Modelling and experimental performance analysis of solar-assisted ground source heat pump system

被引：339
|
作者：
Esen, Hikmet [1 ]
Esen, Mehmet [1 ]
Ozsolak, Onur [2 ]
机构：
[1] Firat Univ, Fac Technol, Dept Energy Syst Engn, Elazig, Turkey
[2] Cumhuriyet Univ, Fac Technol, Dept Mfg Engn, Sivas, Turkey
来源：
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE | 2017年 / 29卷 / 01期
关键词：
Solar energy; ground source heat pump; artificial neural network; adaptive neuro-fuzzy inference system; ARTIFICIAL NEURAL-NETWORK; VERTICAL TEMPERATURE PROFILES; BOREHOLE RESISTANCE; THERMAL PERFORMANCE; EXCHANGERS; ENERGY; ANFIS; ANN;
D O I：
10.1080/0952813X.2015.1056242
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this study, slinky (the slinky-loop configuration is also known as the coiled loop or spiral loop of flexible plastic pipe)type ground heat exchanger (GHE) was established for a solar-assisted ground source heat pump system. System modelling is performed with the data obtained from the experiment. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used in modelling. The slinky pipes have been laid horizontally and vertically in a ditch. The system coefficient of performance (COPsys) and the heat pump coefficient of performance (COPhp) have been calculated as 2.88 and 3.55, respectively, at horizontal slinky-type GHE, while COPsys and COPhp were calculated as 2.34 and 2.91, respectively, at vertical slinky-type GHE. The obtained results showed that the ANFIS is more successful than that of ANN for forecasting performance of a solar ground source heat pump system.
引用
收藏
页码：1 / 17
页数：17
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