热能储存
相变材料
储能
潜热
可再生能源
热的
核工程
传热
材料科学
化学
机械
热力学
工程类
电气工程
功率(物理)
物理
作者
Moucun Yang,Mohammad Moghimi Ardekani,R. Loillier,Christos N. Markides,Mohammadreza Kadivar
出处
期刊:Applied Energy
[Elsevier]
日期:2023-04-01
卷期号:336: 120848-120848
被引量:13
标识
DOI:10.1016/j.apenergy.2023.120848
摘要
Latent heat thermal energy storage (LHTES) systems using phase change materials (PCMs) have appeared as promising solutions for energy storage when harnessing renewable energy sources in a wide range of engineering applications. The present study focuses on the design of horizontal shell-and-tube PCM-based LHTES systems capable of simultaneous charging and discharging in solar domestic hot water (SDHW) applications. Two scenarios are investigated: (i) initially fully charged, and (ii) initially fully discharged LHTES systems, in both cases with a 30-min charge/discharge time interval. Configurations with key geometrical design variations are considered to identify the best radial and tangential positions of the heat transfer fluid (HTF) tubes inside the shell that enhance storage performance against the following criteria: (i) gained and released thermal power, and (ii) total gained and released energy per unit mass of PCM. The distance between the hot and cold HTF tubes was maintained constant and an LHTES with horizontally aligned HTF tubes was selected as a baseline case. The findings showed that tangential displacement had a considerable impact on the performance of the system, while the effect of radial displacement was marginal. A design with displacements of ¼ tube diameter and 90° in the radial and tangential positions of the HTF tubes, respectively, had promising performance in both considered scenarios. In comparison to the baseline case, which had the hot and cold tubes positioned horizontally, and symmetrically on the shell's central plane, this configuration demonstrated a 103.02% enhancement in energy delivery in the fully discharged and a 2% enhancement in the fully charged scenario, respectively.
科研通智能强力驱动
Strongly Powered by AbleSci AI