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Review

Variable Water Flow Control of Hybrid Geothermal Heat Pump System

by
Ji-Hyun Shin
1,
Hyo-Jun Kim
2,
Han-Gyeol Lee
3 and
Young-Hum Cho
4,*
1
Sustainable Planning Division, EnertecUnited, Busan 48059, Republic of Korea
2
Institute of Industrial Technology, Yeungnam University, Gyeongsan 38541, Republic of Korea
3
Department of Architecture, Graduate School of Yeungnam University, Gyeongsan 38541, Republic of Korea
4
School of Architecture, Yeungnam University, Gyeongsan 38541, Republic of Korea
*
Author to whom correspondence should be addressed.
Energies 2023, 16(17), 6113; https://doi.org/10.3390/en16176113
Submission received: 31 May 2023 / Revised: 3 August 2023 / Accepted: 19 August 2023 / Published: 22 August 2023
(This article belongs to the Section G: Energy and Buildings)
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Abstract

:
Ground heat accumulation caused by imbalanced heating and cooling loads in a building can cause the heat-source temperature to increase as the operating age of a geothermal heat pump (GHP) system increases. An alternative system to improve upon this situation is the hybrid GHP system. This study reviews existing research on GHP systems and hybrid GHP systems, variable water flow (VWF) control, and coefficient of performance (COP) prediction. Generally, constant flow control is applied to the circulating pump to provide a flow rate according to the maximum load. The need for VWF control was identified because the hybrid GHP system is used mainly as a heating and cooling heat source system for partial loads rather than the entire building load. Previous studies on predicting the COPs of GHP systems developed prediction models by selecting input values based on mathematical models, collecting data through multiple measurement points, and utilizing data from production environments. The model can be limited by the field environment, and it is necessary to predict the COP using machine learning based on existing field monitoring data.

1. Introduction

The importance of energy savings is gaining traction as the need to reduce greenhouse gas emissions increases worldwide [1]. The building sector, which accounts for 30% of total energy consumption, is trying to reduce energy through various measures [2]. Therefore, a certain percentage of energy must be generated from renewable energy to reduce energy consumption in the building sector.
The Korean government has introduced and implemented various programs to induce the use of renewable energy, such as the mandatory renewable energy supply system and the mandatory renewable energy installation project [3]. Under the mandatory renewable energy installation project, public buildings and buildings with a gross floor area of 1000 m2 or more, including new construction and expansion, must supply a certain percentage of their energy usage with renewable energy. The percentage mandated is at least 30% by 2020, up from 24% in 2018. Renewable energy penetration has increased steadily because of the implementation of renewable-energy-related schemes [4].
Of all the renewable energies, GHP systems are of interest because they can provide a stable heat source and exhibit efficient operation and excellent performance throughout the year [5]. GHP systems have mainly been used in public buildings with small capacities because of construction difficulties and high initial investment costs [6]. On the other hand, installation in public institutions and general buildings is increasing with the implementation of a mandatory supply system [7].
GHP systems are becoming increasingly popular [8,9,10]. On the other hand, they are not being operated efficiently after installation [11]. Generally, the heating and cooling loads in a building are different from each other [12]. The prolonged operation of a GHP system causes problems with the ground thermal environment due to ground heat accumulation because of this load imbalance, which reduces the performance of the system [13]. Hybrid GHP systems are considered an economical and practical alternative to compensate for these problems [14,15,16,17,18]. Hybrid GHP systems use a secondary heat sink for buildings with large cooling loads or a secondary heat source for buildings with large heating loads [19]. The auxiliary equipment may include a cooling tower, boiler, and solar thermal system. By coupling these facilities with a GHP system, the increased ground temperature caused by long-term operation can be controlled [20]. The operation of a hybrid GHP system can reduce the installed capacity of the ground heat exchanger, reduce the equipment cost, and improve the performance of the system [21].
Hybrid GHP systems need variable water flow (VWF) control to prevent energy waste caused by the supply of a constant water flow rate independent of the design maximum load [22]. Variable water flow rates for the load side and source side can be controlled in a hybrid GHP system. The overall energy consumption of the system should be considered according to the energy consumption characteristics of the circulation pump and heat pump (HP) under VWF control. For the efficient operation of a hybrid GHP system, it is necessary to set the transitional operating conditions of the connected heat source systems to prevent performance degradation. In addition, flow control that supplies a constant flow rate of circulating water under partial load will waste unnecessary energy and reduce the performance of the entire system. VWF control, which varies the water flow rate according to the real-time load, can improve the performance of the system and reduce energy consumption [23]. Optimal VWF control is needed to achieve the maximum system coefficient of performance (COP). The HP energy consumption increases when the water flow rate decreases, and the water circulation pump energy increases when the flow rate increases [24]. VWF control is needed to increase efficiency in the GHP system and reduce energy consumption. Efficient operation requires continuous monitoring of the coefficient of performance (COP), which indicates the energy performance and efficiency of the GHP system. This is why hybrid GHP system operation requires COP monitoring and prediction. For the system operation, it is necessary to develop a prediction model that learns with data because of the need for expensive measurement equipment, sensors to measure various variables in the mathematical model, and accuracy limitations [25]. COP prediction models can use machine learning-based predictive models using operational data. Machine learning and big data are used in buildings to reduce energy consumption and improve building performance [26]. Building energy systems are controlled and operated through various sensors, algorithms, and setpoints [27]. In addition, various methods and technologies such as big data, statistics, and machine learning are used to optimize control methods and predict the performance of systems [28]. Hybrid GHP systems require studies on VWF control as one of the energy-saving measures. Therefore, this study reviewed the existing studies on hybrid GHP systems, VWF control, and COP prediction models to propose a VWF control scheme for hybrid GHP systems.

