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High performance computing for the heliostat field layout evaluation

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Abstract

In Solar Central Receiver Systems (SCRS), the heliostat field is generally the most important subsystem in terms of initial investment and energy losses. Therefore, heliostat field layout needs to be carefully designed and optimized when deploying this kind of power facilities. This optimization procedure can be focused on multiple and heterogeneous criteria depending on particular factors that lead to define different optimization problems based on specific objective functions. However, objective functions defined for this problem are, in general terms, computationally very expensive. This fact may make an exhaustive optimization process infeasible, specially depending on the available resources, and forces particular simplifications at some steps of the process. Fortunately, some of the objective functions defined can benefit from parallelization, even though this idea is not usually pointed out or discussed, and then, become affordable in better conditions. In this paper, the heliostat field optical efficiency, which is a common objective function in this area, is analyzed to be parallelized by three different approaches.

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Notes

  1. PSA is the acronym for ‘Plataforma Solar de Almería’, a solar energy research center in Southern Spain.

References

  1. Behar O, Khellaf A, Mohammedi K (2013) A review of studies on central receiver solar thermal power plants. Renew Sustain Energy Rev 23:12–39

    Article  Google Scholar 

  2. Besarati S, Goswami D (2014) A computationally efficient method for the design of the heliostat field for solar power tower plant. Renew Energy 69:226–232

    Article  Google Scholar 

  3. Blanco-Muriel M, Alarcón-Padilla D, López-Moratalla T, Lara-Coira M (2001) Computing the solar vector. Solar Energy 70(5):431–441

    Article  Google Scholar 

  4. Camacho E, Berenguel M, Rubio F, Martínez D (2012) Control of solar energy systems. Springer, New York

    Book  Google Scholar 

  5. Carrizosa E, Domínguez-Bravo C, Fernández-Cara E, Quero M (2014) An optimization approach to the design of multi-size heliostat fields. Technical report IMUS

  6. Collado FJ, Gómez A, Turégano JA (1986) An analytic function for the flux density due to sunlight reflected from a heliostat. Solar Energy 37(3):215–234

  7. Collado FJ, Turégano JA (1989) Calculation of the annual thermal energy supplied by a defined heliostat field. Solar Energy 42(2):149–165

    Article  Google Scholar 

  8. Cristóbal A (2011) Diseño del campo de helióstatos para torres solares de receptor central. Degree Dissertation, Universidad Carlos III de Madrid, Spain

  9. Ewert M, Fuentes O (2015) Modelling and simulation of a solar tower power plant. Technical report MathCCES. http://www.mathcces.rwth-aachen.de/_media/5people/frank/solartower. Accessed on 21 December 2015

  10. Kolb G, Davenport R, Gorman D, Lumia R, Thomas R, Donnelly M (2007) Heliostat cost reduction. In: ASME 2007 Energy Sustainability Conference. American Society of Mechanical Engineers, pp 1077–1084

  11. Laue E (1970) The measurement of solar spectral irradiance at different terrestrial elevations. Solar Energy 13(1):43–57

    Article  Google Scholar 

  12. Mustafa M, Abdelhady S, Elweteedy A (2012) Analytical study of an innovated solar power tower (PS10) in Aswan. Int J Energy Eng 2(6):273–278

    Article  Google Scholar 

  13. Noone C, Torrilhon M, Mitsos A (2012) Heliostat field optimization: a new computationally efficient model and biomimetic layout. Solar Energy 86(2):792–803

    Article  Google Scholar 

  14. Ramos A, Ramos F (2012) Strategies in tower solar power plant optimization. Solar Energy 86(9):2536–2548

    Article  Google Scholar 

  15. Reddy V, Kaushik S, Ranjan K, Tyagi S (2013) State-of-the-art of solar thermal power plants—a review. Renew Sustain Energy Rev 27:258–273

    Article  Google Scholar 

  16. Redondo J, Fernandez J, Garcia I, Ortigosa P (2008) Parallel algorithms for continuous competitive location problems. Optim Methods Softw 23(5):779–791

    Article  MathSciNet  MATH  Google Scholar 

  17. Schwarzbzl P, Schmitz M, Pitz-Paal R (2009) Visual HFLCAL-A software tool for layout and optimization of heliostat fields. In: SolarPACES Conference. Berlin

  18. Stine W, Geyer M (2015) Power from the sun (2001) Public website. http://powerfromthesun.net/book.html. Accessed 21 December 2015

  19. Tan MH (2011) Design and optimization of heliostat field using spinning-elevation sun tracking method based on computational analysis Doctoral Dissertation. University Tunku Abdul Rahman

  20. Yao Z, Wang Z, Lu Z, Wei X (2009) Modeling and simulation of the pioneer 1 MW solar thermal central receiver system in China. Renew Energy 34(11):2437–2446

    Article  Google Scholar 

  21. Zhang H, Juchli I, Favrat D, Pelet X (2007) Multi-objective thermoeconomic optimisation of the design of heliostat field of solar tower power plants. In: Engineering for Sustainable Energy in Developing Countries. Rio de Janeiro

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Authors and Affiliations

  1. Agrifood Campus of International Excellence ceiA3, Department of Informatics, University of Almería, Almeria, Spain

    N. C. Cruz, J. L. Redondo, M. Berenguel, J. D. Álvarez, A. Becerra-Teron & P. M. Ortigosa

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  1. N. C. Cruz
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  2. J. L. Redondo
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  3. M. Berenguel
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  4. J. D. Álvarez
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  5. A. Becerra-Teron
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  6. P. M. Ortigosa
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Corresponding author

Correspondence to N. C. Cruz.

Additional information

This work has been funded by Grants from the Spanish Ministry of Economy and Competitiveness (TIN2012-37483-C03-03 and ENERPRO DPI 2014-56364-C2-1-R), Junta de Andalucía (P10-TIC-6002, P11-TIC7176 and P12-TIC301). Juana López Redondo and José Domingo Álvarez Hervás are fellows of the Spanish ‘Ramón y Cajal’ contract program, co-financed by the European Social Fund.

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Cruz, N.C., Redondo, J.L., Berenguel, M. et al. High performance computing for the heliostat field layout evaluation. J Supercomput 73, 259–276 (2017). https://doi.org/10.1007/s11227-016-1698-7

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  • DOI: https://doi.org/10.1007/s11227-016-1698-7

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