Abstract
This study’s primary goal is to evaluate the performance of a large thermal energy storage tank installed in a Gas District Cooling (GDC) plant. The performance parameters considered in this study include thermocline thickness (WTc), Cumulated Charge (Qcum), and Half Figure of Merit (½ FOM). The operation sensor data of a large Thermal Energy Storage (TES) tank was acquired for this analysis. The recorded temperature sensor from the 1st to 7th January and from 12th to 17th October 2019 was considered in this research. GraphPad prism computer software was deployed for analyses, and the temperature distribution data were analyzed to determine the four temperature parameters (hot water temperature (Th), cool water temperature (Tc), cool water depth (C), and slope gradient (S)) using a non-linear regression curve fitting technique and sigmoid Dose Responses function as integrated with the software. At the end of this research, the relationship between the growth of the determined performance parameter with charging hours was analyzed and presented. The research results proved the ability of GraphPad Prism software to assess the temperature distribution in the TES tank and also the corresponding effects on the overall Tank performance. The software offers better advantages in evaluating the performance parameter of the TES tank accurately.
Highlights
District Cooling System (DCS) is a smart solution that provides cooling energy within a centralized region
Joko’s analysis was based on a mathematical formulation that utilized the sigmoid Dose–Response equation. He concluded that the significant performance parameters, which include thermocline thickness, half-cycle Figure of Merit, and cumulative cooling capacity, could be accurately determined during the charging cycle of the Thermal Energy Storage (TES) tank
Data on the TES tank specification and the plant operations were extracted from the datasheet
Summary
District Cooling System (DCS) is a smart solution that provides cooling energy within a centralized region. Joko [12], in his research, accurately determined the performance parameters of a hot stratified Thermal Energy Storage tank by using the temperature distribution profile of an operating TES tank. Joko’s analysis was based on a mathematical formulation that utilized the sigmoid Dose–Response equation He concluded that the significant performance parameters, which include thermocline thickness, half-cycle Figure of Merit, and cumulative cooling capacity, could be accurately determined during the charging cycle of the TES tank. Analyzed in their study the thermal energy storage tank performance using thermocline thickness and half-cycle Figure of Merit. They obtained a temperature profile from simulating temperature as distributed in a TES tank by using a non-linear regression curve function and sigmoid Dose–Response. An hourly temperature dataset of the TES plant, from 1st to 7th January and from
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