Performance Analysis and Optimization of SHS Based on Solar Resources Distribution in Typical Cities in Cold Regions of China

Juan Zhao (), Yifei Bai, Botao Zhou, Junmei Gao, Tianwei Qiang, Suqian Yan and Pei Liang ()
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Juan Zhao: Engineering Research Center of Building Energy Efficiency Control and Evaluation, Ministry of Education, Anhui Jianzhu University, Hefei 230601, China
Yifei Bai: School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi’an 710048, China
Botao Zhou: School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi’an 710048, China
Junmei Gao: School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi’an 710048, China
Tianwei Qiang: School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi’an 710048, China
Suqian Yan: School of Urban Planning and Municipal Engineering, Xi’an Polytechnic University, Xi’an 710048, China
Pei Liang: College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China

Energies, 2022, vol. 15, issue 20, 1-13

Abstract: The variability and inhomogeneity of solar energy limits the development of solar heating systems (SHS) in many fields. In order to improve the utilization efficiency of SHS, this paper takes three typical cities (Xi’an, Dunhuang, Lhasa) as the research object, studies the operation state of SHS in student dormitory buildings, and puts forward a corresponding optimization strategy. The research shows that the reduction of water supply temperature will improve the operation efficiency and energy saving effect of a spontaneous combustion heat pump and that there is an optimal volume of heat storage water tank (HSWT), which can make the energy saving effect of SHS run better. The optimization of the SHS shows the water supply temperature is 35 °C, and the optimal volume of HSWT is 15 m 3 in the “Resource-general area (Ⅲ)” represented by Xi’an, 25 m 3 in the “Resource-rich area (Ⅱ)” represented by Dunhuang, and 40 m 3 in the “Resource-richer area (Ⅰ)” represented by Lhasa. With the increase in the abundance of solar energy resources in the region, the optimal volume of HSWT also increases. Meanwhile, the solar energy contribution rate of the three regions in descending order is 61.3% (Lhasa), 32.8% (Dunhuang), and 25.9% (Xi’an). After optimization, the contribution of SHS increased by about 5%. The research results will help improve the efficiency of SHS in cold areas of China and make the system more efficient and energy efficient during operation.

Keywords: solar heating; energy performance; optimization strategy; dynamic simulation; contribution rate of solar energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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