The likelihood evaluation of the heat exchanger unit model design method in the ground source heat pump system utilizing heat exchanger piles

A ground source heat pump system (GSHP) utilizing the foundation piles as heat exchangers is expected to reduce the initial cost compared with the borehole type of the conventional system because the heat exchanger piles is not needed to install anew. However, the arrangement of the piles is depend on the floor layout of a residence. Therefore, the thermal performance prediction of heat exchange piles has to strictly conduct three-dimensional analysis for every residence. Conducting such analysis, it is a heavy burden for a designer to perform performance prediction of the GSHP with satisfaction of the annual heating and cooling demand. Then, the two- dimensional heat unit model was proposed in order to ease a designer´s burden. This model has the characteristic of originally not using the soil portion where the ground heat source is available. And if it is seemed to be the design likelihood, it makes the designer´s load reduce. The introductory possibility of the GSHP, which uses the foundation pile in the semi-cold district of our country, is shown by the numerical analysis using this model. It is necessary to show clearly how much the analytical results calculated by use of this model has likelihood. Then, as compared with the higher-dimensional analysis results, the same heating demand conditions are employed at the thermal prediction. The rectangular and triangle arrangements of piles are inquired for the evaluations. The finite difference method is employed for the numerical analysis. It is shown that the evaluation using the proposed model has an average of 10 - 50% of likelihood compared with the higher dimensional analysis evaluation when single layer of piles surrounds the center piles. In the case of the arrangements in which multi layers of piles surround the center piles, the proposed thermal unit model leads the same analytical results by use of higher dimensional coordinates model.