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Multi-objective genetic algorithm for the optimization of a flat-plate solar thermal collector

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Abstract

We present a multi-objective genetic algorithm we developed for the optimization of a flat-plate solar thermal collector. This collector consists of a waffle-shaped Al substrate with NiCrOx cermet and SnO2 anti-reflection conformal coatings. Optimal geometrical parameters are determined in order to (i) maximize the solar absorptance α and (ii) minimize the thermal emittance ε. The multi-objective genetic algorithm eventually provides a whole set of Pareto-optimal solutions for the optimization of α and ε, which turn out to be competitive with record values found in the literature. In particular, a solution that enables α = 97.8% and ε = 4.8% was found.

© 2014 Optical Society of America

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Figures (2)

Fig. 1
Fig. 1 Waffle-shaped Al structure with NiCrOx and SnO2 conformal coatings. This corrugated structure sits on a semi-infinite Al substrate. This structure is considered for the development of high-performance flat-plate solar thermal collectors.
Fig. 2
Fig. 2 Left: number of Pareto-optimal solutions when searching for P, H, f, r, t1 and t2 with the objective of optimizing the parameters α and ε of a solar thermal collector; Right: reflectance spectrum of the waffle-shaped Al/NiCrOx/SnO2 structure that provides α = 97.8% and ε = 4.8% (solid), a flat Al/NiCrOx/SnO2 structure with t1 = t2 = 50 nm (dashed) and a flat uncoated Al (dot-dashed). The figure includes the normalized solar irradiance spectrum BS(λ) and the normalized black-body spectrum Ba(λ) of the absorber at 373 K.

Tables (1)

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Table 1 Parameters relevant to the optimization of α and ε of a solar thermal collector. The first line corresponds to the solution that maximizes f1 + f2. The next three lines correspond to selected Pareto-optimal solutions.

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