2. Hybrid GHP System

GHP systems utilize commercially available geothermal sources at depths of 100 to 300 m. In summer, the system operates as a cooling system that absorbs heat from the room and releases it into the ground. In winter, it operates as a heating system that absorbs heat from the ground and releases it into the room [29]. Figure 1 presents the concept of a GHP system.
The GHP system consists of a condenser, compressor, evaporator, expansion valve, four-way valve, and ground heat exchanger. The heating and cooling cycle of a heat pump works by repeating four cycles: compression, condensation, expansion, and evaporation. The compressor has high-pressure and low-pressure valves to repeat the suction and discharge action. It sucks in a low-temperature, low-pressure gaseous refrigerant evaporated by the evaporator and compresses it into a high-temperature, high-pressure refrigerant gas. The compressed refrigerant is sent to the condenser, which acts as a pump to circulate the refrigerant. The condenser is a device that condenses and liquefies the refrigerant by removing the heat from the high-temperature, high-pressure gaseous refrigerant discharged from the compressor during heating. Initially, the vapor refrigerant loses heat to the ground, transforming it into a liquid refrigerant, and the heat corresponding to the latent heat is radiated into the room to warm it. The expansion valve is a device that changes the low-temperature, high-pressure liquid refrigerant from the condenser into a low-temperature, low-pressure gaseous refrigerant that is easier to evaporate in the evaporator. It also regulates the flow rate of the refrigerant. The evaporator changes the liquid refrigerant at low temperatures and pressures into a gaseous refrigerant at low temperatures and pressures at the expansion valve. The evaporator accomplishes this directly by absorbing heat from the cooled material and evaporating it. Evaporators are categorized into indirect and direct cooling methods. Geothermal heat exchangers are classified into indirect and direct refrigeration by absorbing and evaporating heat from the refrigerant. In summer, the low-temperature and low-pressure liquid refrigerant passes through the evaporator connected to the geothermal loop system, extracts heat from the circulating water in the loop system with a relatively high water temperature, and changes into vapor refrigerant. GHP systems utilize a four-way valve to convert the cooling operation to the heating operation. Generally, after passing through the compressor, the vapor refrigerant moves toward the condenser, where the temperature and pressure are higher and there is less thermal energy to give off heat. After passing through the condenser, the vapor refrigerant moves toward the condenser, which has a higher temperature and pressure and less thermal energy to give off heat. When the high-temperature and high-pressure vapor refrigerant passing through the four-way valve moves to the condenser installed indoors, the GHP system is in heating mode, and vice versa, when it moves to the geothermal exchanger, it is in cooling mode [30].
The operation of a GHP system is affected by the flow rate and inlet and outlet temperatures. If the inlet temperature increases during the cooling operation or decreases during the heating operation, the heat pump efficiency decreases, and the heating and cooling capacities decrease [31]. The efficient operation of a heat pump requires a high heat capacity of the heat pump. The heat capacity of a heat pump can be calculated using Equation (1).
Q = m C p T o − T i
where Q : heat capacity, kW; m : mass flow rate, kg/s;   C p : specific heat of water, kJ/kg∙K;   T o : outlet water temperature of heat pump, K; and T i : inlet water temperature of heat pump, K.
The COP, an indicator of heat pump performance, can be expressed as the ratio of the heat produced by the heat pump to the energy consumed to operate it. The cooling COP can be calculated from Equation (2), the heating COP from Equation (3), and the overall system COP from Equation (4).
C O P c = Q c W c
C O P h = Q h W c
C O P s y s = Q H P W c + W p + W f
where C O P c : cooling coefficient of performance for heat pump; C O P h : heating coefficient of performance for heat pump;   C O P s y s : coefficient of performance for heat pump system;   Q c : cooling capacity of heat pump, kW; Q h : heating capacity of heat pump, kW; Q H P : cooling and heating capacity of heat pump, kW;   W c : power consumption of compressor for heat pump, kW; W p : power consumption of circulation pump for heat pump, kW; and W p : power consumption of fan for heat pump, kW.
The COP, an indicator of heat pump performance, can be expressed as the ratio of the heat produced by the heat pump to the energy consumed to operate it. The cooling COP, heating COP, and overall system COP can be calculated using Equations (2)–(4), respectively.
The GHP system exchanges heat by absorbing heat from the ground during heating and, conversely, dissipating heat to the ground during the cooling operation. Ground heat storage occurs in buildings where the heating load is lower than the cooling load, and the opposite phenomenon occurs when the cooling load is lower than the heating load because the uses of heating and cooling are not constant year-round. Therefore, the ground temperature can change during long-term operation because of the imbalance of cooling and heating loads [32]. Figure 2 shows the change in ground temperature during long-term operation caused by unbalanced cooling and heating loads [33].
