<p>The present article highlights the implementation of differential evolution (DE)-assisted metaheuristic optimizer to provide the solution of an inverse multi-variable problem related to a flat absorber solar collector consisting of a single glass. For satisfying a given heating requirement from the solar collector, the necessary tilt angle and the thickness of the glass cover are simultaneously predicting using the proposed DE methodology. The existing study of inverse multi-variable optimization analysis has been done for dynamic values of solar energy radiation and different ambient conditions commonly encountered in various geographical locations of India. Formulation of the current research involves the minimization of a newly proposed cost function involving the required and the acquired heat transfer rates from the solar collector in Euclidean space. The solution approach then utilizes a dynamic exchange between evolutionary metaheuristic DE and a well-validated forward solver containing analytical expressions of heat energy balance within the solar collector. Variations of cost function and the estimated design variables are mainly studied to visualize the algorithm’s behavior for a single gazing-based solar thermal device. Multiple possible groupings of the unknown parameters of the solar collector are revealed which always collectively result in a desired heating requirement from the solar collector. Sensitivity indices related to the design variables are evaluated for ascertaining the relative importance of parameter selection. Encouraging opportunity is found towards the system’s size reduction through sparing selection of inclination angle. The current study provides a convenient and cost-effective tool to select the necessary inclination and glass covers to obtain low to medium heating requirements from the available incident solar energy.</p>

An Inverse Method for Parameter Retrieval in Solar Thermal Collector With a Single Glass Cover

Paper Proceedings: https://asmedigitalcollection.asme.org/POWER/POWER2021/volume/85109

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