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Study on analytical modelling approaches to the performance of thin film PV modules in sunny inland climates

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  • Torres-Ramírez, M.
  • Nofuentes, G.
  • Silva, J.P.
  • Silvestre, S.
  • Muñoz, J.V.

Abstract

This work is aimed at verifying that analytical modelling approaches may provide an estimation of the outdoor performance of TF (thin film) PV (photovoltaic) technologies in inland sites with sunny climates with adequate accuracy for engineering purposes. Osterwald's and constant fill factor methods were tried to model the maximum power delivered and the annual energy produced by PV modules corresponding to four TF PV technologies. Only calibrated electrical parameters at STC (standard test conditions), on-plane global irradiance and module temperature are required as inputs. A 12-month experimental campaign carried out in Madrid and Jaén (Spain) provided the necessary data. Modelled maximum power and annual energy values obtained through both methods were statistically compared to the experimental ones. In power terms, the RMSE (root mean square error) stays below 3.8% and 4.5% for CdTe (cadmium telluride) and CIGS (copper indium gallium selenide sulfide) PV modules, respectively, while RMSE exceeds 5.4% for a-Si (amorphous silicon) or a-Si:H/μc-Si PV modules. Regarding energy terms, errors lie below 4.0% in all cases. Thus, the methods tried may be used to model the outdoor behaviour of the a-Si, a-Si:H/μc-Si, CIGS and CdTe PV modules tested – ordered from the lowest to the highest accuracy obtained – in sites with similar spectral characteristics to those of the two sites considered.

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  • Torres-Ramírez, M. & Nofuentes, G. & Silva, J.P. & Silvestre, S. & Muñoz, J.V., 2014. "Study on analytical modelling approaches to the performance of thin film PV modules in sunny inland climates," Energy, Elsevier, vol. 73(C), pages 731-740.
    • Handle: RePEc:eee:energy:v:73:y:2014:i:c:p:731-740
    DOI: 10.1016/j.energy.2014.06.077
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    1. Cañete, Cristina & Carretero, Jesús & Sidrach-de-Cardona, Mariano, 2014. "Energy performance of different photovoltaic module technologies under outdoor conditions," Energy, Elsevier, vol. 65(C), pages 295-302.
    2. Makrides, George & Zinsser, Bastian & Phinikarides, Alexander & Schubert, Markus & Georghiou, George E., 2012. "Temperature and thermal annealing effects on different photovoltaic technologies," Renewable Energy, Elsevier, vol. 43(C), pages 407-417.
    3. van Dyk, E.E. & Meyer, E.L., 2004. "Analysis of the effect of parasitic resistances on the performance of photovoltaic modules," Renewable Energy, Elsevier, vol. 29(3), pages 333-344.
    4. Almonacid, F. & Rus, C. & Hontoria, L. & Muñoz, F.J., 2010. "Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods," Renewable Energy, Elsevier, vol. 35(5), pages 973-980.
    5. van Dyk, E.E. & Gxasheka, A.R. & Meyer, E.L., 2005. "Monitoring current–voltage characteristics and energy output of silicon photovoltaic modules," Renewable Energy, Elsevier, vol. 30(3), pages 399-411.
    6. Alonso-Abella, M. & Chenlo, F. & Nofuentes, G. & Torres-Ramírez, M., 2014. "Analysis of spectral effects on the energy yield of different PV (photovoltaic) technologies: The case of four specific sites," Energy, Elsevier, vol. 67(C), pages 435-443.
    7. 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.
    8. Nofuentes, G. & García-Domingo, B. & Muñoz, J.V. & Chenlo, F., 2014. "Analysis of the dependence of the spectral factor of some PV technologies on the solar spectrum distribution," Applied Energy, Elsevier, vol. 113(C), pages 302-309.
    9. Durisch, Wilhelm & Lam, King-Hang & Close, Josie, 2006. "Efficiency and degradation of a copper indium diselenide photovoltaic module and yearly output at a sunny site in Jordan," Applied Energy, Elsevier, vol. 83(12), pages 1339-1350, December.
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    11. de la Parra, I. & Muñoz, M. & Lorenzo, E. & García, M. & Marcos, J. & Martínez-Moreno, F., 2017. "PV performance modelling: A review in the light of quality assurance for large PV plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 780-797.
    12. Rawat, Rahul & Singh, Ramayan & Sastry, O.S. & Kaushik, S.C., 2017. "Performance evaluation of micromorph based thin film photovoltaic modules in real operating conditions of composite climate," Energy, Elsevier, vol. 120(C), pages 537-548.
    13. Senturk, A. & Eke, R., 2017. "A new method to simulate photovoltaic performance of crystalline silicon photovoltaic modules based on datasheet values," Renewable Energy, Elsevier, vol. 103(C), pages 58-69.
    14. Gulkowski, Slawomir & Muñoz Diez, José Vicente & Aguilera Tejero, Jorge & Nofuentes, Gustavo, 2019. "Computational modeling and experimental analysis of heterojunction with intrinsic thin-layer photovoltaic module under different environmental conditions," Energy, Elsevier, vol. 172(C), pages 380-390.
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