Experimental investigation of the temperatures and performance of a commercial ice-storage tank

López-Navarro, A.; Biosca-Taronger, J.; Torregrosa-Jaime, Bárbara; Martínez-Galván, I; Corberán, José M.; Esteban-Matías, J.C.; Payá, J.

doi:10.1016/j.ijrefrig.2012.09.008

Cited by 30 publications

(18 citation statements)

References 15 publications

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“…The mathematical model presented in Section 3 was verified using experimental results available in [33,34], which have been obtained with the ice-based tank model ICEBANK 1098C [35]. Parameters for a single tube are provided in Table 2.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…A special tank setup is used in [33,34] to carry out the experiments, where the top 16 levels out of the total 34 are blocked and the HTF circulates through the bottom 18 levels only, which are submerged in water. The total volume of water of the tank is V w = 3710 L [35] and the partial mass of water/ ice is approximately m w = 1876 kg; this implies an effective volume of V w,e = 1876 L = 1.876 m 3 (nearly half of the volumetric capacity) [33].…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…As in Experiment 1, temperature information has 4 Comparison between experimental and simulated mean cooling power. The small notch presented in P e,a at 110 min comes from the experimental results in [33] For completeness, the charging process as reported in [34], incidentally adopting the same tank setup as in the discharging experiments, was replicated here with the simulation model. A vapour-compression chiller system supplies the cold HTF.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The tank model was implemented in MATLAB/Simulink to analyse different operating conditions, including charging and discharging processes. To verify the validity of the model, simulation results are compared against experimental results reported in [33,34], where a specific ice-based tank configuration is presented but no mathematical model of the storage tank is included.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic modelling of ice‐based thermal energy storage for cooling applications

Bastida

Ugalde‐Loo

Abeysekera

et al. 2022

IET Energy Syst Integration

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The development of accurate dynamic models of thermal energy storage (TES) units is important for their effective operation within cooling systems. This paper presents a one‐dimensional discretised dynamic model of an ice‐based TES tank. Simplicity and portability are key attributes of the presented model as they enable its implementation in any programing language which would, in turn, facilitate the simulation and analysis of complex cooling systems. The model considers three main components: energy balance, definition of the specific heat curve, and calculation of the overall heat transfer coefficient. An advantage of the model is that it can be adapted to other types of TES units employing phase change materials. The modelling approach assumes equal flow and temperature distribution in the tank and considers two internal tubes only to represent the whole tank—significantly reducing the number of equations required and thus the computation time. Thermophysical properties of water during the phase change and of the heat transfer fluid are captured. The ice‐based TES tank model has been implemented in MATLAB/Simulink. A good agreement between simulation results and experimental data available in the literature has been achieved—providing confidence in the validity of the mathematical model.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic modelling of ice‐based thermal energy storage for cooling applications

Bastida

Ugalde‐Loo

Abeysekera

et al. 2022

IET Energy Syst Integration

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“…The better overall efficiency was obtained at the lowest supplied temperatures and mass flow rates. Lopez-Navarro et al [5,6] performed an experimental analysis of an internal melt-ice-on-coil system. The total refrigeration capacity of the installed set-up was 172 kWh.…”

Section: Introductionmentioning

confidence: 99%

Numerical Modeling of the Melting Process in a Shell and Coil Tube Ice Storage System for Air-Conditioning Application

et al. 2019

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Cold thermal energy storage, as a promising way of peak-shifting, can store energy by using cheap electricity during off-peak hours and regenerate electricity during peak times to reduce energy consumption. The most common form of cold storage air conditioning technology is ice on the coil energy storage system. Most of the previous studies so far about ice on coil cold storage system have been done experimentally. Numerical modeling appears as a valuable tool to first better understand the melting process then to improve the thermal performance of such systems by efficient design. Hence, this study aims to simulate the melting process of phase change materials in an internal melt ice-on-coil thermal storage system equipped with a coil tube. A three-dimensional numerical model is developed using ANSYS Fluent 18.2.0 to evaluate the dynamic characteristics of the melting process. The effects of operating parameters such as the inlet temperature and flowrate of the heat transfer fluid are investigated. Also, the effects of the coil geometrical parameters—including coil pitch, diameter, and height—are also considered. Results indicate that conduction is the dominant heat transfer mechanism at the initial stage of the melting process. Increasing either the inlet temperature or the flowrate shortens the melting time. It is also shown that the coil diameter shows the most pronounced effect on the melting rate compared to the other investigated geometrical parameters.

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A Computational Study on Utilizing Phase Change Material With a Condenser to Improve air Conditioning System Performance

Sao,

Arora,

Sahu

2024

Energy Storage

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The efficacy of employing multiple cylindrical phase change materials (PCM) to enhance the performance of an air conditioning (AC) unit is examined in this study. The objective of the present study is to examine the effects of combining an AC unit with a cylindrical PCM container configuration on the PCM discharge process and the performance of the AC system. The procedure involves the connection of a heat exchanger with a cold energy storage PCM to the condenser of the AC. During the daytime, the warm surrounding air is cooled and then transmitted to the AC unit's condenser. Four different turbulence models, that is, the SST , standard , Realizable and RNG have been considered for the present computational study. The investigation has been performed for different air flow rates, that is, 33.6, 42, and 49 for a constant inlet air temperature of 308.15 K. The present outcomes indicate that as the flow rate rises, the air temperature inside the domain increases and the solid PCM starts melting. It is noted that complete discharging time for multi‐cylindrical PCM reduces as the air flow rate rises which are around 13.36, 11.03, and 9.94 h for airflow rates of 33.6, 42, and 49 , respectively. The maximum achieved increase in the COP is around 94.49%, 88.68%, and 87.57% at airflow rates of 33.6, 42, and 49 L/s, respectively, for the multi‐cylindrical PCM throughout the summer. It is found that for the same temperature, as the airflow rate rises, the consumed power saving rises.

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Experimental investigation of the temperatures and performance of a commercial ice-storage tank

Cited by 30 publications

References 15 publications

Dynamic modelling of ice‐based thermal energy storage for cooling applications

Dynamic modelling of ice‐based thermal energy storage for cooling applications

Numerical Modeling of the Melting Process in a Shell and Coil Tube Ice Storage System for Air-Conditioning Application

A Computational Study on Utilizing Phase Change Material With a Condenser to Improve air Conditioning System Performance

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