Análisis de la distancia focal en un concentrador solar de disco parabólico utilizando trazado de rayos
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nov 1, 2026
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https://doi.org/10.36677/rici.v4i3.28584
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David Rojas Valdez
http://orcid.org/0000-0002-2917-558X
Miriam Sánchez Pozos
http://orcid.org/0000-0002-6528-5524
María Dolores Durán García
http://orcid.org/0000-0002-7569-249X
Iván Galileo Martínez Cienfuegos
http://orcid.org/0000-0001-5417-0548
Martha Fernanda Mohedano Castillo
http://orcid.org/0009-0003-6685-2345
http://orcid.org/0000-0002-2917-558X
Miriam Sánchez Pozos
http://orcid.org/0000-0002-6528-5524
María Dolores Durán García
http://orcid.org/0000-0002-7569-249X
Iván Galileo Martínez Cienfuegos
http://orcid.org/0000-0001-5417-0548
Martha Fernanda Mohedano Castillo
http://orcid.org/0009-0003-6685-2345
Resumen
Este estudio investiga la influencia de la longitud focal en el rendimiento de un concentrador solar de disco parabólico (CDP) mediante el método de trazado de rayos. Se utilizaron el software SolTrace, Tonatiuh y un programa desarrollado en MATLAB para analizar cómo varía la energía concentrada en el receptor al modificar la longitud focal del paraboloide. Los concentradores solares parabólicos son fundamentales para aplicaciones de energía solar de alta temperatura, como la generación de electricidad, donde la eficiencia del sistema depende en gran medida de la correcta focalización de la energía solar. La investigación se centra en el análisis de la distribución del flujo de energía en el receptor para diversas longitudes focales, utilizando el método Monte Carlo para simular el comportamiento de los rayos solares. Los resultados muestran que existe una longitud focal óptima que maximiza la concentración de energía en el receptor, mejorando así la eficiencia del sistema. Además, se realizó una comparación entre los resultados obtenidos con SolTrace, Tonatiuh y MATLAB, identificando diferencias mínimas en la uniformidad y la distribución de la energía concentrada. El estudio concluye que la correcta selección de la longitud focal es crucial para optimizar el rendimiento de los concentradores solares parabólicos. Estos hallazgos son de gran importancia tanto para el diseño de sistemas solares más eficientes como para la implementación de tecnologías de concentración solar en aplicaciones industriales. Este trabajo contribuye significativamente al campo de la energía solar, ofreciendo un enfoque metodológico para la optimización del rendimiento de concentradores solares parabólicos.
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ROJAS VALDEZ, David et al.
Análisis de la distancia focal en un concentrador solar de disco parabólico utilizando trazado de rayos.
Ideas en Ciencias de la Ingeniería, [S.l.], v. 4, n. 3, p. 66-88, nov. 2026.
ISSN 2992-7447.
Disponible en: <https://ideasencienciasingenieria.uaemex.mx/article/view/28584>. Fecha de acceso: 01 nov. 2026
doi: https://doi.org/10.36677/rici.v4i3.28584.
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Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-SinObrasDerivadas 4.0.
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[21] M. Reeze, M. A. Veerman, and C. C. van Heerwaarden, “Machine learning-based denoising of surface solar irradiance simulated with Monte Carlo ray tracing,” Journal of Geophysical Research: Machine Learning and Computation, vol. 2, Art. no. e2024JH000515, 2025, doi: 10.1029/2024JH000515.
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[25] J. Yan, Y.-X. Liu, and Y.-D. Peng, “Study on the optical performance of novel dish solar concentrator formed by rotating array of plane mirrors with the same size,” Renewable Energy, vol. 195, pp. 416–430, 2022, doi: 10.1016/j.renene.2022.06.005.
[2] E. González-Mora and M. Durán-García, “Energía solar concentrada para procesos industriales: un recurso estratégico hacia la sostenibilidad,” CIENCIA ergo-sum, vol. 33, 2025, doi: 10.30878/ces.v33n0a54.
[3] K. Faye, A. Thiam, M. Faye, K. J. Craig, E. H. I. Cissé, and V. Sambou, “Combining ray tracing and CFD to evaluate the outlet air temperature of an indirectly irradiated solar receiver equipped with a 3D-CPC for a solar tower power plant,” SSRN Electronic Journal, 2022, doi: 10.2139/ssrn.4237380.
[4] G. Klepp, “Solar Stirling for Renewable Energy Multigeneration Systems,” Sustainability, vol. 17, no. 3, p. 1257, 2025, doi: 10.3390/su17031257.
[5] D. Banitia, S. Ramachandran, S. S. Bhogilla, and P. K. Vijayan, “Optical analysis and design of a novel solar beam down concentrator for indoor cooking,” Solar Compass, vol. 12, Art. no. 100083, 2024, doi: 10.1016/j.solcom.2024.100083.
[6] L. F. Martins, J. E. P. Navalho, M. A. A. Mendes, and J. C. F. Pereira, “Optical and thermal performance analysis of ceramic foam solar receivers in parabolic dish solar collector assemblies: The role of collector geometrical and optical parameters and absorber and coating materials,” Energy Conversion and Management, vol. 365, Art. no. 121694, 2026, doi: 10.1016/j.enconman.2026.121694.
[7] M. H. Farhat, Y. Mazloum, S. Wakim, W. Bou Nader, M. ALEbrahim, and N. Ghareeb, “Energy optimization of parabolic dish solar concentrator coupled to organic Rankine cycle: Experimental and analytical investigation of cavity receiver design and covering effects,” International Journal of Thermofluids, vol. 23, Art. no. 100730, 2024, doi: 10.1016/j.ijft.2024.100730.
