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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%.

Suggested Citation

  • 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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    Cited by:

    1. Peñaranda Chenche, Luz Elena & Hernandez Mendoza, Oscar Saul & Bandarra Filho, Enio Pedone, 2018. "Comparison of four methods for parameter estimation of mono- and multi-junction photovoltaic devices using experimental data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2823-2838.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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).

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