2026-05-27T12:54:46Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/457002026-02-25T00:45:21Zcom_10630_2254col_10630_37953

Combining ray-tracing and a linear thermal model to predict the performance of a panel solar cooker under varying solar angles García-Fernández, Jesús Carrillo-Andrés, Antonio Apaolaza-Pagoaga, Xabier García-Ruiz, Antonio Ruiz-Reina, Emilio Cocinas Energía solar Panel-type solar cookers are low-cost, lightweight systems that are easy to assemble using readily available materials, making them well suited for sustainable energy initiatives in low-income or displaced communities. These cookers usually rely on manual azimuthal sun-tracking, but their optical performance is sensitive to the solar elevation angle, which can vary significantly during a typical cooking session. Such variability directly affects the overall thermal performance of the cooker, reducing the probability of successful cooking. This work introduces a combined optical and thermal simulation workflow capable of predicting the performance of a panel-type solar cooker under varying solar angles. The method is applied to the Copenhagen solar cooker, whose complex, non-analytical panel geometry is reproduced using a structural simulation of the folding process. These geometrical models form the basis for ray-tracing simulations that generate two-dimensional optical performance maps coupled to a simplified thermal model to predict heat gain under different solar angles. Simulated and experimental results agree well, demonstrating that the proposed workflow is a practical and transferable tool for performance prediction and design optimization of simple solar cooking technologies. 2026-05 journal article García-Fernández, Jesús, Carrillo-Andrés, Antonio, Apaolaza-Pagoaga, Xabier, García-Ruiz, Antonio, Ruiz-Reina, Emilio (2026). Combining ray-tracing and a linear thermal model to predict the performance of a panel solar cooker under varying solar angles. Renewable Energy. Elsevier. Vol. 263, 1 de mayo https://hdl.handle.net/10630/45700 10.1016/j.renene.2026.125443 eng http://creativecommons.org/licenses/by/4.0/ open access Attribution 4.0 International Elsevier