Parametric Investigation to Assess the Charging and Discharging Time for a Latent Heat Storage Material-Based Thermal Energy Storage System for Concentrated Solar Power Plants

Thermal energy storage (TES) systems are becoming increasingly crucial as viable alternatives for effective energy utilization from various sources, such as solar power plants and waste heat from different industrial sectors. The present work focuses on latent heat TES system optimization for solar thermal power plant applications. This study aims to assess the impact of different thermal processing factors on the efficiency of TES systems. Parametric analysis determines a TES system's charging and discharging durations that use latent heat storage material. Thermal processing conditions were selected as input parameters, such as the heat transfer fluid inlet temperature, flow rate, and number of phase change material (PCM) capsules. Experiments were planned to use the L₉ orthogonal array of the Taguchi method, and response measures, such as charging time (CT) and discharging time (DT), were monitored. A signal-to-noise ratio analysis was used to evaluate the significance of the thermal processing parameters on the response measures. Response surface methodology (RSM) postulates the mathematical relationships between process conditions and responses. Finally, the multi-objective Jaya optimization algorithm (MOJOA) was used to optimize the parametric combination to minimize CT and maximize DT simultaneously. A heat transfer fluid inlet temperature of 65°C, flow rate of 2 L/min, and 40 PCM capsules were determined as the optimal parametric conditions by MOJOA for predicting the combined CT and DT. The verification test results substantiate the enhanced responses of the latent heat TES system, specifically in the CT and DT. Utilizing the integrated Taguchi method, RSM-MOJOA is advantageous for examining, modeling, and predicting PCM-based TES systems.