Constrained Multi-Objective Optimization of Thermocline Packed- Bed Thermal Energy Storage Systems
Abstract
A constrained multi-objective optimization approach is used to optimize the exergy efficiency and material costs of thermocline packed-bed thermal energy storage systems. The storage height, top and bottom radii, insulation-layer thickness, and particle diameter were chosen as design variables. The competing objectives of maximizing the exergy efficiency and minimizing the material costs are dealt with by forming a Pareto front. The Pareto front allows the identification of the most efficient design for a given cost and is an important tool in the design of thermal energy storage systems. Constraints are imposed to obtain storage systems with a specified capacity. The optimization approach is applied to identify the influence of various design variables on the exergy efficiency and the material costs. The results show that a storage shaped like a truncated cone with the smallest cross-section on top has a higher exergy efficiency than common designs with a cylindrical shape or a truncated cone with the largest cross-section on top. The basic thermodynamic mechanisms leading to this superior performance are identified with detailed information about the axial temperature distribution in the packed bed and thermal losses through the structure and insulation materials.
Keywords
Thermal energy storage, Thermocline energy storage, Packed bed, Exergy efficiency, Multi- objective optimization, Pareto optimality, Pareto front