Development of a quasi-2D variable resistance–capacitance model for tube-encapsulated phase change material storage tanks. (September 2022)

• Record Type: Journal Article
• Authors: Wan, Hang; Xu, Xinhua; Xu, Tao; Yuen, Kwok Kit Richard; Huang, Gongsheng
• Is Part Of: Applied thermal engineering. Volume 214(2022)
• Publication Date: 2022-09
• Subjects: Thermal variable resistance and capacitance model -- Quasi-2D model -- PCM storage tank -- Heat transfer dynamics -- carbon neutrality; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2022.118868
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Continuous and differentiable functions of the PCM thermal properties are presented. A quasi-2D VRC model for the thermodynamic of PCM storage tanks is presented. The high computational efficiency and stability of the proposed model is presented. A brief structure of the heat transfer function of the PCM is presented. Abstract: Latent heat thermal energy storage (LHTES) always uses phase change materials (PCMs) as thermal storage medium, and has attracted research interests over the past decades due to its high energy storage density. Although many models have been developed for simulating the heat transfer of LHTES, such as CFD models and effectiveness-NTU models, they may suffer from high computational demand (CFD models) or cannot be applied to simulating partially charging/discharging (effectiveness-NTU models). Therefore, this paper presents the development and validation of a dynamic model for tube-capsulated PCM storage tanks, which is computationally efficient and simultaneously can simulate partially charging/ discharging of PCM storage tanks. The proposed model was built using a thermally variable resistance–capacitance (VRC) network in a quasi-two-dimension, thus titled as quasi-2D VRC model. The accuracy of the quasi-2D VRC model was investigated using two published experiments, and the mean absolute error was within 1.0 °C. Its computational efficiency was tested by comparing with an improved effectiveness-NTU model. The results showed that the computation time of the former was about 10% of the latter if the same precision was required. Therefore, the proposed model could find applications in real-time prediction, simulation and control of PCM storage tanks.