A two-stage liquid desiccant dehumidification system by the cascade utilization of low-temperature heat for industrial applications

Bosheng Su, Wei Han, Jun Sui and Hongguang Jin

Applied Energy, 2017, vol. 207, issue C, 643-653

Abstract: Cooling dehumidification driven by power is widely used in industrial processes to obtain dry air, but the main drawback is its large power consumption. In these processes, large amounts of low-temperature waste heat are released to the environment directly, so there is a great energy-saving potential to recover low-temperature waste heat and generate dry air. A new two-stage liquid desiccant dehumidification system with the cascade utilization of low-temperature heat is proposed. The waste heat is used in a cascade manner. The higher-temperature heat is used to generate a strong desiccant solution, which will be used in the first-stage dehumidifier. The lower-temperature heat is used to drive a single-effect absorption refrigerator and provide cooling energy to the second-stage dehumidifier. Simulation results showed that the proposed system can reduce electricity consumption by 92.29% compared with the conventional cooling dehumidification system driven by power. The ratio of electricity savings to absorbed heat can reach 7.35%. The advantage of the cascade utilization of the low-temperature heat was further illuminated by studying the driving force in the dehumidifiers, and a preliminary economic and environmental analysis was performed. The increased initial investment can be recovered in only 3.39years. Approximately 11,028 tons of standard coal are saved per year, and a reduction of 27,488 tons CO2 can also be realized per year. Finally, a parametric sensitivity analysis was conducted to optimize the system performance. This study may provide a new method to perform dehumidification by efficiently using a low-temperature heat source.

Keywords: Low-temperature utilization; Liquid desiccant dehumidification; Power saving; Driving force difference; Economic and environmental analysis; Parametric analysis (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:207:y:2017:i:c:p:643-653

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DOI: 10.1016/j.apenergy.2017.05.184

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