GSHP Analysis

Optimization of GSHP and GHX is a wide research area and many optimization models are proposed [6-29]. Some are focused on control and operational strategy of GSHP system [6-7, 9-10, 12-13 16]. Gao et al. [18] optimized the control strategy of an air-conditioning integrated GSHP system and obtained the reductions of energy consumption in summer. Gang et al. [19] proposed suitable operating strategies to control a hybrid energy system consisted of GSHP and a cooling tower. An artificial neural network (ANN) was used to predict the dynamic variation in fluid temperature of a ground loop. Fannou et al. [20] carried out the modeling and optimization of DXGSHP by using ANN for enhancing the efficiency of the system. They found that in the heat pump
Zhou et al [21] optimized the performance of GSHP system through TRNSYS simulation. Sivasakthivel et al. [22] proposed optimum parameters of a GSHP system for both cooling and heating operations. Zeng et al. [23] used the multi-population genetic algorithm (MPGA) to optimize the operation and capacity strategy for CCHP–GSHP coupling system, resulting in excellent energy-saving and cost-saving effect in a case study. Esen et al. [24] utilized Taguchi method to optimize the GSHP system and concluded that the depth of borehole is the most significant parameter.
Even though many studies have been conducted with the aim of investigating and evaluating GSHP, still more studies are needed to understand the performance of GHX when GSHP is used for both cooling and heating applications. Some of the researchers [8, 10-11, 13-14, 17] are carried out optimization of horizontal and vertical ground-coupled heat pump system to reduce the cost of the system. Gang and Wang [25] applied static and dynamic models of ANN to predict the exit temperature of GHX. They concluded that compared to static model; the dynamic model was able to predict
[31] presented an optimization methodology for horizontal GHX’s based on energy conservation and heat transfer principles. Modeling of a slinky loop GHX was carried out by Esen et al. [32] using ANN and adaptive neuro-fuzzy interface system. Verma and Murugesan [33] carried out optimization of the length of GHX and area of collector for better COP of SAGSHP system. They estimated the reduction in the solar collector area and length of GHX was around 2.5% and 1.6% respectively. Wang et al. [34] studied the effect of groundwater flow on heat transfer process in a spiral coil pile GHX. It is found that heat transfer rate can be increased by an increase in ground water flow. When conducting an optimization that determines how much heat should be generated by GHX, it needs to compare many combinations of operations. Due to this, optimization problems that involve GHX along with GSHP operation cannot be solved easily. One of the best methods is Taguchi optimization. This technique is used in many applications like civil engineering, manufacturing, and thermal engineering, etc [35-41]. In this paper, an attempt will be made to apply Taguchi technique to optimize the GHX parameters for ground source heat pump