2016
DOI: 10.1016/j.est.2016.10.006
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Energy model optimization for thermal energy storage system integration in data centres

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Cited by 14 publications
(3 citation statements)
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“…Today, thermal energy storage has become a crucial technology for solving the global energy crisis in the oil, gas, and electricity markets. The development of thermal energy storage engineering has contributed to the reduction of energy consumption and the stabilization of power supplies across various industries, including commercial air conditioning, , data center cooling, , battery cooling, , photovoltaics, , and thermoregulation. …”
Section: Introductionmentioning
confidence: 99%
“…Today, thermal energy storage has become a crucial technology for solving the global energy crisis in the oil, gas, and electricity markets. The development of thermal energy storage engineering has contributed to the reduction of energy consumption and the stabilization of power supplies across various industries, including commercial air conditioning, , data center cooling, , battery cooling, , photovoltaics, , and thermoregulation. …”
Section: Introductionmentioning
confidence: 99%
“…12 Others used the potential of more sophisticated optimization tools, such as Lin et al who used a genetic algorithm to optimize the design and operation of an LHTES system in a solar air system 13 and Oró et al, who used TRNSYS and GenOpt for the optimization of a TES system integrated in a data centre. 14 Yuksel et al, by the performance assessment of a solar towerbased multigeneration system, determines those factors that maximize the benefits from the integration of a TES system. 15 Although these approaches consider the overall performance of the application, they require a deep knowledge on the process and rely on complex simulations that are highly time-consuming.…”
Section: Introductionmentioning
confidence: 99%
“…In this way, Hübner et al determined, by parametric simulation, an optimum cross‐sectional geometry for a finned‐tube LHTES system integrated with a steam turbine 12. Others used the potential of more sophisticated optimization tools, such as Lin et al who used a genetic algorithm to optimize the design and operation of an LHTES system in a solar air system13 and Oró et al, who used TRNSYS and GenOpt for the optimization of a TES system integrated in a data centre 14. Yuksel et al, by the performance assessment of a solar tower‐based multigeneration system, determines those factors that maximize the benefits from the integration of a TES system 15.…”
Section: Introductionmentioning
confidence: 99%