Renewable Energy, Vol.157, 130-149, 2020
An intuitive framework for optimizing energetic and exergetic performances of parabolic trough solar collectors operating with nanofluids
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/m(2), an inlet temperature of 240.793 degrees 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. (C) 2020 Elsevier Ltd. All rights reserved.
Keywords:Solar energy;Parabolic trough collector;Nanofluid;Computational fluid dynamics;Artificial neural network;Multi-objective optimization