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Transient thermal conduction optimization for solid sensible heat thermal energy storage modules by the Monte Carlo method

Author

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  • Hua, Yu-Chao
  • Zhao, Tian
  • Guo, Zeng-Yuan

Abstract

The demand for more efficient energy utilization is leading to the need for efficient thermal energy storage (TES) systems. High temperature, low thermal conductivity concrete has been widely used in solid TES modules. The thermal conduction in concrete is improved by adding a fixed amount of high thermal conductivity materials into the original material with the characteristic time for thermal storage and release from the system as the optimization objective. Here, this transient thermal conduction optimization problem was solved using a Monte Carlo (MC) method with the simulated annealing algorithm. The optimal thermal conductivity distribution should be approximately a piecewise function whose configuration depends on the amount of the additional high conductivity material and the thermal conductivity ratio between the upper and lower bounds of the thermal conductivity within the TES module. A more practicable design with a multi-region distribution of thermal conductivity was proposed for more efficient energy storage and release. The MC results showed the optimization criterion can be the temperature gradient uniformity, that is, the shortest characteristic time corresponds to a uniform temperature gradient distribution. For comparison, the system was analyzed using the entropy generation which shows the minimum entropy generation does not optimize transient thermal conduction.

Suggested Citation

  • Hua, Yu-Chao & Zhao, Tian & Guo, Zeng-Yuan, 2017. "Transient thermal conduction optimization for solid sensible heat thermal energy storage modules by the Monte Carlo method," Energy, Elsevier, vol. 133(C), pages 338-347.
  • Handle: RePEc:eee:energy:v:133:y:2017:i:c:p:338-347
    DOI: 10.1016/j.energy.2017.05.073
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    Cited by:

    1. Wanruo Lou & Lingai Luo & Yuchao Hua & Yilin Fan & Zhenyu Du, 2021. "A Review on the Performance Indicators and Influencing Factors for the Thermocline Thermal Energy Storage Systems," Energies, MDPI, vol. 14(24), pages 1-19, December.
    2. Xiangqian Xu & Zhexuan Zhou & Yajie Dou & Yuejin Tan & Tianjun Liao, 2018. "Sustainable Queuing-Network Design for Airport Security Based on the Monte Carlo Method," Sustainability, MDPI, vol. 10(2), pages 1-19, January.
    3. Haiyuan Yang & Li Zhang & Ronghe Liu & Xianli Wen & Yongfei Yang & Lei Zhang & Kai Zhang & Roohollah Askari, 2019. "Thermal Conduction Simulation Based on Reconstructed Digital Rocks with Respect to Fractures," Energies, MDPI, vol. 12(14), pages 1-13, July.

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