[8] M. Rahbari, P. Esfanjani, A. Mahmoudi, and M. S. Valipour, “Performance enhancement of a parabolic dish collector with a novel receiver assisted with a secondary reflector,” Solar Energy Materials and Solar Cells, vol. 283, Art. no. 113464, 2025, doi: 10.1016/j.solmat.2025.113464.
[9] R. Mitchell, Y. Wang, M. Izygon, J. Pye, and G. Zhu, “Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL,” Solar Energy, vol. 300, Art. no. 113785, 2025, doi: 10.1016/j.solener.2025.113785.
[10] L. Jadhav, P. Gadiya, J. Girnar, H. Bhusal, and P. Gadhe, “Numerical analysis using SolTrace software to determine the size and position of a central receiver for ganged heliostat system,” IOP Conference Series: Earth and Environmental Science, vol. 1042, no. 1, Art. no. 012015, 2022, doi: 10.1088/1755-1315/1042/1/012015.
[11] P. Richter and F. Hövelmann, “Computationally fast analytical ray-tracer for central receiver systems,” in AIP Conference Proceedings, vol. 2445, Art. no. 030019, 2022, doi: 10.1063/5.0085714.
[12] L. Li, Y. Zhang, H. Li, R. Liu, and P. Guo, “An optimized approach for solar concentrating parabolic dish based on particle swarm optimization-genetic algorithm,” Heliyon, vol. 10, no. 4, Art. no. e26165, 2024, doi: 10.1016/j.heliyon.2024.e26165.
[13] K. H. Kumar, D. S. Reddy, and M. Karmakar, “Optical modeling of a cylindrical-hemispherical receiver for parabolic dish concentrator,” Environmental Science and Pollution Research, vol. 30, no. 22, pp. 63121–63134, May 2023, doi: 10.1007/s11356-023-26432-4.
[14] E. H. El-Gamal, M. Emran, O. Elsamni, M. Rashad, and O. Mokhiamar, “Parabolic Dish Collector as a New Approach for Biochar Production: An Evaluation Study,” Applied Sciences, vol. 12, no. 24, Art. no. 12677, 2022, doi: 10.3390/app122412677.
[15] H. S. Al-Arab, “Analyzes and compares the optical characteristics for two types of solar dish concentrators,” Journal of Optics, 2024, doi: 10.1007/s12596-024-02278-y.
[16] D. Banitia, S. Ramachandran, S. S. Bhogilla, and P. K. Vijayan, “Mathematical modeling and optical-thermal analysis of a novel solar beam down parabolic dish concentrator,” Solar Compass, vol. 15, Art. no. 100137, 2025, doi: 10.1016/j.solcom.2025.100137.
[17] N. Zhang, N. Huang, and C. Gong, “Improved Monte Carlo ray-tracing algorithm based on importance sampling,” Journal of Physics: Conference Series, vol. 2700, no. 1, Art. no. 012005, 2024, doi: 10.1088/1742-6596/2700/1/012005.
[18] G. Canneto, I. Balog, P. Di Ascenzi, and G. Caputo, “Analysis of Experimental Data from a Concentrating Parabolic Solar Plant and Comparison with Simulation Model Results,” Energies, vol. 18, no. 12, Art. no. 3161, 2025, doi: 10.3390/en18123161.
[19] S. Y. Khan, M. Uzair, and U. Allauddin, “Coupled optical-thermal performance enhancement of solar parabolic dish system using a hemiellipsoidal tubular receiver,” Renewable Energy, vol. 256, Part F, Art. no. 124434, 2026, doi: 10.1016/j.renene.2025.124434.
[20] N. ur Rehman and M. Uzair, “Hybrid ray-tracing model for solar energy assessment and its open-source implementation as a service,” Transactions of the Canadian Society for Mechanical Engineering, vol. 49, no. 2, pp. 289–300, 2025, doi: 10.1139/tcsme-2024-0044.
[21] M. Reeze, M. A. Veerman, and C. C. van Heerwaarden, “Machine learning-based denoising of surface solar irradiance simulated with Monte Carlo ray tracing,” Journal of Geophysical Research: Machine Learning and Computation, vol. 2, Art. no. e2024JH000515, 2025, doi: 10.1029/2024JH000515.
[22] R. Winston, J. C. Miñano, and P. Benítez, Nonimaging Optics. Burlington, MA, USA: Elsevier Academic Press, 2005.
[23] F. M. Boora, J. Ebrahimpourboura, and M. Sheikholeslami, “Machine learning technique for optimization of solar unit equipped with a novel design tube filled with nanofluid,” Engineering Applications of Artificial Intelligence, vol. 166, Part A, Art. no. 113544, 2026, doi: 10.1016/j.engappai.2025.113544.
[24] Y. Zheng, L. Li, S. Dai, D. Liu, H. Zheng, S. Yang, Y. Guo, M. Rafique, B. Wang, C.-H. Wang, and Y. Shuai, “Monte-Carlo ray tracing simulation of view factors for diffuse solar radiation determination in cylindrical photobioreactor arrays for microalgae cultivation,” Bioresource Technology, vol. 436, Art. no. 132813, 2025, doi: 10.1016/j.biortech.2025.132813.
[25] J. Yan, Y.-X. Liu, and Y.-D. Peng, “Study on the optical performance of novel dish solar concentrator formed by rotating array of plane mirrors with the same size,” Renewable Energy, vol. 195, pp. 416–430, 2022, doi: 10.1016/j.renene.2022.06.005.