In order to further improve the utilization efficiency of solar energy, a solar coupled multi-heat source heat pump （SMSHP） drying system was proposed based on the solar coupled air source heat pump （SASHP） drying system. The simulation model of the SMSHP drying system was constructed using the TRSNYS simulation software. The system performance of the air source heat pump （ASHP） drying system, the SASHP drying system, and the SMSHP drying system in autumn were analyzed for drying 75 kg wolfberry in Xining of Qinghai Province, and the tank heating guarantee rate of the SASHP drying system and the SMSHP drying system was calculated. Moreover, the interaction effects of component parameters on the SMSHP drying system were also investigate, and the particle swarm optimization algorithm was utilized to optimize the life-cycle cost of the SMSHP drying system. The results show that, compared to the ASHP and SASHP drying systems, the system performance of the SMSHP drying system in a typical autumn day was increases by 67.19% and 21.35%, respectively, and the energy consumption is reduced by 32.02% and 10%, respectively. The order of influence of component parameters on the SMSHP system is solar collector area, water tank volume, heat pump power, collector tilt angle, and the matching degree between the solar collector area and the water tank volume as well as between the solar collector area and the heat pump power should be considered in the optimization process. After optimization, the solar collector area is 26.7 m2, the water tank volume is 1.97 t, the collector tilt angle is 43.2°, and a heat pump power is 8.75 kW. The optimal ratio of the solar collector area to the water tank volume is 73 L/m2, and the solar collector area to the heat pump power is 0.33 kW/m2. After optimization, the cost of installation and single drying operation of the system is reduced by about 16.09% and 6.56% respectively. Compared with the SASHP drying system, the installation and single drying operation costs of the optimized system are reduced by about 13.31% and 12.91%, respectively.
Key words
drying /
air source heat pump /
solar collector /
TRNSYS /
particle swarm optimization algorithm
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