Sensitivity analysis and optimization of design parameters of heating tower heat pump. (15th April 2022)

• Record Type: Journal Article
• Authors: Xie, Lingyun; Zhang, Muxing; Huang, Shifang; Zhao, Shanguo; Zhang, Xiaosong
• Is Part Of: Energy conversion and management. Volume 258(2022)
• Publication Date: 2022-04-15
• Subjects: Heating tower heat pump -- Design parameters -- Sensitivity analysis -- Optimal design -- Large-scale simulation; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2022.115547
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A framework is established for design optimization of heating tower heat pumps. Design optimizations of systems in different climate regions are obtained. Mean outdoor relative humidity during winter operations is the key role. 3.81–9.91% lifecycle costs can be saved compared with the current level. Abstract: Heating tower heat pumps (HTHPs) are evolving rapidly owing to their high performance and adaptability. However, the lack of relevant design standards causes mismatches between components and leads to low operation efficiency. To address this problem, this study proposes a framework to optimize the design parameters of HTHPs. Case studies in 21 locations in different climate regions are carried out to investigate the saving in energy and costs. The results suggest that an increase in the design airflow flux ( G a ), solution flow flux ( G s ), water flow flux ( G w ), or heat exchange area of the tower ( A ) can improve the performance of the heat pump unit and reduce the regeneration load. However, they can increase the energy consumption of the fan and pump, or the initial cost of the components. Considering 10-year lifecycle costs as the criterion, the optimal combination of G a, G s, G w, and A is determined from 15, 625 matrices with varying design parameters for each location. For the locations whose mean relative humidity (MRH) is approximately 70% during winter operations (e.g., Nanjing and Shanghai), the optimal design approach and range in winter are approximately 2.6 and 2.9 °C, respectively; these change to 4.7 and 6.6 °C in summer conditions. The G s and G w are 3.26 and 3.24 kg m −2 s −1, respectively, and G a is 1.08 kg m −2 s −1 in summer and 2.94 kg m −2 s −1 in winter. The areas with MRH around 80% (e.g., Chongqing and Changsha) should have larger G a and A, and lower G s in winter, which can significantly reduce the energy used in regeneration. The regions with MRH less than 65% (e.g., Tianjin and Beijing) should have smaller G a and A, and higher G s in winter, which can reduce the negative effects of evaporative cooling. Compared with the conventional design parameter matrices, the optimal ones can save 7.01%, 9.91%, and 3.81% lifecycle costs, respectively, in the above three types of climate regions.