Performance of the air source heat pump assisted solar heating system combined with PCM floor

Zheng, Xuejing; Tang, Zhiyun; Wang, Yaran; Liu, Huzhen

doi:10.1016/j.applthermaleng.2023.122115

Cited by 18 publications

(1 citation statement)

References 21 publications

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“…The unit energy consumption of the EB system was considerably higher than that of the heating system with AHP as the heat source. This was because EB needed to consume electricity completely, and AHP had the ability to save energy (Zheng et al, 2024). Among them, the energy consumption of the AHP system in Nanjing was 72.17% lower than that of the EB system.…”

Section: Energy Consumption Analysismentioning

confidence: 99%

Research on the optimization of the clean heating system for regional residential buildings based on the multi-objective optimization strategy

Fu,

Wang,

Long

2024

Front. Energy Res.

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For the residential building district heating (RBDH) system, choosing the appropriate combination of heat sources according to local conditions is the key to improving economic efficiency. In this study, three climatic regions in China were selected, namely, a hot summer and cold winter region, cold region, and severe cold region. Among them, Nanjing, Tianjin, and Shenyang were selected as typical representative cities in the hot summer and cold winter region, cold region, and severe cold region, respectively. Taking the levelized cost of heat (LCOH) as the economic evaluation index and considering the carbon emission cost of the system operation, the energy consumption and the CO2 emissions were analyzed. TRNSYS software was used to simulate and analyze the system performance. The multi-objective optimization based on a genetic algorithm was proposed to optimize system parameters. From an economic point of view, the SA system was suitable for the hot summer and cold winter region, the SAS system was suitable for the cold region, and the SE system was suitable for the severe cold region. The operation control strategy based on quality adjustment can reduce heating energy consumption and maintain indoor temperatures at approximately 20°C. The proportion of clean energy heating in the optimized heating system decreased after the multi-objective optimization strategy. However, the initial investment and maintenance costs of the system were reduced, which reduced the LOCH of the system. Therefore, the multi-objective optimization strategy can effectively reduce the heating costs.

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Section: Energy Consumption Analysismentioning

confidence: 99%