Optimizing the solar-air hybrid source heat pump heating system based on the particle swarm algorithm

• DOI: 10.1016/j.egyr.2022.05.098
• Publication Date: 2022-05-30T15:57:56Z
• Authors: Zhiguo Wang; Haoyu Chen; Xiao Sun; Haibing Lu; Tianyi Wang
• Keywords: TRNSYS; Concentrated solar power; Heating system

In order to deal with the increasingly severe energy situation and climate change, reducing global carbon emissions developing new have become a universal consensus among countries in world. The design of clean heating systems such as solar collectors (SC) air source heat pumps (ASHP) has also received widespread attention. However, optimizing multiple parameters that interact each other hybrid solar-air (HSHP) is still challenging, optimization remains be studied. By using TRNSYS simulation platform, modify performance decrease system's annual cost particle swarm (PSO) coordinate search method (CSM), respectively. results show two algorithms can significantly enhance system performance, where it easier for PSO find optimum, average index COPsys about 15% higher than CSM, power consumption could lowered by 27.75%; addition, matching principle key proposed sensitivity ranking optimized derived. These offer theoretical foundations optimal HSHP system.