Development of numerical techniques for evaluation of point-focus solar cavity receiver performance

Abstract

Solar receiver cavities, which are designed to absorb large amounts of concentrated solar irradiation, form the central component of a solar collection plant. Since this receiver’s efficiency is directly proportional to the plant’s overall performance, the optimum design of these receivers is an important research field, as it is key to the maximisation of electricity output, while maintaining reasonable costs as an alternative to the high costs of fossil fuel energy generation technologies. Due to the high temperatures that are reached inside a solar receiver, the prediction of heat flux distribution and the subsequent effects on conjugate heat transfer have been key areas of research in the solar field. Initially dominated by experimental studies, research has trended towards numerical prediction using finite volume methods (FVM), due to the low turnaround time and cost-effective nature of this type of analysis. Owing to the need to accurately predict these heat flux distributions, a methodology to numerically simulate concentrated heat flux on complex surfaces of a solar receiver is developed. A combination of Monte Carlo ray tracing (MCRT) methods and computational fluid dynamics (CFD) is implemented to estimate system performance, while minimising computational time and expense, with limited sacrifice of accuracy. After successful validation of this method with experimental data, iterative performance simulations on a candidate geometry, implemented in a realistic solar-concentrating field, are performed to showcase the ability of the methodology to accurately predict system performance. The sample geometry is based on a number of implementations from various case studies and receivers that are used nowadays, with each iteration allowing for parameter adjustment to maximise optical and thermal efficiency. Key result outputs include the prediction of heat flux distributions and subsequent thermal stress raisers, such as hot spots, convective and re-radiation heat losses, and operating temperatures. Determining which of these thermal stress raisers from the implementation of this model can further improve and streamline designs.