IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i5p730-d99281.html
   My bibliography  Save this article

A New Methodology for Building-Up a Robust Model for Heliostat Field Flux Characterization

Author

Listed:
  • Nicolás C. Cruz

    (Department of Informatics, Agrifood Campus of International Excellence-Center for Research in Solar Energy (ceiA3-CIESOL), University of Almería, Sacramento Road s/n, La Cañada, 04120 Almería, Spain)

  • José D. Álvarez

    (Department of Informatics, Agrifood Campus of International Excellence-Center for Research in Solar Energy (ceiA3-CIESOL), University of Almería, Sacramento Road s/n, La Cañada, 04120 Almería, Spain)

  • Juana L. Redondo

    (Department of Informatics, Agrifood Campus of International Excellence-Center for Research in Solar Energy (ceiA3-CIESOL), University of Almería, Sacramento Road s/n, La Cañada, 04120 Almería, Spain)

  • Jesús Fernández-Reche

    (Solar Platform of Almería-Center for Research in Energy, Environment and Technology (CIEMAT), P.O. Box 22, Tabernas, Almería E-04200, Spain)

  • Manuel Berenguel

    (Department of Informatics, Agrifood Campus of International Excellence-Center for Research in Solar Energy (ceiA3-CIESOL), University of Almería, Sacramento Road s/n, La Cañada, 04120 Almería, Spain)

  • Rafael Monterreal

    (Solar Platform of Almería-Center for Research in Energy, Environment and Technology (CIEMAT), P.O. Box 22, Tabernas, Almería E-04200, Spain)

  • Pilar M. Ortigosa

    (Department of Informatics, Agrifood Campus of International Excellence-Center for Research in Solar Energy (ceiA3-CIESOL), University of Almería, Sacramento Road s/n, La Cañada, 04120 Almería, Spain)

Abstract

The heliostat field of solar central receiver systems (SCRS) is formed by hundreds, even thousands, of working heliostats. Their adequate configuration and control define a currently active research line. For instance, automatic aiming methodologies of existing heliostat fields are being widely studied. In general, control techniques require a model of the system to be controlled in order to obtain an estimation of its states. However, this kind of information may not be available or may be hard to obtain for every plant to be studied. In this work, an innovative methodology for data-based analytical heliostat field characterization is proposed and described. It formalizes the way in which the behavior of a whole field can be derived from the study of its more descriptive parts. By successfully applying this procedure, the instantaneous behavior of a field could be expressed by a reduced set of expressions that can be seen as a field descriptor. It is not intended to replace real experimentation but to enhance researchers’ autonomy to build their own reliable and portable synthetic datasets at preliminary stages of their work. The methodology proposed in this paper is successfully applied to a virtual field. Only 30 heliostats out of 541 were studied to characterize the whole field. For the validation set, the average difference in power between the flux maps directly fitted from the measured information and the estimated ones is only of 0.67% (just 0.10946 kW/m 2 of root-mean-square error, on average, between them). According to these results, a consistent field descriptor can be built by applying the proposed methodology, which is hence ready for use.

