为进一步提高太阳能利用率,基于太阳能耦合空气源热泵（SASHP）干燥系统,提出太阳能耦合多热源热泵（SMSHP）干燥系统,利用TRSNYS仿真软件搭建SMSHP干燥系统的仿真模型,并对比分析空气源热泵（ASHP）干燥系统、SASHP干燥系统、SMSHP干燥系统在青海西宁地区秋季干燥75 kg枸杞的系统性能以及SASHP干燥系统与SMSHP干燥系统水箱供热保证率,同时对SMSHP干燥系统的部件参数的交互影响进行分析,并利用粒子群优化算法对SMSHP干燥系统生命周期成本进行优化。研究表明：秋季典型日SMSHP干燥系统相较于ASHP、SASHP干燥系统的性能分别提升67.19%、21.35%,能耗分别降低32.02%、10%;部件参数对SMSHP系统影响的先后顺序为太阳能集热器面积-水箱体积-热泵功率-集热器倾角,优化过程中要考虑集热器面积与水箱体积、集热器面积与热泵功率的匹配度;优化后系统集热器面积为26.7 m2、水箱体积为1.97 m3、集热器倾角为43.2°、热泵功率为8.75 kW,集热器面积与水箱体积的最佳比值为73 L/m2,集热器面积与热泵功率的最佳比值为0.33 kW/m2,优化后系统的安装与单次干燥运行成本分别降低了约16.09%、6.56%;与SASHP干燥系统相比,优化后系统的安装与单次干燥运行成本分别降低了约13.31%、12.91%。
Abstract
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.
关键词
干燥 /
空气源热泵 /
太阳能集热器 /
TRNSYS /
粒子群优化算法
Key words
drying /
air source heat pump /
solar collector /
TRNSYS /
particle swarm optimization algorithm
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基金
河南省自然科学基金（222300420375）; 河南省高等学校重点科研项目（23A470014）
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