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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2016: Hybrid Artificial Intelligent Systems pp 273–282Cite as

Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9648))

Abstract

The Concentrating Photovoltaic technology is focused on the generation of electricity reducing the associated costs. The main characteristics is to concentrate the sunlight in solar cells by means of optical device such as plastic or glass material. This technology could contribute with several benefits to our environmental. This paper presents a new study of the Concentrating Photovoltaic technology with the analysis of the solar spectrum considering the impact of the direct normal irrandiance spectral distribution. In this way, a estimation of regression coefficients for the spectral matching ratio multivariable regression and the average photon energy multivarible regression are obtained through a differential evolution approach. The accurate calculation of the model parameters reveals relations among the atmospheric conditions very useful for the experts.

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References

  1. Almonacid, F., Pérez-Higueras, P., Fernández, E., Rodrigo, P.: Relation between the cell temperature of a hcpv module and atmospheric parameters. Solar Energy Mater. Solar Cells 105, 322–327 (2012)

    Article  Google Scholar 

  2. Antón, I., Martínez, M., Rubio, F., Núñez, R., Herrero, R., Domínguez, C., Victoria, M., Askins, S., Sala, G.: Power rating of cpv systems based on spectrally corrected dni, vol. 1477, pp. 331–335 (2012)

    Google Scholar 

  3. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Chapman & Hall, New York (1984)

    MATH  Google Scholar 

  4. Castro, M., Domínguez, C., Núez, R., Antón, I., Sala, G., Araki, K.: Detailed effects of wind on the field performance of a 50 kw cpv demonstration plant. In: AIP Conference Proceedings, vol. 1556, pp. 256–260 (2013)

    Google Scholar 

  5. Chan, N., Brindley, H., Ekins-Daukes, N.: Impact of individual atmospheric parameters on cpv system power, energy yield and cost of energy. Prog. Photovoltaics 22, 1080–1095 (2014)

    Article  Google Scholar 

  6. C. Domínguez, I. Askins, S. Antón, and G. Sala. Indoor characterization of cpv modules using helios 3198 solar simulator. In: 24th European Photovoltaic Solar Energy Conference and Exhibition, pp. 165–169 (2009)

    Google Scholar 

  7. Fan, R., Chen, P., Lin, C.: Working set selection using the second order information for training svm. J. Mach. Learn. Res. 6, 1889–1918 (2005)

    MathSciNet  MATH  Google Scholar 

  8. Flury, B., Riedwyl, H.: Multiple linear regression. In: Multivariate Statistics, pp. 54–74 (1988)

    Google Scholar 

  9. Gupta, R.: CPV: expansion and bankability required. Renew. Energy focus 14(4), 12–13 (2013)

    Article  Google Scholar 

  10. Helmers, H., Schachtner, M., Bett, A.: Influence of temperature and irradiance on triple-junction solar subcells. Solar Energy Mater. Solar Cells 116, 144–152 (2013)

    Article  Google Scholar 

  11. Herrero, R., Victoria, M., Domínguez, C., Askins, S., Antón, I., Sala, G.: Concentration photovoltaic optical system irradiance distribution measurements and its effect on multi-junction solar cells. Prog. Photovoltaics Res. Appl. 20(4), 423–430 (2012)

    Article  Google Scholar 

  12. Kinsey, G., Hebert, P., Barbour, K., Krut, D., Cotal, H., Sherif, R.: Concentrator multijunction solar cell characteristics under variable intensity and temperature. Prog. Photovoltaics Res. Appl. 16(6), 503–508 (2008)

    Article  Google Scholar 

  13. Law, D., King, R., Yoon, H., Archer, M., Boca, A., Fetzer, C., Mesropian, S., Isshiki, T., Haddad, M., Edmondson, K., Bhusari, D., Yen, J., Sherif, R., Atwater, H., Karam, N.: Future technology pathways of terrestrial iii-v multijunction solar cells for concentrator photovoltaic systems. Solar Energy Mater. Solar Cells 94(8), 1314–1318 (2010)

    Article  Google Scholar 

  14. Leloux, J., Lorenzo, E., Garca-Domingo, B., Gueymard, J.A.C.: A bankable method of assessing the performance of a cpv plant. Appl. Energy 118(C), 1–11 (2014)

    Article  Google Scholar 

  15. Lin, C.-K., Fang, J.-Y.: Analysis of structural deformation and concentrator misalignment in a roll-tilt solar tracker. In: AIP Conference Proceedings, vol. 1556, pp. 210–213 (2013)

