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

Authors :
Abubakr, Mohamed
Amein, Hamza
Akoush, Bassem M.
El-Bakry, M. Medhat
Hassan, Muhammed A.
Source :
Renewable Energy: An International Journal. Sep2020, Vol. 157, p130-149. 20p.
Publication Year :
2020

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 (Al 2 O 3 , CuO, and SiO 2) 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. Image 1 • A procedure is proposed for optimizing the performance of PTC with nanofluids. • Optical, thermal, prediction and optimization models are developed and validated. • 3840 combinations of nanofluids and operating conditions are studied. • Optimal solutions of the multi-objective optimization problem are presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09601481
Volume :
157
Database :
Academic Search Index
Journal :
Renewable Energy: An International Journal
Publication Type :
Academic Journal
Accession number :
143782332
Full Text :
https://doi.org/10.1016/j.renene.2020.04.160