Determination of performance parameters of hot stratified thermal energy storage tank

Waluyo, Joko

doi:10.1109/inaes.2016.7821937

Cited by 4 publications

(6 citation statements)

References 3 publications

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“…The water temperature distribution was used to evaluate the effect of the re-established method on stratified TES tank operations. 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.…”

Section: Of 19mentioning

confidence: 99%

“…GraphPad prism computer software was used to process the temperature distribution data using a non-linear regression technique to determine the hot water temperature (Th), cool water temperature (Tc), cool water depth (C), and slope gradient (S) parameter. These determined parameters representing the S-curve temperature profile were used to analyze the TES tank's performance during the charging cycle [12,20]. Data used for the analysis in this research were acquired from a large district gas cooling plant with a remote sensor interval distance that records data every second.…”

Section: Of 19mentioning

confidence: 99%

“…This describes the capacity of stored energy during the charging cycle of a stratified thermal storage tank. Joko Waluyo [12] in his research formulated a mathematical expression (in Equation 12)to calculate the cumulative cooling capacity of a TES tank.…”

Section: Determination Of Cumulative Cooling Capacity Q Cummentioning

confidence: 99%

“…Temperature distribution in the TES tank can be used to observe stratified TES tanks for several purposes. These include performance evaluations, parametric studies, and characterization of the determination of mixing effects [12]. The stratification of the TES tank enables cold water to distinctively settle in the bottom layer, while warm water occupies the upper layer of the TES tank, forming an S-curve demarcation where the thermocline is created.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of a Thermal Energy Storage Tank in a Large District Cooling System: A Case Study

et al. 2020

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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.

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Section: Of 19mentioning

confidence: 99%

Section: Of 19mentioning

confidence: 99%

Section: Determination Of Cumulative Cooling Capacity Q Cummentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of a Thermal Energy Storage Tank in a Large District Cooling System: A Case Study

et al. 2020

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“…The methods are cycle thermal efficiency, half cycle figure of merit (FOM) and thermocline thickness [6,7,8,9]. …”

Section: Introductionmentioning

confidence: 99%

Evaluations of thermocline and half cycle figure of merit of a thermal energy storage tank

Majid

Kin

2017

MATEC Web Conf.

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Abstract. Two main criteria that are commonly used to evaluate thermal energy storage systems are thermocline thickness and half cycle figure of merit. For the thermocline thickness, the preference is to achieve as thin as possible the thermocline thickness. While the preference for half cycle figure of merit is to achieve the value of greater than 90 per cent. These two criteria were used to evaluate a thermal storage system at University Teknologi PETRONAS district cooling plant. The capacity of the thermal energy storage tank of the plant is 10,000 RTh. Operating data was used for the evaluation. The values of evaluated thermocline thickness ranges from 2.248 meters to 5.445 meters with an average of 3.251 meters. These values are very much higher in comparison to findings of other studies. One possible reason is due to higher flow rates. For the half cycle figure of merit the evaluated values ranges from 0.9469 to 0.9847, with the average of 0.9698, which are within the acceptable range. For future work a model should be developed which could automatically evaluate both the thermocline thickness and half cycle figure of merit. This would enable both of these parameters to be continuously evaluated.

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Can heat pump heat storage system perform better for space heating in China’s primary schools? A field test and simulation analysis

Deng

Peng

Qiang

et al. 2023

Energy and Buildings

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Determination of performance parameters of hot stratified thermal energy storage tank

Cited by 4 publications

References 3 publications

Analysis of a Thermal Energy Storage Tank in a Large District Cooling System: A Case Study

Analysis of a Thermal Energy Storage Tank in a Large District Cooling System: A Case Study

Evaluations of thermocline and half cycle figure of merit of a thermal energy storage tank

Can heat pump heat storage system perform better for space heating in China’s primary schools? A field test and simulation analysis

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