Abstract
To achieve a high performance in sub-module power conditioning circuits, it is important that power converters are designed in accordance with the photovoltaic (PV) cell impedance at the input. Taking this one step further, exploiting the impedance of cell strings could even support novel power conditioning approaches in PV modules. In this work, we characterize the impedance of eight single-cell laminates based on different industrial c-Si PV cell architectures. This characterization is carried out by impedance spectroscopy in dark conditions at room temperature, and the capacitive and inductive effects are evaluated through equivalent model fitting. By comparing the results for the different laminates, it is revealed how the cell design affects its impedance. Our experiments show that the PN junction capacitance at maximum power point varies for the different cells between 0.30 and 45.6 μF/cm2. The two main factors contributing to a high PV cell capacitance at maximum power point are (i) a low wafer dopant concentration and (ii) a high maximum power point voltage. In high-efficiency c-Si PV cells that will be fabricated in the coming years, increasing capacitances are expected for operation near the maximum power point. Furthermore, the single-cell laminates exhibit inductances between 63 and 130 nH, and our results indicate that the inductance is mostly affected by the number of busbars and the geometry of the metal contacts.
Original language | English |
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Article number | 112486 |
Journal | Solar Energy Materials and Solar Cells |
Volume | 260 |
DOIs | |
Publication status | Published - 2023 |
Keywords
- Capacitance
- Crystalline silicon
- Impedance spectroscopy
- Inductance
- Partial shading
- Photovoltaics
- Photovoltatronics
- Shading tolerance
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Data underlying the publication: Revealing capacitive and inductive effects in modern industrial c-Si photovoltaic cells through impedance spectroscopy
van Nijen, D. A. (Creator), Muttillo, M. (Creator), Van Dyck, R. I. K. (Creator), Zeman, M. (Creator), Isabella, O. (Creator), Manganiello, P. (Creator) & Poortmans, J. (Creator), TU Delft - 4TU.ResearchData, 14 Oct 2023
DOI: 10.4121/0C9538D5-5930-4AE5-A3C7-0A8DBE4B94F5
Dataset/Software: Dataset