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

页码：1 / 17

页数：17

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