Silicon (BSFR) solar cell AC parameters at different temperatures

Kumar, Ranjeet; Suresh, S.; Nagaraju, J.

doi:10.1016/j.solmat.2004.05.017

Cited by 31 publications

(29 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the values of the C p and R p model parameters vary depending on factors such as illumination, temperature, and cell voltage bias [20], [21]. When the R p value changes, resistance changes are visualized as the resistive magnitude regions moving up or down directly with the resistance change.…”

Section: A Pv Cell Dynamic Modelmentioning

confidence: 99%

“…The R p value can be determined directly from the dc impedance, R p + R s , since it is assumed that R s is constant. Generally, temperature increase slightly lowers resistance due to a higher number of free carriers, and increasing illumination also lowers resistance slightly [21], [22]. An intuitive way to understand how the dc impedance and, in turn, R p change under various conditions is from the slope of the I-V curve.…”

Section: B Parallel Resistancementioning

confidence: 99%

“…Diffusion capacitance, C d , comes from the charge stored in the neutral region of the semiconductor outside the depletion region. The diffusion capacitance is prominent when the p-n junction is forward biased above the MPP voltage, where the junction carries significant current, but it is negligible when reverse biased [21]- [23]. Fig.…”

Section: Parallel Capacitancementioning

confidence: 99%

“…5 illustrates capacitance trends over cell voltage bias and identifies the region where each capacitance type dominates. Generally, PV capacitance tends to increase with voltage bias, increase with temperature, and increase with illumination [21], [22]. …”

Section: Parallel Capacitancementioning

confidence: 99%

See 3 more Smart Citations

Photovoltaic Hot-Spot Detection for Solar Panel Substrings Using AC Parameter Characterization

Kim

Seo

Cho

et al. 2016

IEEE Trans. Power Electron.

178

View full text Add to dashboard Cite

Hot spotting is a problem in photovoltaic (PV) systems that reduces panel power performance and accelerates cell degradation. In present day systems, bypass diodes are used to mitigate hot spotting, but it does not prevent hot spotting or the damage it causes. This paper presents an active hot spot detection method to detect hot spotting within a series of PV cells, using ac parameter characterization. A PV cell is comprised of series and parallel resistances and parallel capacitance, which are affected by voltage bias, illumination, and temperature. Experimental results have shown that when a PV string is under a maximum power point tracking control, hot spotting in a single cell results in a capacitance increase and dc impedance increase. The capacitance change is detectable by measuring the ac impedance magnitude in the 10-70 kHz frequency range. An impedance value change due to hot spotting can be detected by monitoring one high-frequency measurement in the capacitive region and one low-frequency measurement in the dc impedance region. Alternatively, the dc impedance can also be calculated using dc operating point measurements. The proposed hot spot detection method can be integrated into a dc-dc power converter that operates at the panel or subpanel level.

show abstract

Section: A Pv Cell Dynamic Modelmentioning

confidence: 99%

Section: B Parallel Resistancementioning

confidence: 99%

Section: Parallel Capacitancementioning

confidence: 99%

Section: Parallel Capacitancementioning

confidence: 99%

See 2 more Smart Citations

Photovoltaic Hot-Spot Detection for Solar Panel Substrings Using AC Parameter Characterization

Kim

Seo

Cho

et al. 2016

IEEE Trans. Power Electron.

178

View full text Add to dashboard Cite

show abstract

“…A diffusion and junction capacitance model for si solar cell is given in [124], where the cells are tested at different temperatures to find the junction temperature. Dynamic models with more than one dynamic parameter are presented in this method.…”

Section: Dynamic Modelsmentioning

confidence: 99%