In the case of a large imbalance between heating and cooling loads, the deterioration of the ground thermal environment because of heat accumulation in the ground occurs during long-term operation, which reduces the efficiency of the GHP. Dual- or multisource heat pumps are designed to improve the deficiencies of a single heat source, such as geothermal, solar heat, water, or outside air [34]. Hybrid GHP systems are an economical solution to overcome the above-described problems of GHPs. When operating a GHP system alone, even if the ground heat exchanger (GHE) is designed for a full load, the ground thermal environment will deteriorate if there is a large imbalance between the heating and cooling loads because of heat accumulation in the ground, reducing the efficiency of the GHP system. The ground heat exchanger can be oversized, or the installation area can be increased by increasing the spacing between boreholes to delay this deterioration of the ground thermal environment and maintain the performance of the ground heat exchanger in the design [35]. Hybrid GHP systems are an economical alternative to these GHP disadvantages. The capacity of the ground heat exchanger can be reduced while preventing deterioration of the ground thermal environment through proper coordination with the auxiliary heat source by coupling an auxiliary heat source, such as a boiler, cooling tower, or solar collector, to the GHP [14,17,18,20,36]. Figure 3 presents a cooling hybrid GHP that utilizes a cooling tower as an auxiliary cooling system and a heating hybrid GHP system that utilizes a solar collector as an auxiliary heating system. Hybrid GHP systems consist of a heat pump unit, a ground heat exchanger, and an auxiliary unit that supplements the ground heat, with the auxiliary loop typically separated from the ground loop by a plate heat exchanger. The most common hybrid GHP system auxiliary unit is a cooling tower. In a hybrid GHP system, the secondary fluid discharged from the geothermal heat exchanger releases additional heat to the auxiliary heat source unit and enters the condenser within the heat pump, where it exchanges heat with the refrigerant to prevent heat pump degradation.
There are also various studies related to hybrid GHP systems. Kavanaugh [14] proposes using hybrid systems as an alternative to the poor performance of GHP systems because of the imbalance of cooling and heating loads. Albert [37] designed a system combining a GHP system and a chiller in response to the difficulty and cost of using heating, ventilation, and air conditioning (HVAC) systems in hotels in Florida. Hackel et al. [38] developed a simulation tool to help engineers design optimal hybrid GHP systems across different climates and building types using the TRNSYS program. They also monitored and analyzed three buildings with hybrid GHP systems to demonstrate the performance of hybrid systems [39]. Wang et al. [40] proposed a hybrid GHP system connected with a solar thermal system for an office building and analyzed the system performance using a dynamic energy simulation. They also proposed a solar system operation control scheme based on the COP of the hybrid GHP system. Zishu et al. [21] analyzed the penetration of hybrid GHP systems globally and investigated their development status in China. Qing et al. [41] evaluated the impact of three common operation and control strategies for hybrid GHP systems. The control strategies were as follows: (1) a strategy in which the cooling tower operates when the inlet fluid temperature of the heat exchanger exceeds the setpoint; (2) a strategy in which the control criterion is the difference between the heat pump inlet temperature and the outdoor wet bulb temperature; (3) a strategy that considers the cooling heat storage in the ground. Xu [42] presented a performance evaluation of GHP using a direct evaporative cooling tower. The heat-source side of the system consisted of three borehole ground loop heat exchangers, two packaged water heat pumps, and a direct evaporative cooling tower. The target buildings used for performance evaluation were selected as two small buildings using hydronic cooling and heating. The experimental validation was performed on each component and the full system. Gao et al. [43] reported that energy storage technology (EST) promotes efficient utilization of energy conservation and renewable energy and is expected to become more widespread. Therefore, the study reviewed the progress of underground thermal energy storage (UTES) accompanying GHP and investigated the development of GHP and the origins of soil/rock UTES in particular. Lazzarin et al. [34] used dynamic simulations to size the plant and illustrate the appropriate control algorithm of the main system. They reported high efficiency and low primary energy consumption for the entire system because of the high energy independence from the grid. You et al. [44] reviewed the principle, configuration, and functionality of a hybrid PVT-GSHP that combines solar thermal and GHP systems. PVT for direct heating and temperature rise can improve the efficiency of hybrid GHP systems. Table 1 lists previous studies of hybrid GHP systems.
Previous studies of hybrid GHP systems developed simulation tools for calculating the capacity of the auxiliary heat source or ground heat exchanger, deriving the optimal arrangement of the auxiliary heat source system, and analyzing the economic feasibility of the hybrid GHP system (Table 1). The main focus in designing and applying hybrid GHP systems is analyzing the cooling and heating performance according to various cooling or heating heat source systems and the configuration of the GHP system. Compared to the large number of studies on the design and cooling and heating performance analysis of hybrid GHP systems, there is a lack of research on the development of operating conditions and measures to improve the performance of hybrid GHP systems. For the efficient operation of the hybrid GHP system, it is necessary to analyze the COP during system operation. On the other hand, only the performance of the developed operation method was analyzed in previous studies, and it was not possible to check the COP during operation; furthermore, the economic analysis of the operation method is lacking.

