Abstract
This study investigates a novel design optimization method for a low-temperature latent thermal energy storage (LTES) in a shell-and-tube heat exchanger configuration for a district/urban cooling network. An ordered hexagonal tube-packing method is first developed for the inner configuration of the LTES followed by the implementation of a differential evolutionary multi-objective optimization scheme for key design variables. Using a numerical model, transient characterisation of the optimized designs from a prior work confirmed that the method was capable of producing improved outcomes of up to 54.7% increased storage capacity. Key observations from the optimization revealed that heat transfer maximization scales costs by up to 10 times while minimizing costs translates to a mere three-fold decrease in heat transfer characteristics. Further characterisation of the optimized LTES designs under district cooling application showed that optimizing for discharge exergy efficiency in addition to cost and heat transfer efficiency was crucial in maximising discharge efficiency by up to 30%, as well as producing 33% and 20% greater capital cost savings compared to the single- and double-objective optimization cases respectively.
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