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

Nicolás C. Cruz, José D. Álvarez, Juana L. Redondo, Jesús Fernández-Reche, Manuel Berenguel, Rafael Monterreal and Pilar M. Ortigosa
Additional contact information
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

Energies, 2017, vol. 10, issue 5, 1-17

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.

Keywords: solar central receiver systems; flux distribution; heliostat field characterization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/5/730/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/5/730/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:5:p:730-:d:99281

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().