期刊
APPLIED ENERGY
卷 306, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.118012
关键词
Thermoelectric generator; Output power; Computational fluid dynamics (CFD); Reynolds number; Plate fins; Waste heat recovery
资金
- Ministry of Science and Technology, Taiwan, R.O.C. [MOST 110-2221-E-006-145-MY3, MOST 110-2622-E-006-001-CC1]
Utilizing low-temperature waste heat for power generation is a promising method, and the study shows that the number of partitions in a thermoelectric module does not significantly affect its performance. The installation of fins greatly intensifies heat transfer and improves the performance of thermoelectric modules.
Low-temperature waste heat has great potential for renewable power because it accounts for around 60% of total industrial waste heat. This study develops a model of integrating thermoelectric generation, computational fluid dynamics, and plate fins to figure out a low-temperature waste heat recovery system for power generation. The effect of the number of partitions of a thermoelectric module on its performance is examined, and the results show that a single module without a partition can provide accurate predictions. Four different combinations between wastewater and air in the hot and cold channels under three different Reynolds numbers (i.e., Re = 10, 100, and 1,000) on thermoelectric modules' performance suggest that only combining hot wastewater and cooling water can contribute electricity to a certain extent. By installing fins with a number range of 0-27, it indicates that fin installation can dramatically intensify heat transfer and thermoelectric modules' performance. The optimal number of fins at Re = 10 and 100 is 21, whereas it is 27 at Re = 1,000. The maximum total output power and mean conversion efficiency are 0.411 W and 0.95%, respectively, with 27 fins at Re = 1,000. These values account for 105.5% and 43.94% improvements when compared to the TEMs without fins. Even though installing fins increases the pressure drop in the channel, its value is much smaller than the generated power (less than1%). The developed method in this study can be used to efficiently and accurately predict the performance of thermoelectric modules, and obtained results have provided practical insights into the design of low -temperature waste heat recovery systems for green power generation.
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