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

Esen H., Esen M., Ozsolak O.

JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, cilt.29, sa.1, ss.1-17, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 1
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1080/0952813x.2015.1056242
  • Dergi Adı: JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1-17
  • Anahtar Kelimeler: 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
  • Kayseri Üniversitesi Adresli: Hayır

Özet

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.