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An automated high-granularity tool for a fast evaluation of the yield of PV plants accounting for shading effects

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  • d'Alessandro, Vincenzo
  • Di Napoli, Fabio
  • Guerriero, Pierluigi
  • Daliento, Santolo

Abstract

In this paper, an automated tool for the evaluation of I–V characteristics and energy yield of photovoltaic (PV) plants is proposed. The tool translates an AutoCAD drawing of the plant and surrounding obstacles into an in-house Matlab code that automatically generates an equivalent circuit representing the system, which is in turn solved by PSPICE. The plant is described at a high-granularity single-cell level, so that also the non-intuitive influence of small-area shadows can be accurately predicted. Nevertheless, the robust PSPICE engine ensures short simulation times.

Suggested Citation

  • d'Alessandro, Vincenzo & Di Napoli, Fabio & Guerriero, Pierluigi & Daliento, Santolo, 2015. "An automated high-granularity tool for a fast evaluation of the yield of PV plants accounting for shading effects," Renewable Energy, Elsevier, vol. 83(C), pages 294-304.
    • Handle: RePEc:eee:renene:v:83:y:2015:i:c:p:294-304
    DOI: 10.1016/j.renene.2015.04.041
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    References listed on IDEAS

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    Cited by:

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    3. Alfredo Nespoli & Emanuele Ogliari & Sonia Leva & Alessandro Massi Pavan & Adel Mellit & Vanni Lughi & Alberto Dolara, 2019. "Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques," Energies, MDPI, vol. 12(9), pages 1-15, April.
    4. Rico Espinosa, Alejandro & Bressan, Michael & Giraldo, Luis Felipe, 2020. "Failure signature classification in solar photovoltaic plants using RGB images and convolutional neural networks," Renewable Energy, Elsevier, vol. 162(C), pages 249-256.
    5. Bressan, M. & Gutierrez, A. & Garcia Gutierrez, L. & Alonso, C., 2018. "Development of a real-time hot-spot prevention using an emulator of partially shaded PV systems," Renewable Energy, Elsevier, vol. 127(C), pages 334-343.
    6. Rehman, Naveed ur & Uzair, Muhammad, 2020. "Optimizing the inclined field for solar photovoltaic arrays," Renewable Energy, Elsevier, vol. 153(C), pages 280-289.
    7. Arias-Rosales, Andrés & LeDuc, Philip R., 2020. "Comparing View Factor modeling frameworks for the estimation of incident solar energy," Applied Energy, Elsevier, vol. 277(C).
    8. Gonçalves, Juliana E. & van Hooff, Twan & Saelens, Dirk, 2021. "Simulating building integrated photovoltaic facades: Comparison to experimental data and evaluation of modelling complexity," Applied Energy, Elsevier, vol. 281(C).
    9. Rehman, Naveed ur & Uzair, Muhammad & Allauddin, Usman, 2020. "An optical-energy model for optimizing the geometrical layout of solar photovoltaic arrays in a constrained field," Renewable Energy, Elsevier, vol. 149(C), pages 55-65.
    10. Alonso Gutiérrez Galeano & Michael Bressan & Fernando Jiménez Vargas & Corinne Alonso, 2018. "Shading Ratio Impact on Photovoltaic Modules and Correlation with Shading Patterns," Energies, MDPI, vol. 11(4), pages 1-26, April.

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