Novel Multi-Objective Optimal Design of a Shell-and-Tube Latent Heat Thermal Energy Storage Device

Francesco Fornarelli (), Lorenzo Dambrosio, Sergio Mario Camporeale and Luigi Terlizzi
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Francesco Fornarelli: Department of Sciences of Agriculture, Food, Natural Resources and Engineering, University of Foggia, Via Napoli, 25, 71121 Foggia, Italy
Lorenzo Dambrosio: Department of Mechanics, Mathematics and Management (DMMM), Politecnico di Bari, Via Orabona, 4, 70125 Bari, Italy
Sergio Mario Camporeale: Department of Mechanics, Mathematics and Management (DMMM), Politecnico di Bari, Via Orabona, 4, 70125 Bari, Italy
Luigi Terlizzi: Department of Mechanics, Mathematics and Management (DMMM), Politecnico di Bari, Via Orabona, 4, 70125 Bari, Italy

Energies, 2023, vol. 16, issue 4, 1-14

Abstract: In the present paper a new multi-objective optimisation procedure for the design of a shell-and-tube Latent Heat Thermal Energy Storage (LHTES) is proposed. A simple arrangement of a cylindrical shell with multiple vertical tubes has been examined. The optimisation considers, as design variables, the number of tubes, the tube internal radius and the device height-to-diameter ratio, H / D , while the storage volume is kept constant. This analysis aims to detect the set of solutions which optimises the LHTES performances evaluated in terms of charging and discharging times and overall thermal energy capacity. To accomplish the multi-objectives optimal thermal storage design, a simplified mathematical model of the LHTES has been employed. This model can evaluate the prescribed performances for a given set of design variables. The proposed optimisation procedure evaluates new solutions along the most promising directions in the design variables domain, leading to a significant improvement in storage performances. The Design of the Experiment, together with the Pareto dominance relationship, gives a starting optimal solutions subset. The proposed optimisation procedure permits to enhance the starting optimal solutions subset letting approach the Pareto barrier. The paper shows that, at the end of the optimisation procedure, the designer can select the solutions on the Pareto barrier with the best performance and the corresponding design variables for each chosen solution. The proposed optimisation procedure will also allow for maintaining low computational costs due to the low number of the new design variables evaluated only in the promising directions.

Keywords: thermal storage; LHTES; multi-objective optimisation; PCM (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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