Experimental Investigation of Energy and Exergy Performance of Ground Source Heat Pump Systems under Turbulent and Laminar Flow Regimes
摘要
An experimental study was conducted to investigate the impact of variations in cooling water flow rate and flow regime on the operational characteristics of a ground source heat pump (GSHP) system. An experimental platform for the system was set up, and energy and exergy analyses of the system were performed under cooling mode. The results indicate that, in the energy analysis, when the cooling water flow rate is between 1.2 m3/h and 2.6 m3/h, corresponding to a turbulent flow state, the system’s coefficient of performance (COP) reaches its highest range of 3.32 to 3.20, and the system’s heat loss rate remains within a lower range of 4.93% to 5.71%. In the exergy analysis, the optimal range for the cooling water flow rate is 0.4 m3/h to 1.2 m3/h, corresponding to the laminar and initial turbulent flow stages, during which the system’s exergy loss is the lowest and the exergy efficiency is the highest. The optimal cooling water flow rate obtained through energy and exergy analysis is 1.2 m3/h, corresponding to a flow velocity of 0.16 m/s. Compared to the system’s exergy efficiency under the most unfavorable flow conditions, there is an improvement of 118.2% in exergy efficiency and a reduction of 38.7% in exergy loss. Using thermodynamic perfectibility as the primary evaluation criterion, among the main equipment in the system, the heat pump unit exhibits the lowest thermodynamic perfection of only 18.08%. Its exergy efficiency, at 28.17%, is also relatively low, and it has the highest exergy loss rate, reaching 77.14%. Consequently, the heat pump unit is identified as the primary target for improvement. Based on the comprehensive evaluation of exergy indices and thermodynamic perfectibility, the order of improvement potential for components within the system and heat pump unit is: evaporator > buried pipe > fan coil > condenser > compressor > expansion valve. This provides valuable insights for the optimization design of GSHP systems.