Evaluation of heliostat field global tracking error distributions by Monte Carlo simulations

L. A. Díaz-Félix, M. Escobar-Toledo, J. Waissman, N. Pitalúa-Díaz, C. A. Arancibia-Bulnes*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

13 Scopus citations

Abstract

Several error sources can contribute to the global tracking error of heliostats. These sources can be, for instance, angular offset in the reference position of the tracking mechanisms, imperfect leveling of the heliostat pedestal, lack of perpendicularity between the tracking axes, lack of precise clock synchronization. All these possible errors are characterized by angles that have very specific numerical values for each heliostat in a central receiver installation. However, they are intrinsically random in nature, and the errors in different heliostats are independent from each other. In principle, the overall drift behavior of the heliostats can be characterized by a statistical distribution of tracking errors. This global distribution characterizes the angular deviation of the heliostat normal and is used in ray tracing simulations of heliostat fields. It is usually assumed to be Gaussian, although some authors argue in favor of other types of distributions. In the present work, the dependence of the global tracking error distribution on the above mentioned primary error sources is investigated by means of Monte Carlo simulations. Random values are assumed for the different error parameters, and the resulting global tracking error distributions are evaluated for different times of the year for a heliostat field.

Original languageEnglish
Pages (from-to)1308-1317
Number of pages10
JournalEnergy Procedia
Volume49
DOIs
StatePublished - 2014
EventInternational Conference on Solar Power and Chemical Energy Systems, SolarPACES 2013 - Las Vegas, NV, United States
Duration: 17 Sep 201320 Sep 2013

Bibliographical note

Funding Information:
This work has been funded jointly by CONACYT (Grant Universidad Nacional Autónoma de México (UNAM).

Keywords

  • Gaussian distribution
  • Heliostat
  • Monte Carlo simulations
  • Solar tower power plants
  • Tracking errors

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