Performance prediction and optimization of a three-layer thermocline tank using the response surface method

The majority of prior experimental and computational studies of the energy tank system employed in solar power plant systems have been focused on parametric studies. The interaction effects of several input factors on the thermal behavior of the TTES tank configuration using RSM have not yet been addressed. A predictive approach depending on the response surface method (RSM) is built in this work to demonstrate the link between the independent and dependent parameters of the thermocline storage tank structure. The two-phase dispersion-concentric numerical model equations were calculated and solved using MATLAB software. RSM is used for both single and multi-objective optimization to suggest appropriate control parameters for various optimization purposes. Four response factors are considered: charging/discharging time, efficiency, and recovered energy. The analysis of variance check and perturbation assessment is as well used to assess the model's appropriateness and statistical significance. Based on the findings, it is recommended to choose a capsule diameter of 0.015 m, a charging cycle inlet temperature of 400°C, a discharging cycle inlet temperature of 250°C, and a molten salt mass flow rate of 100 kg/s to minimize charging and discharging time while also maximizing overall efficiency and recovered energy.