Bypass diode effect and photovoltaic parameter estimation under partial shading using a hill climbing neural network algorithm

Bypass diode effect and photovoltaic parameter estimation under partial shading using a hill climbing neural network algorithm

In recent decades, population growth and industrial evolution have led to a significant increase in the need to produce electricity. Photovoltaic energy has assumed a key role in responding to this need, mainly due to its low cost and reduced environmental impact. Therefore, predicting and controlli...

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Bibliographic Details
Main Authors: H. G. G. Nunes, F. A. L. Morais, J. A. N. Pombo, S. J. P. S. Mariano, M. R. A. Calado
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Energy Research
Subjects:
hill climbing neural network algorithm
parameter estimation
single-diode model
double-diode model
bypass diode
partial shading condition
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2022.837540/full

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https://www.frontiersin.org/articles/10.3389/fenrg.2022.837540/full

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