-488.
    8. Piliougine, Michel & Elizondo, David & Mora-López, Llanos & Sidrach-de-Cardona, Mariano, 2013. "Multilayer perceptron applied to the estimation of the influence of the solar spectral distribution on thin-film photovoltaic modules," Applied Energy, Elsevier, vol. 112(C), pages 610-617.
    9. Talavera, D.L. & Pérez-Higueras, P. & Ruíz-Arias, J.A. & Fernández, E.F., 2015. "Levelised cost of electricity in high concentrated photovoltaic grid connected systems: Spatial analysis of Spain," Applied Energy, Elsevier, vol. 151(C), pages 49-59.
    10. García-Domingo, B. & Aguilera, J. & de la Casa, J. & Fuentes, M., 2014. "Modelling the influence of atmospheric conditions on the outdoor real performance of a CPV (Concentrated Photovoltaic) module," Energy, Elsevier, vol. 70(C), pages 239-250.
    11. Fernández, Eduardo F. & Pérez-Higueras, P. & Almonacid, F. & Ruiz-Arias, J.A. & Rodrigo, P. & Fernandez, J.I. & Luque-Heredia, I., 2015. "Model for estimating the energy yield of a high concentrator photovoltaic system," Energy, Elsevier, vol. 87(C), pages 77-85.
    12. Rodrigo, P. & Fernández, E.F. & Almonacid, F. & Pérez-Higueras, P.J., 2013. "Models for the electrical characterization of high concentration photovoltaic cells and modules: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 752-760.
    13. Almonacid, F. & Fernández, E.F. & Mallick, T.K. & Pérez-Higueras, P.J., 2015. "High concentrator photovoltaic module simulation by neuronal networks using spectrally corrected direct normal irradiance and cell temperature," Energy, Elsevier, vol. 84(C), pages 336-343.
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    Cited by:

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    2. Rodrigo, P. & Velázquez, Ramiro & Fernández, Eduardo F. & Almonacid, F. & Pérez-Higueras, P.J., 2016. "Analysis of electrical mismatches in high-concentrator photovoltaic power plants with distributed inverter configurations," Energy, Elsevier, vol. 107(C), pages 374-387.
    3. Rodrigo, P.M. & Talavera, D.L. & Fernández, E.F. & Almonacid, F.M. & Pérez-Higueras, P.J., 2019. "Optimum capacity of the inverters in concentrator photovoltaic power plants with emphasis on shading impact," Energy, Elsevier, vol. 187(C).
    4. Khan, Firoz & Al-Ahmed, Amir & Al-Sulaiman, Fahad A., 2021. "Critical analysis of the limitations and validity of the assumptions with the analytical methods commonly used to determine the photovoltaic cell parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    5. Almonacid, Florencia & Fernandez, Eduardo F. & Mellit, Adel & Kalogirou, Soteris, 2017. "Review of techniques based on artificial neural networks for the electrical characterization of concentrator photovoltaic technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 938-953.
    6. Nofuentes, Gustavo & de la Casa, Juan & Solís-Alemán, Ernesto M. & Fernández, Eduardo F., 2017. "Spectral impact on PV performance in mid-latitude sunny inland sites: Experimental vs. modelled results," Energy, Elsevier, vol. 141(C), pages 1857-1868.
    7. Manuel Cáceres & Andrés Firman & Jesús Montes-Romero & Alexis Raúl González Mayans & Luis Horacio Vera & Eduardo F. Fernández & Juan de la Casa Higueras, 2020. "Low-Cost I–V Tracer for PV Modules under Real Operating Conditions," Energies, MDPI, vol. 13(17), pages 1-17, August.

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