Mathematical models of photovoltaic modules degradation in desert environment

M. Boussaid; A. Belghachi; K. Agroui; N.Djarfour; M. Boussaid; A. Belghachi; K. Agroui; N.Djarfour

doi:10.3934/energy.2019.2.127

AIMS Energy

2019, Volume 7, Issue 2: 127-140. doi: 10.3934/energy.2019.2.127

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Mathematical models of photovoltaic modules degradation in desert environment

1.
Laboratory of energy, environment and information systems (LEEIS), Department of material sciences, university of Ahmed Draia, street 11 December 1960, Adrar (01000), Algeria
2.
Laboratory of physics devices semiconductor (LPDS), department of physics, university of Bechar, PO Box 417 Bechar, Algeria
3.
Development unit of silicon technology, PB 3992 BD Dr. Frantz Fanon, Algiers, Algeria
4.
Department of hydrocarbons and renewable energies, university of Ahmed Draia, Street11 December 1960, Adrar (01000), Algeria

Received: 29 January 2019 Accepted: 14 March 2019 Published: 27 March 2019

The lifetime of a photovoltaic module operating in natural environment may never be known. It is useful to look for mathematical laws that are reliable in predicting the approximate warranty and performance times of these instruments before they fail. Literature is rich of many laws (parametric, semi-parametric or non-parametric) that have a high efficiency in all scientific branches. Parametric laws are used more than others in the branches of electronics. In this paper, we examined the validity of some reliability laws (15 models) to simulate the degradation of the maximum electrical power of crystalline silicon photovoltaic modules and to estimate their lifetimes when exposed to Saharan environments (especially the Sahara of Adrar in the South West of Algeria and the desert of California in the United States of America) where the climate is generally warm and dry during half a year. A genetic algorithm (a method of artificial intelligence) has been used here to calculate the parameters of each tested model. The modified Weibul model is the most adequate one compared to the other parametric models tested. In this study, the average lifespan of photovoltaic modules in the desert of California has been estimated to approximately 30 years (29 years for Adrar) for which the electrical energy supplied reaches 46% of its initial value. The prediction results must be taken into consideration for any construction study of a solar station in desert environments.
- degradation,
- module photovoltaic,
- Weibul modified model,
- desert environments,
- lifetimes,
- silicon crystalline
Citation: M. Boussaid, A. Belghachi, K. Agroui, N.Djarfour. Mathematical models of photovoltaic modules degradation in desert environment[J]. AIMS Energy, 2019, 7(2): 127-140. doi: 10.3934/energy.2019.2.127

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Abstract

The lifetime of a photovoltaic module operating in natural environment may never be known. It is useful to look for mathematical laws that are reliable in predicting the approximate warranty and performance times of these instruments before they fail. Literature is rich of many laws (parametric, semi-parametric or non-parametric) that have a high efficiency in all scientific branches. Parametric laws are used more than others in the branches of electronics. In this paper, we examined the validity of some reliability laws (15 models) to simulate the degradation of the maximum electrical power of crystalline silicon photovoltaic modules and to estimate their lifetimes when exposed to Saharan environments (especially the Sahara of Adrar in the South West of Algeria and the desert of California in the United States of America) where the climate is generally warm and dry during half a year. A genetic algorithm (a method of artificial intelligence) has been used here to calculate the parameters of each tested model. The modified Weibul model is the most adequate one compared to the other parametric models tested. In this study, the average lifespan of photovoltaic modules in the desert of California has been estimated to approximately 30 years (29 years for Adrar) for which the electrical energy supplied reaches 46% of its initial value. The prediction results must be taken into consideration for any construction study of a solar station in desert environments.

