Numerical analysis and optimization of an indirectly irradiated solar receiver for a Brayton cycle. (1st January 2019)

• Record Type: Journal Article
• Authors: Ndiogou, Baye A.; Thiam, Ababacar; Mbow, Cheikh; Stouffs, Pascal; Azilinon, Dorothé
• Is Part Of: Energy. Volume 166(2019)
• Page Start: 519
• Page End: 529
• Publication Date: 2019-01-01
• Subjects: CSP -- Air solar receiver -- Net-radiation method -- CFD modeling -- Response surface method optimization -- MOGA; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.09.176
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This work presents the modeling and optimization of an indirectly irradiated solar receiver. A numerical model of the cavity-absorber block is put forward with the coupling of the net-radiation method using the infinitesimal areas and a CFD code. An iterative method with a relaxation factor made it possible to obtain the temperature distribution and the developed code was implemented in the form of UDF and used as boundary conditions in the CFD model of the absorber to simulate the flow of air and heat transfer. The good ability of the receiver to transfer heat to the fluid is proved with a 92% thermal efficiency obtained. Then the combination of the Kriging surface response method and the MOGA allowed the mathematical optimization of the receiver. The response surface results showed that the most influencing parameter on the outlet temperature is porosity with 62%, due to the fact that it strongly impacts on the exchange surfaces between the fluid and the porous matrix. The results obtained by MOGA made it possible to obtain the best combinations of parameters allowing the temperature and the amount of energy to be maximized at the output of the receiver. Highlights: Net-radiation method using infinitesimal areas for cavity radiative exchange model. Numerical model of the cavity-absorber block. Kriging Response for quantitative and qualitative analysis of the design parameters. MOGA optimization gives optimums temperature outlet and thermal efficiencies couples. MOGA gives compromise between temperatures outlet and thermal efficiencies.