Revolutionizing heat recovery in shell-and-tube latent heat storage systems: an arc-shaped fin approach

Strengthening the thermal response of Phase-Change Materials (PCMs) is an essential and active field of research with promising potential for advanced applications such as solar energy storage, building energy conservation, and thermal management in electronic devices. This article evaluates the efficacy of a new arc-shaped fin array in shell-and-tube heat storage systems to enhance the PCM response during the discharge mode. Different fin geometric parameters including the fin curvature angle, the fin spacing, and the nonuniform angle between fins in the top and bottom sections of the PCM domain were considered to identify the best-performing layout. The analysis shows that increasing the curvature of arc-shaped fins between 60° and 180° and increasing the fin spacing between 5 and 15 mm can significantly reduce solidifying time and improve heat recovery rates. Moreover, the arc-shaped fins are more efficient than conventional longitudinal (+-shaped) fins, which are commonly employed in thermal energy storage applications. Arc-shaped fins can also save discharge time by more than half and improve the rate of heat recovery by almost four times than that of + -shaped fins. The present findings suggest that arc-shaped fins represent a promising design for enhancing the heat-recovery aspects in PCM-based energy storage systems

A novel efficient energy optimization in smart urban buildings based on optimal demand side management

Data availability: The data used for this research and prepatation of this article can be accessed from Brunel University of London repository at: https://doi.org/10.17633/rd.brunel.26049436.v1.Increasing electrical energy consumption during peak hours leads to increased electrical energy losses and the spread of environmental pollution. For this reason, demand-side management programs have been introduced to reduce consumption during peak hours. This study proposes an efficient energy optimization in Smart Urban Buildings (SUBs) based on Improved Sine Cosine Algorithm (ISCA) that uses the load-shifting technique for demand-side management as a way to improve the energy consumption patterns of a SUBs. The proposed system's goal is to optimize the energy of SUBs appliances in order to effectively regulate load demand, with the end result being a reduction in the peak to average ratio (PAR) and a consequent minimization of electricity costs. This is accomplished while also keeping user comfort as a priority. The proposed system is evaluated by comparing it with the Grasshopper Optimization Algorithm (GOA) and unscheduled cases. Without applying an optimization algorithm, the total electricity cost, carbon emission, PAR and waiting time are equal to 1703.576 ID, 34.16664 (kW), and 413.5864s respectively for RTP. While, after applying GOA, the total electricity cost, carbon emission, PAR and waiting time are improved to 1469.72 ID, 21.17 (kW), and 355.772s respectively for RTP. While, after applying the ISCA Improves the total electricity cost, PAR, and waiting time by 1206.748 ID, 16.5648 (kW), and 268.525384s respectively. Where after applying GOA, the total electricity cost, PAR, and waiting time are improved to 13.72 %, 38.00 %, and 13.97 % respectively. And after applying proposed method, the total electricity cost, PAR, and waiting time are improved to 29.16 %, 51.51 %, and 35.07 % respectively. According to the results, the created ISCA algorithm performed better than the unscheduled case and GOA scheduling situations in terms of the stated objectives and was advantageous to both utilities and consumers. Furthermore, this study has presented a novel two-stage stochastic model based on Moth-Flame Optimization Algorithm (MFOA) for the co-optimization of energy scheduling and capacity planning for systems of energy storage that would be incorporated to grid connected smart urban buildings.The research has been partially supported by the Faculty of Informatics and Management UHK excellence project “Methodological perspectives on modeling and simulation of hard and soft systems”