LAUSR

Abstract The porous volumetric solar receiver shows advantages such as the volumetric absorption of solar radiation and the enhanced convective heat transfer. However, few studies were focused on the selection of the appropriate parameters of the receiver to improve its performance. In this contribution, an optimization method which couples the genetic algorithm and the heat transfer analysis of the porous volumetric solar receiver is proposed. The fluid flow and heat transfer in the receiver are evaluated by the volume-averaging simulation method based on the local thermal non-equilibrium model. By combining with the genetic algorithm, the solar receiver with high thermal efficiency and low flow resistance could be identified. The single-objective optimization results present that larger porosity and higher inlet velocity are preferable to improve the thermal efficiency of the porous volumetric solar receiver. The optimized pore size increases with the increase of the thickness of the receiver and the decrease of the inlet velocity. Meanwhile, the porosity and the pore size are optimized simultaneously through the multi-objective optimization. The Pareto front which indicates the receiver with relatively lower flow resistance and relatively higher thermal efficiency is derived.