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Solar Cell Capacitance Determination Based on an RLC Resonant Circuit

Author

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  • Petru Adrian Cotfas

    (Department of Electronics and Computers, Transilvania University of Brasov, Eroilor 29, 500036 Brasov, Romania)

  • Daniel Tudor Cotfas

    (Department of Electronics and Computers, Transilvania University of Brasov, Eroilor 29, 500036 Brasov, Romania)

  • Paul Nicolae Borza

    (Department of Electronics and Computers, Transilvania University of Brasov, Eroilor 29, 500036 Brasov, Romania)

  • Dezso Sera

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 101, DK-9220 Aalborg, Denmark)

  • Remus Teodorescu

    (Department of Energy Technology, Aalborg University, Pontoppidanstraede 101, DK-9220 Aalborg, Denmark)

Abstract

The capacitance is one of the key dynamic parameters of solar cells, which can provide essential information regarding the quality and health state of the cell. However, the measurement of this parameter is not a trivial task, as it typically requires high accuracy instruments using, e.g., electrical impedance spectroscopy (IS). This paper introduces a simple and effective method to determine the electric capacitance of the solar cells. An RLC (Resistor Inductance Capacitor) circuit is formed by using an inductor as a load for the solar cell. The capacitance of the solar cell is found by measuring the frequency of the damped oscillation that occurs at the moment of connecting the inductor to the solar cell. The study is performed through simulation based on National Instruments (NI) Multisim application as SPICE simulation software and through experimental capacitance measurements of a monocrystalline silicon commercial solar cell and a photovoltaic panel using the proposed method. The results were validated using impedance spectroscopy. The differences between the capacitance values obtained by the two methods are of 1% for the solar cells and of 9.6% for the PV panel. The irradiance level effect upon the solar cell capacitance was studied obtaining an increase in the capacitance in function of the irradiance. By connecting different inductors to the solar cell, the frequency effect upon the solar cell capacitance was studied noticing a very small decrease in the capacitance with the frequency. Additionally, the temperature effect over the solar cell capacitance was studied achieving an increase in capacitance with temperature.

Suggested Citation

  • Petru Adrian Cotfas & Daniel Tudor Cotfas & Paul Nicolae Borza & Dezso Sera & Remus Teodorescu, 2018. "Solar Cell Capacitance Determination Based on an RLC Resonant Circuit," Energies, MDPI, vol. 11(3), pages 1-13, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:672-:d:136591
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    References listed on IDEAS

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    1. Cotfas, D.T. & Cotfas, P.A. & Kaplanis, S., 2016. "Methods and techniques to determine the dynamic parameters of solar cells: Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 213-221.
    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. Javier Cubas & Santiago Pindado & Carlos De Manuel, 2014. "Explicit Expressions for Solar Panel Equivalent Circuit Parameters Based on Analytical Formulation and the Lambert W-Function," Energies, MDPI, vol. 7(7), pages 1-18, June.
    4. Gude, Veera Gnaneswar & Nirmalakhandan, Nagamany & Deng, Shuguang, 2011. "Desalination using solar energy: Towards sustainability," Energy, Elsevier, vol. 36(1), pages 78-85.
    5. Das, Narottam & Wongsodihardjo, Hendy & Islam, Syed, 2015. "Modeling of multi-junction photovoltaic cell using MATLAB/Simulink to improve the conversion efficiency," Renewable Energy, Elsevier, vol. 74(C), pages 917-924.
    6. Yadav, Pankaj & Pandey, Kavita & Bhatt, Vishwa & Kumar, Manoj & Kim, Joondong, 2017. "Critical aspects of impedance spectroscopy in silicon solar cell characterization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1562-1578.
    7. Muhammad Ali Mughal & Qishuang Ma & Chunyan Xiao, 2017. "Photovoltaic Cell Parameter Estimation Using Hybrid Particle Swarm Optimization and Simulated Annealing," Energies, MDPI, vol. 10(8), pages 1-14, August.
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    Cited by:

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