Suggested Citation

  • Nicolás C. Cruz & José D. Álvarez & Juana L. Redondo & Jesús Fernández-Reche & Manuel Berenguel & Rafael Monterreal & Pilar M. Ortigosa, 2017. "A New Methodology for Building-Up a Robust Model for Heliostat Field Flux Characterization," Energies, MDPI, vol. 10(5), pages 1-17, May.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:730-:d:99281
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/5/730/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/5/730/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khan, Jibran & Arsalan, Mudassar H., 2016. "Solar power technologies for sustainable electricity generation – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 414-425.
    2. Piroozmand, Pasha & Boroushaki, Mehrdad, 2016. "A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions," Energy, Elsevier, vol. 106(C), pages 240-252.
    3. Spiros Alexopoulos & Bernhard Hoffschmidt, 2017. "Advances in solar tower technology," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 6(1), January.
    4. Zhang, Maolong & Yang, Lijun & Xu, Chao & Du, Xiaoze, 2016. "An efficient code to optimize the heliostat field and comparisons between the biomimetic spiral and staggered layout," Renewable Energy, Elsevier, vol. 87(P1), pages 720-730.
    5. Behar, Omar & Khellaf, Abdallah & Mohammedi, Kamal, 2013. "A review of studies on central receiver solar thermal power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 12-39.
    6. Collado, Francisco J. & Guallar, Jesús, 2013. "A review of optimized design layouts for solar power tower plants with campo code," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 142-154.
    7. Siala, F.M.F & Elayeb, M.E, 2001. "Mathematical formulation of a graphical method for a no-blocking heliostat field layout," Renewable Energy, Elsevier, vol. 23(1), pages 77-92.
    8. Collado, Francisco J. & Guallar, Jesús, 2012. "Campo: Generation of regular heliostat fields," Renewable Energy, Elsevier, vol. 46(C), pages 49-59.
    9. Zhang, H.L. & Baeyens, J. & Degrève, J. & Cacères, G., 2013. "Concentrated solar power plants: Review and design methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 466-481.
    10. Ellabban, Omar & Abu-Rub, Haitham & Blaabjerg, Frede, 2014. "Renewable energy resources: Current status, future prospects and their enabling technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 748-764.
    11. Avila-Marin, Antonio L. & Fernandez-Reche, Jesus & Tellez, Felix M., 2013. "Evaluation of the potential of central receiver solar power plants: Configuration, optimization and trends," Applied Energy, Elsevier, vol. 112(C), pages 274-288.
    12. Besarati, Saeb M. & Yogi Goswami, D., 2014. "A computationally efficient method for the design of the heliostat field for solar power tower plant," Renewable Energy, Elsevier, vol. 69(C), pages 226-232.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cruz, N.C. & Redondo, J.L. & Berenguel, M. & Álvarez, J.D. & Ortigosa, P.M., 2017. "Review of software for optical analyzing and optimizing heliostat fields," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1001-1018.
    2. Zaharaddeen Ali Hussaini & Peter King & Chris Sansom, 2020. "Numerical Simulation and Design of Multi-Tower Concentrated Solar Power Fields," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    3. Saghafifar, Mohammad & Gadalla, Mohamed & Mohammadi, Kasra, 2019. "Thermo-economic analysis and optimization of heliostat fields using AINEH code: Analysis of implementation of non-equal heliostats (AINEH)," Renewable Energy, Elsevier, vol. 135(C), pages 920-935.
    4. Cruz, N.C. & Salhi, S. & Redondo, J.L. & Álvarez, J.D. & Berenguel, M. & Ortigosa, P.M., 2018. "Hector, a new methodology for continuous and pattern-free heliostat field optimization," Applied Energy, Elsevier, vol. 225(C), pages 1123-1131.
    5. Wang, Jianxing & Duan, Liqiang & Yang, Yongping, 2018. "An improvement crossover operation method in genetic algorithm and spatial optimization of heliostat field," Energy, Elsevier, vol. 155(C), pages 15-28.
    6. Piroozmand, Pasha & Boroushaki, Mehrdad, 2016. "A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions," Energy, Elsevier, vol. 106(C), pages 240-252.
    7. Merchán, R.P. & Santos, M.J. & Medina, A. & Calvo Hernández, A., 2022. "High temperature central tower plants for concentrated solar power: 2021 overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    8. Collado, Francisco J. & Guallar, Jesus, 2019. "Quick design of regular heliostat fields for commercial solar tower power plants," Energy, Elsevier, vol. 178(C), pages 115-125.
    9. Xie, Qiyue & Guo, Ziqi & Liu, Daifei & Chen, Zhisheng & Shen, Zhongli & Wang, Xiaoli, 2021. "Optimization of heliostat field distribution based on improved Gray Wolf optimization algorithm," Renewable Energy, Elsevier, vol. 176(C), pages 447-458.
    10. Chao Li & Rongrong Zhai & Yongping Yang, 2017. "Optimization of a Heliostat Field Layout on Annual Basis Using a Hybrid Algorithm Combining Particle Swarm Optimization Algorithm and Genetic Algorithm," Energies, MDPI, vol. 10(11), pages 1-15, November.
    11. Omar Behar & Daniel Sbarbaro & Luis Morán, 2020. "A Practical Methodology for the Design and Cost Estimation of Solar Tower Power Plants," Sustainability, MDPI, vol. 12(20), pages 1-16, October.
    12. Okoroigwe, Edmund & Madhlopa, Amos, 2016. "An integrated combined cycle system driven by a solar tower: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 337-350.
    13. Zhang, Maolong & Xu, Chao & Du, Xiaoze & Amjad, Muhammad & Wen, Dongsheng, 2017. "Off-design performance of concentrated solar heat and coal double-source boiler power generation with thermocline energy storage," Applied Energy, Elsevier, vol. 189(C), pages 697-710.
    14. Merchán, R.P. & Santos, M.J. & Heras, I. & Gonzalez-Ayala, J. & Medina, A. & Hernández, A. Calvo, 2020. "On-design pre-optimization and off-design analysis of hybrid Brayton thermosolar tower power plants for different fluids and plant configurations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    15. Wang, Shuang & Asselineau, Charles-Alexis & Fontalvo, Armando & Wang, Ye & Logie, William & Pye, John & Coventry, Joe, 2023. "Co-optimisation of the heliostat field and receiver for concentrated solar power plants," Applied Energy, Elsevier, vol. 348(C).
    16. Mostafavi Tehrani, S. Saeed & Taylor, Robert A., 2016. "Off-design simulation and performance of molten salt cavity receivers in solar tower plants under realistic operational modes and control strategies," Applied Energy, Elsevier, vol. 179(C), pages 698-715.
    17. Rizvi, Arslan A. & Yang, Dong, 2022. "A detailed account of calculation of shading and blocking factor of a heliostat field," Renewable Energy, Elsevier, vol. 181(C), pages 292-303.
    18. Wang, Jianxing & Guo, Lili & Zhang, Chengying & Song, Lei & Duan, Jiangyong & Duan, Liqiang, 2020. "Thermal power forecasting of solar power tower system by combining mechanism modeling and deep learning method," Energy, Elsevier, vol. 208(C).
    19. Wang, Jianxing & Duan, Liqiang & Yang, Yongping & Yang, Zhiping & Yang, Laishun, 2019. "Study on the general system integration optimization method of the solar aided coal-fired power generation system," Energy, Elsevier, vol. 169(C), pages 660-673.
    20. Zhang, Maolong & Yang, Lijun & Xu, Chao & Du, Xiaoze, 2016. "An efficient code to optimize the heliostat field and comparisons between the biomimetic spiral and staggered layout," Renewable Energy, Elsevier, vol. 87(P1), pages 720-730.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:730-:d:99281. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.