Dynamic modeling of solar-assisted ground source heat pump using Modelica

被引:23
|
作者
Chen, Yongbao [1 ,2 ]
Chen, Zhisen [3 ]
Chen, Zhe [1 ]
Yuan, Xiaolei [3 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China
[2] Shanghai Key Lab Multiphase Flow & Heat Transfer, Shanghai 200093, Peoples R China
[3] Tongji Univ, Sch Mech & Energy Engn, Shanghai 201804, Peoples R China
基金
中国博士后科学基金;
关键词
Ground source heat pump; Solar-assisted energy storage; Demand response; Dymola simulation; ENERGY-STORAGE; RESIDENTIAL BUILDINGS; DEMAND FLEXIBILITY; SYSTEM; PERFORMANCE; OPTIMIZATION; COLLECTORS;
D O I
10.1016/j.applthermaleng.2021.117324
中图分类号
O414.1 [热力学];
学科分类号
摘要
Traditional rural energy sources, such as straw, firewood, and coal are the main energy resources in developing countries; however, these resources are associated with low efficiency and can cause considerable air pollution. With the rapid development of renewable energy worldwide, existing energy frameworks in rural areas need to be urgently transformed. Developing a universal and reliable dynamic modeling framework for multi-source heat pumps remains an unresolved issue. To this end, this paper proposes an integrated energy system based on a solar-assisted ground source heat pump (SGSHP), which can facilitate the utilization of renewable energy, reduce the electricity consumption, and provide demand response (DR) resources in rural houses. A 150-m2 rural house on the outskirts of Shanghai, China was considered as a case building. A novel Dymola modeling framework of an SGSHP system was established, and the heating performance was analyzed. Considering the variation in the energy demand in winter, four practical operation modes were implemented to maximize energy efficiency. The results show that the coefficients of performance of the system are 4.2 and 3.5 with and without solar collectors, respectively. The contributions of solar energy, geothermal heat, and electricity in the system are 27%, 18%, and 55%, respectively. Moreover, approximately 79.6% of AC loads can be shaved during evening peak load time in our proposed energy system.
引用
收藏
页数:14
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