Series Resistance Both Temperature and Wavelength Dependent in Silicon Solar Cell under Steady State

Diatta, Ibrahima; Ly, I.; Diouf, Marcel Sitor; Traore, Youssou; Ndiaye, Mor; Mbodji, Senghane; Sissoko, G.

doi:10.23956/ijermt/v6n1/101

Cited by 2 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The performance of a PV cell is related to internal factors (temperature of the base, recombination, grains sizes ...) and external factors (electric field, magnetic field …) given by Pelanchon et al [1], Zoungrana et al [2], Soika et al [3]. Many studies of illumination, temperature, grains recombination boundaries effects on solar cell have been made by Gupta et al [4], Miyakawa [5], Diatta [6], Agroui [7], O'Donnell [8], Soro et al [9]. Some studies have also been carried out on 3D modelling by Soro et al [9], Samb et al [10], Mane et al [12], Dugas [13].…”

Section: Introductionmentioning

confidence: 99%

“…The results of these studies have shown that increasing the intensity of illumination increases the performance of solar cells. Also, the influence of temperature on the performances of a PV cell has already made the topic of numerous studies such as the study of the influence of the temperature on: the density of charge carriers done by Diatta [6]; the photocurrent and photovoltage done by Agroui [7], Essalam et al [15], Merahi et al [16]; the electric power done by Agroui [7], Merahi et al [16], Belhadj et al [17]. It should be noted that all these studies were made with monofacial or bifacial monocrystalline, polycrystalline and multicrystalline silicon solar cells or InGaAs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

3-d modelling of electrical parameters’ effects on the heating of the base of an intense light illuminated polycrystalline silicon PV cell

Soro¹,

Savadogo²,

Zouma³

et al. 2021

J. Fundam and Appl Sci.

View full text Add to dashboard Cite

Performances of a solar cell are significantly influenced by the heating of the base. Two phenomena contribute to the heating of the base of a PV cell: the heat due to the transfer by conduction of the solar energy radiation received by the surface of the PV cell and the heat generated inside the solar cell by various phenomena related to the movement of photogenerated electrons and holes. Thus, even if the increase of the quantity of carriers leads to improve the PV cell electrical parameters, this phenomenon also leads to the increase of some internal phenomena like thermalization, carriers braking and the carriers collisions which are sources of heating of the base of the solar cell Indeed, electrical parameters (photocurrent, photovoltage, electric power) are physical quantities related to the movement of charge carriers and also to the illumination mode, this means that changing of electrical parameters during the operation of the PV cell leads to a variation of the temperature inside the base of the PV cell. This work presents the effects of the increase of some electrical parameters (photocurrent, photovoltage, electric power) on the behaviour of the temperature of the base of a silicon PV cell under intense light illumination.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

3-d modelling of electrical parameters’ effects on the heating of the base of an intense light illuminated polycrystalline silicon PV cell

Soro¹,

Savadogo²,

Zouma³

et al. 2021

J. Fundam and Appl Sci.

View full text Add to dashboard Cite

show abstract

Unsupervised Classification of Water Quality Using Artificial Intelligence: The Case of the Moulouya Wadi's Surface Waters (NE, Morocco)

Manssouri¹,

Manssouri

Hmaidi

et al. 2023

JERA

View full text Add to dashboard Cite

Due to its cruciality, water requires a high care to its physicochemical and microbiological properties to ensure the quality of several utilizations. The particles it carries are likely to be ingested, breathed, or come into contact with the skin. For the classification of the quality of surface water in the Moulouya River (NE, Morocco), this study presents many unsupervised classification methods. The overall quality of surface water in the Moulouya River in northeast Morocco was assessed using nine physicochemical parameters (pH, T°C, EC, O2-diss, NH4+, NO3-, SO42-, PO43-, and biological oxygen demand after 5 days (BOD5)) from March to August 2014. Over a 600-kilometer stretch, twenty-two sites were examined, from the river's source in the High Atlas to its mouth in the Mediterranean. During the first stage, three quality classes (excellent, good and poor) were defined by the calculation of the water quality index (WQI) and water quality evaluation system (QES-Water). In the second stage, the K-means algorithm, the fuzzy C-means algorithm and the self-organizing maps (SOM) of Kohonen were applied to the nine physicochemical parameters used as input variables for the model. The classification method used is capable of projecting high-dimensional data into a lower dimension, typically 2D. This nonlinear projection can be useful in classes’ analysis and their discovery. In terms of performance, the SOM classification showed very close results compared to the K-means and the fuzzy C-means algorithms, with only an insignificant difference across the three models, with SOM maps having a slight advantage.

show abstract

Series Resistance Both Temperature and Wavelength Dependent in Silicon Solar Cell under Steady State

Cited by 2 publications

References 8 publications

3-d modelling of electrical parameters’ effects on the heating of the base of an intense light illuminated polycrystalline silicon PV cell

3-d modelling of electrical parameters’ effects on the heating of the base of an intense light illuminated polycrystalline silicon PV cell

Unsupervised Classification of Water Quality Using Artificial Intelligence: The Case of the Moulouya Wadi's Surface Waters (NE, Morocco)

Contact Info

Product

Resources

About