Parameter analysis and optimization of the energy and economic performance of solar-assisted liquid desiccant cooling system under different climate conditions

Abstract Operation conditions significantly affect the energy and economic performance of solar-assisted liquid desiccant cooling systems. This study optimized the system control parameters for buildings in different climates, i.e., Singapore (hot and humid), Beijing (moderate) and Boulder (hot and dry), with a multi-parameter optimization based on the Multi-Population Genetic Algorithm to obtain optimal system performance in terms of relatively maximum electricity saving rate with a minimum cost payback period. The results indicated that the selection of operation parameters is significantly influenced by climatic conditions. The solar collector installation area exhibited the greatest effect on both energy and economic performance in humid areas, and the heating water flow rate was also important. For dry areas, a change in desiccant concentration had the largest effect on system performance. Although the effect of the desiccant flow rate was significant in humid cities, it appeared to have little influence over buildings in dry areas. Furthermore, the requirements of the solar collector installation area in humid areas were much higher. The optimized area was up to 70 m2 in Singapore compared with 27.5 m2 in Boulder. Similar results were found for the flow rates of heating water and the desiccant solution. Applying the optimization, humid cities could achieve an electricity saving of more than 40% with a six-year payback period. The optimal performance for hot and dry areas of a 38% electricity saving with a payback period of 14 years was also acceptable. The results facilitate anyone faced with choosing suitable operational parameters under different climate conditions.