Enhancing phase change energy storage efficiency: Performance optimization of Fibonacci fractal fins under fluctuating heat source

Solar power, though an essential renewable energy source, suffers from intermittency and fluctuations, leading to reduced efficiency in thermal storage systems. This research examines an enhanced three-tube latent heat storage system (TES) incorporating Fibonacci fractal tree-shaped fins, an innovat...

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Veröffentlicht in:Solar energy materials and solar cells Jg. 293; S. 113859
Hauptverfasser: Ren, Fan, Li, Qibin, Shi, Lei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.12.2025
Schlagworte:
Fibonacci sequence
Fractal tree-shaped fins
Non-dominated sorting genetic algorithm
Phase change heat storage
Fractal tree-shaped fins
Non-dominated sorting genetic algorithm
Fibonacci sequence
Phase change heat storage
ISSN:0927-0248
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Zusammenfassung:Solar power, though an essential renewable energy source, suffers from intermittency and fluctuations, leading to reduced efficiency in thermal storage systems. This research examines an enhanced three-tube latent heat storage system (TES) incorporating Fibonacci fractal tree-shaped fins, an innovative design developed to optimize heat transfer performance. The results reveal that increasing the fin branching angle significantly improves heat transfer efficiency within the TES system. Furthermore, both the period and amplitude of sinusoidal fluctuating heat sources exert considerable influence on phase change material (PCM) temperature distribution and thermal storage capacity. Through multi-objective optimization employing the non-dominated sorting genetic algorithm (NSGA-II) algorithm, the study determines an optimal system configuration achieving a melting time of 151.18 s and thermal storage capacity of 576.32 kJ. The optimized parameters consist of a 109.99-s sinusoidal period, 12.50 K amplitude, and 102.07°branching angle. The key innovation of this study resides in the synergistic integration of bio-inspired fractal fin structures with advanced multi-objective optimization algorithms, which establishes a novel approach for addressing intermittency challenges in solar thermal energy storage systems. •A fractal fin of Fibonacci series is proposed.•When the PCM melts 60 %, the following PCM will show sinusoidal fluctuation.•The larger the amplitude, the earlier the PCM average temperature fluctuates.•Multi-objective optimization of TES was carried out by response surface method.
ISSN:0927-0248
DOI:10.1016/j.solmat.2025.113859