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

Packed-bed sensible thermal energy storage system using demolition wastes for concentrated solar power plants

“…Charging efficiency drops dramatically over 1.5 mm/s velocity. Unsteady laminar flow starts when Rep is higher than 150 [14] and for the system analysed here, Rep is close to 150 at 3.0 mm/s velocity. As seen in Figure 1, stratification of thermocline starts to be destroyed after 1.5 mm/s.…”

“…Although using cheap storage material is important criteria, there are a lot of design parameters that effect the storage performance. According to Marti et al [14], mass flow, inlet temperature, particle diameter, bed void fraction and packed bed dimensions are main operational and geometrical parameters that need to be determined for storage design. Khan et al [5] have determined that fluid velocity and particle dimensions are effective on solid storage system behavior in CSP plants.…”

Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories

“…Recently, multi-objective optimization approaches have been successfully applied to various scenarios. Examples include the rational design of dielectric nanoantennas 11 and plasmonic waveguides, 12 the optimization of Stirling heat pumps, 13 the design of thermal-energy storage systems, 14 – 16 and optimizations on scheduling problems in combined hydro-thermo-wind power plants. 17 However, in the aforementioned applications the merit of a set of conditions could be assessed by analytic models which were fast to evaluate computationally.…”

Numerical Model of Lab-Scale Packed-Bed Thermal Energy Storage System

“…There are many parameters that affect the performance of thermocline packed-bed TES systems. Marti et al [2] classifies these critical design parameters as operational, thermophysical, geometrical and performance parameters (Table I).…”