    Google Scholar 

  16. Luque, A., Sala, G., Luque-Heredia, I.: Photovoltaic concentration at the onset of its commercial deployment. Prog. Photovoltaics Res. Appl. 14(5), 413–428 (2006)

    Article  Google Scholar 

  17. Minemoto, T., Nakada, Y., Takahashi, H., Takakura, H.: Uniqueness verification of solar spectrum index of average photon energy for evaluating outdoor performance of photovoltaic modules. Solar Energy 83(8), 1294–1299 (2009)

    Article  Google Scholar 

  18. Moller, M.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw. 6(4), 525–533 (1993)

    Article  Google Scholar 

  19. Nishioka, K., Takamoto, T., Agui, T., Kaneiwa, M., Uraoka, Y., Fuyuki, T.: Annual output estimation of concentrator photovoltaic systems using high-efficiency ingap/ingaas/ge triple-junction solar cells based on experimental solar cell’s characteristics and field-test meteorological data. Solar Energy Mater. Solar Cells 90(1), 57–67 (2006)

    Article  Google Scholar 

  20. Nofuentes, G., García-Domingo, B., Muoz, J., Chenlo, F.: Analysis of the dependence of the spectral factor of some pv technologies on the solar spectrum distribution. Appl. Energy 113, 302–309 (2014)

    Article  Google Scholar 

  21. Peharz, G., Ferrer Rodríguez, J., Siefer, G., Bett, A.: Investigations on the temperature dependence of cpv modules equipped with triple-junction solar cells. Prog. Photovoltaics Res. Appl. 19(1), 54–60 (2011)

    Article  Google Scholar 

  22. Rodrigo, P., Fernández, E., Almonacid, F., Pérez-Higueras, P.: Models for the electrical characterization of high concentration photovoltaic cells and modules: a review. Renew. Sustain. Energy Rev. 26, 752–760 (2013)

    Article  Google Scholar 

  23. Siefer, G., Bett, A.: Analysis of temperature coefficients for III-V multi-junction concentrator cells. Prog. Photovoltaics Res. Appl. 22(5), 515–524 (2014)

    Article  Google Scholar 

  24. Storn, R., Price, K.: Differential evolution: a simple and efficient adaptive scheme forglobal optimization over continuous spaces.Technical report TR-95-012 (1995)

    Google Scholar 

  25. Wang, L.X., Mendel, J.M.: Generating fuzzy rules by learning from examples. IEEE Trans. Syst. Man Cybern. 22(6), 1414–1427 (1992)

    Article  MathSciNet  Google Scholar 

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Acknowledgments

This work was supported by the Spanish Science and Innovation Department under project ENE2009-08302, by the Department of Science and Innovation of the Regional Government of Andalucia under project P09-TEP-5045, and by Spanish Ministry of Economy and Competitiveness under project TIN2015-68454-R (FEDER Founds).

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Authors and Affiliations

  1. Department of Civil Engineering, University of Burgos, 09006, Burgos, Spain

    Cristobal J. Carmona

  2. Department of Computer Science, University of Jaén, 23071, Jaén, Spain

    F. Pulgar, Antonio Jesús Rivera-Rivas & Maria Jose del Jesus

  3. Department of Electronics and Automatization Engineering, University of Jaén, 23071, Jaén, Spain

    J. Aguilera

Authors
  1. Cristobal J. Carmona
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  2. F. Pulgar
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  3. Antonio Jesús Rivera-Rivas
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  4. Maria Jose del Jesus
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  5. J. Aguilera
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Corresponding author

Correspondence to Cristobal J. Carmona .

Editor information

Editors and Affiliations

  1. Universidad Pablo de Olavide, Sevilla, Spain

    Francisco Martínez-Álvarez

  2. Universidad Pablo de Olavide, Sevilla, Spain

    Alicia Troncoso

  3. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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© 2016 Springer International Publishing Switzerland

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Carmona, C.J., Pulgar, F., Rivera-Rivas, A.J., del Jesus, M.J., Aguilera, J. (2016). Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach. In: Martínez-Álvarez, F., Troncoso, A., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2016. Lecture Notes in Computer Science(), vol 9648. Springer, Cham. https://doi.org/10.1007/978-3-319-32034-2_23

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  • DOI: https://doi.org/10.1007/978-3-319-32034-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32033-5

  • Online ISBN: 978-3-319-32034-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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