Constrained multi-objective optimization of thermocline packed-bed thermal-energy storage

A constrained multi-objective optimization approach is applied to optimize the exergy efficiency and material costs of thermocline packed-bed thermal-energy storage systems using air as the heat-transfer fluid. The axisymmetric packed-bed's height, top and bottom radii, insulation-layer thicknesses, and particle diameter were chosen as design variables. The competing objectives of maximizing the exergy efficiency and minimizing the material costs were treated by a Pareto front. The Pareto front allows identifying the most efficient design for a given cost or the cheapest design for a given efficiency and is an important tool to find the best overall design of storage systems for a specific application. Constraints were imposed to obtain storage systems with specified capacities and limits on the air outflow temperatures during charging and discharging. The results showed that a storage shaped as a truncated cone with the smallest cross-section at the top has a higher exergy efficiency than storages shaped as cylinders or truncated cones with the largest cross-section at the top. The higher efficiency is attributed to the axial temperature distribution in the packed bed and the associated conduction heat losses across the insulated walls. The optimization of an industrial-scale storage allowed identifying a design with an exergy efficiency that was only 4.8% below that of the most efficient design, but a cost that was 81.3% lower than the cost of the most efficient design. Compared to brute-force design approaches, the optimization procedure can reduce the computational time by 91-99%.