References

[1]	Laronde R, Charki A, Bigaud D (2010) Reliability of photovoltaic modules based on climatic measurement data. Int J Metrol Qual Eng 1: 45–49.
[2]	Boussaid M, Belghachi A, Agroui K (2018) Contribution to the degradation modeling of a polycrystalline photovoltaic cell under the effect of stochastic thermal cycles of a desert environment. Int J Control Energy Electr Eng 6: 66–72.
[3]	Polverini D, Field M, Dunlop E, et al. (2013) Polycrystalline silicon PV modules performance and degradation over 20 years. Progress Photovoltaic Res 21: 1004–1015.
[4]	Sample T, Pozza A (2013) 20-Year field exposed polycrystalline silicon PV modules: detailed visual inspection and analysis. European Commission, DG JRC, Institute for Energy and Transport, Ispra (VA), Italy.
[5]	Akhmad K, Kitamura A, Yamamoto F, et al. (1997) Outdoor performance of amorphous silicon and polycrystalline silicon PV modules. Sol Energy Mater Sol Cells 46: 209–218. doi: 10.1016/S0927-0248(97)00003-2
[6]	Ndiaye A, Kébé C, Kobi A, et al. (2014) Degradation evaluation of crystalline-silicon photovoltaic modules after a few operation years in a tropical environment. Sol Energy 103: 70–77. doi: 10.1016/j.solener.2014.02.006
[7]	Smith K (2016) Degradation effects in photovoltaic modules. ENG470 Engineering thesis, Murdoch University, Western Australia.
[8]	Quansah D, Adaramola M, Takyi G, et al. (2017) Reliability and degradation of solar PV modules-case study of 19-year-old polycrystalline modules in Ghana. Technologies 5: 22.
[9]	Köntges M, Kurtz S, Packard C, et al. (2014) Review of failures of photovoltaic modules. IEA PVPST asks 13 External final report IEA-PVPS, ISBN978-3-906042-16-9.
[10]	Sample T (2011) Failure modes and degradation rates from field-aged crystalline silicon modules. Institute for energy, ISPRA, Italy, NREL, Golden USA.
[11]	Kahoul N, Chenni R, Cheghib H, et al. (2017) Evaluating the reliability of crystalline silicon photovoltaic modules in harsh environment. Renewable Energy 109: 66–72. doi: 10.1016/j.renene.2017.02.078
[12]	Bandou F, Arab AH, Belkaïd MS, et al. (2015) Evaluation performance of photovoltaic modules after a long time operation in Saharan environment . Int J Hydrogen Energy 40: 13839–13848.
[13]	Boussaid M, Belghachi A, Agroui K, et al. (2016) Solar cell degradation under open circuit condition in out-doors-in desert region. Results Phys 6: 837–842. doi: 10.1016/j.rinp.2016.09.013
[14]	Fezzani A, Hadj Mahammed I, Said D, et al. (2017) Degradation and performance evaluation of PV module in desert climate conditions with estimate uncertainty in measuring. Serb J Electr Eng 14: 277–299. doi: 10.2298/SJEE1702277F
[15]	Laronde R, Charki A, Bigaud D (2012) Lifetime Estimation of a Photovoltaic Module Subjected to Corrosion Due to Damp Heat Testing. J Sol Energy Eng 135: 010–021.
[16]	Mani GT, Kuitche J (2013) Accelerated lifetime testing of photovoltaic modules. Photovoltaic Reliability Laboratory, Arizona State University. Available from: www.solarabcs.org/acceleratedtesting.
[17]	Sadok M, Benyoucef B, Mehdaoui A (2012) Performances et dégradation des modules PV en milieu saharien. Revue des Energies Renouvelables SIENR'12 Ghardaïa 2012: 203–212.
[18]	Agroui K (2010) Contribution au développement des techniques de contrôle de qualité des modules photovoltaïques de diverses technologies. Thèse, Université de Bechar, Algérie.
[19]	Melanie M (1999) An introduction to genetic algorithms.
[20]	Bodenhofer U (2004) Genetic Algorithms: Theory and Applications. Johannes Kepler University in Linz.
[21]	A Coley D (1998) An introduction to genetic algorithms for scientists and engineers. Singapore: World Scientific.
[22]	Carrion Garcia A (2015) Reliability modeling and prediction. The Research Center of Dependability and Quality Management, Polytechnic University of Valencia, Spain.
[23]	Ayyub B, Mccuen R. (1997) Probability, Statistics & Reliability for engineers. New York: CRC Press.
[24]	Rausand M (2004) System reliability theory: Models, statistical methods and applications. Technometrics 46: 495
[25]	Morice E (1966) Quelques modèles mathématiques de durée de vie. Revues de Statistique Appliquée 14: 45–126.
[26]	Saint Pierre P (2015) Introduction à l'analyse des durées de survie. Université Pierre et Marie Curie, France.

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