An intuitive framework for optimizing energetic and exergetic performances of parabolic trough solar collectors operating with nanofluids

Mohamed Abubakr, Hamza Amein, Bassem M. Akoush, M. Medhat El-Bakry and Muhammed A. Hassan

Renewable Energy, 2020, vol. 157, issue C, 130-149

Abstract: Enhancing the thermal efficiency of parabolic trough collectors (PTCs) is essential for establishing CSP as a sustainable technology. This study proposes a simple procedure for evaluating, predicting, and optimizing the energetic and exergetic performances of PTCs operating with nanofluids. A coupled optical-thermal model is developed to simulate the turbulent flow of three common synthetic oils (Therminol VP-1, Syltherm 800, and Dowtherm Q) mixed with different nanoparticles (Al2O3, CuO, and SiO2) with different concentrations, under typical operating conditions of PTCs. The simulation results are fed to a soft-computing algorithm to develop prediction models that act as fitness functions in the multi-objective optimization process. For the considered range of input parameters and by assigning equal weights for the two optimization objectives (energy and exergy efficiencies), optimal design conditions corresponded to a PTC operating with CuO/Dowtherm Q nanofluid (volumetric concentration of 0.243%), at a direct irradiance level of 1000 W/m2, an inlet temperature of 240.793 °C, and a Reynolds number of 2.915E+05. These conditions led to energy and exergy efficiencies of 69.913 and 32.088%, respectively. The proposed procedure is described in detail to facilitate its adaptation and extension to other nanofluids, operating conditions, or other concentrating solar collectors.

Keywords: Solar energy; Parabolic trough collector; Nanofluid; Computational fluid dynamics; Artificial neural network; Multi-objective optimization (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:157:y:2020:i:c:p:130-149

DOI: 10.1016/j.renene.2020.04.160

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