Valentín Cardeñoso Payo

Prof. Dr. Valentín Cardeñoso Payo

ECA-SIMM research group—Universidad de Valladolid, Valladolid, Spain
orcid

Research Focus & Metrics

Academic Career Length

41Years (1986-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2003 in Spectrochimica Acta Part B: Atomic Spectroscopy
Verified
Journal Article
Closed access
MGMarco Antonio Gigosos
Marco Antonio Gigosos
Manuel A. GonzalezManuel A. Gonzalez
Manuel A. Gonzalez
Valentín Cardeñoso PayoValentín Cardeñoso Payo
Valentín Cardeñoso Payo

28 October 1996 in Journal of Physics B: Atomic, Molecular and Optical Physics
Verified
Journal Article
Closed access
PDF file
MGMarco Antonio Gigosos
Marco Antonio Gigosos
Valentín Cardeñoso PayoValentín Cardeñoso Payo
Valentín Cardeñoso Payo

25 February 2009 in Pattern Analysis and Applications
Verified
Journal Article
Closed access
PDF file
Julian FierrezJulian Fierrez
Julian Fierrez
Javier GalballyJavier Galbally
Javier Galbally
JOJ. Ortega-Garcia
J. Ortega-Garcia
MFM. R. Freire
M. R. Freire
FAFernando Alonso-Fernandez
Fernando Alonso-Fernandez
JGJ. J. Gracia-Roche
J. J. Gracia-Roche

1 March 2012 in Pattern Recognition
Verified
Journal Article
Closed access
NHN. Houmani
N. Houmani
AMA. Mayoue
A. Mayoue
SGS. Garcia-Salicetti
S. Garcia-Salicetti
BDB. Dorizzi
B. Dorizzi
MKM.I. Khalil
M.I. Khalil
CVCarlos Vivaracho-Pascual
Carlos Vivaracho-Pascual

6 October 2022 in Applied Sciences
Verified
Journal Article
Open access
PDF file
HRHéctor Felipe Mateo Romero
Héctor Felipe Mateo Romero
Manuel A. GonzalezManuel A. Gonzalez
Manuel A. Gonzalez
Valentín Cardeñoso PayoValentín Cardeñoso Payo
Valentín Cardeñoso Payo
Víctor Alonso GómezVíctor Alonso Gómez
Víctor Alonso Gómez
APAlberto Redondo Plaza
Alberto Redondo Plaza
Luis Hernández-CallejoLuis Hernández-Callejo
Luis Hernández-Callejo
This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training. Research is still being conducted in order to solve these problems and find techniques with better performance. This article analyzes the most relevant scientific works that use artificial intelligence to deal with the key PV problems by searching terms related with artificial intelligence and photovoltaic systems in the most important academic research databases. The number of publications shows that this field is of great interest to researchers. The findings also show that these kinds of algorithms really have helped to solve these issues or to improve the previous solutions in terms of efficiency or accuracy.

28 November 1987 in Journal of Physics B: Atomic and Molecular Physics
Verified
Journal Article
Closed access
PDF file
MGMarco Antonio Gigosos
Marco Antonio Gigosos
Valentín Cardeñoso PayoValentín Cardeñoso Payo
Valentín Cardeñoso Payo