Multi-objective optimization of fin shape in a cylindrical encapsulated phase change material for thermal energy storage applications

Abstract

This study presents a novel fin design for a latent heat storage unit that improves its thermal performance through a methodology that integrates numerical simulation, the response surface method, and a multi-objective genetic optimization algorithm. The stored latent energy per mass (Em) and mean power (Pt) are chosen as the objectives for the optimization process. The fin parameters are optimized using the NSGA-II (non-dominated sorting genetic algorithm) to achieve the objectives of maximizing both the stored latent energy per mass (Em) and mean power (Pt). The proposed design is evaluated through simulations and the results are analyzed to determine the optimal fin configuration and the effect of the fin design parameters on the stored energy and power of the unit. The results show that the implementation of full-fin in the latent heat storage unit leads to a 7.2% reduction in total stored energy, but a 34% increase in power in comparison to the finless case. However, the use of an optimization approach results in a substantial increase in power output while maintaining minimal compromise to the stored latent energy. In particular, the optimal fin configuration, Design B, is recommended when power and stored energy are given equal importance, as it results in a 90.1% increase in power and a negligible 4.3% decrease in stored energy per mass.