Effects of Climatic Conditions on a Polycrystalline Photovoltaic Module in Niger

Ndiaye, Fatou; Sène, Moustapha; Beye, Modou; Maiga, Amadou Seidou

doi:10.18052/www.scipress.com/ilcpa.55.59

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…In modern fields, a multilayer perception network trained by a supervised learning backpropagation algorithm associated to Levenberg-Marquardt method minimizes the mean square error layer (Ndiaye et al, 2015). A hybrid model has been developed in order to calculate the maximum power considering the changing atmospheric climate.…”

Section: Hybrid Ann Modelmentioning

confidence: 99%

A comparative study of maximum power point tracker approaches based on artificial neural network and fuzzy controllers

Sene¹,

Ndiaye²,

Faye³

et al. 2018

Int. J. Phys. Sci.

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The performances of a photovoltaic (PV) module connected to a load through a conversion stage (chopper, inverter) are linked to the average electricity output including the delivered power. Nevertheless, the efficiency depends on atmospheric parameters as temperature, irradiance, and wind speed. To make electrical power available, Maximum Power Point Trackers (MPPT) algorithms are developed to keep up the PV module at optimal operating point with regard to climatic variations. This paper proposes an assessment of Artificial Neural Networks model based on MultiLayer Perceptron (MLP) and Radial Basis Function (RBF). A comparative study with an Adaptive Neuro-Fuzzy Inference System and a hybrid neural network RBF/MLP is done using measured data to optimize the maximum power point of a photovoltaic generator.

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Section: Hybrid Ann Modelmentioning

confidence: 99%

A comparative study of maximum power point tracker approaches based on artificial neural network and fuzzy controllers

Sene¹,

Ndiaye²,

Faye³

et al. 2018

Int. J. Phys. Sci.

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The effect of the recombination mechanisms location on the temperature sensitivity of thin-film photovoltaic cells

et al. 2019

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Thin film solar cells temperature sensitivity and impact of the main recombination mechanism location are investigated in this paper. The main mechanisms in bulk and at the heterojunction interface are discriminated. Using a 1D simulation software, “Solar Cell Capacitance Simulator” (SCAPS), we observed a higher temperature coefficient of open circuit voltage (Voc) for cells with main recombination centers at the interface than the one with main recombination centers in volume. Furthermore, an LTSpice module model is used to visualize the effects of the recombination centers' location on the performance ratios of the modules. The results show more degradation for the ratios performance of cells with the main recombination mechanisms at the interface than those in volume.

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A performance model using an analytical-numerical method and artificial neural networks for a PV plant output forecast

Tevi¹,

Diouf²,

Kata³

et al. 2021

2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)

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Effects of Climatic Conditions on a Polycrystalline Photovoltaic Module in Niger

Cited by 3 publications

References 6 publications

A comparative study of maximum power point tracker approaches based on artificial neural network and fuzzy controllers

A comparative study of maximum power point tracker approaches based on artificial neural network and fuzzy controllers

The effect of the recombination mechanisms location on the temperature sensitivity of thin-film photovoltaic cells

A performance model using an analytical-numerical method and artificial neural networks for a PV plant output forecast

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