Journal
ENERGY
Volume 133, Issue -, Pages 338-347Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2017.05.073
Keywords
Entropy generation; Monte Carlo; Optimization; Thermal energy storage; Transient thermal conduction
Categories
Funding
- National Natural Science Foundation of China [51136001, 51356001]
- Science Fund for Creative Research Groups [51321002]
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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. (C) 2017 Published by Elsevier Ltd.
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