3. Variable Water Flow Control of Hybrid GHP System

3.1. Constant Water Flow Control

Flow control in a water loop is divided into constant- and variable-speed pumps [45]. The hybrid GHP system has a source-side pump that circulates ground-source water and a load-side circulation pump that circulates heating and cooling water that is heat-exchanged by the heat pump and delivered to areas with heating and cooling loads. Existing water flow control schemes use a constant flow control method that provides a constant circulating water supply regardless of changes in load [9]. For system operation, this method uses logarithmic control based on the setpoint of the temperature of the system. A constant flow control system is a system in which the total flow circulated through the pump is always constant regardless of load fluctuations. In this case, a constant-speed pump is usually used, where the speed of the pump is constant. A constant-speed pump system consists of a pump, a mechanical device for pressurizing or transferring fluid, and an electric motor to drive it. In a constant-speed pump system, the motor is connected directly to a commercial power source. Hence, the rotational speed of the motor is constant. Therefore, the pump runs within a constant speed range. The pump operates on a flow–lift curve at the rated speed. In GHP systems, circulation pumps are typically metered to provide a constant flow rate of design maximum load. GHP systems are used primarily as a heating and cooling heat source system for a portion of the building load rather than the entire load. This makes flow control a source of energy waste and reduces overall system performance in partial load situations [46]. Based on the setpoint of the temperature of the hot and cold water, the existing system increases the number of units when the set upper threshold is reached and decreases the number of units of the GHP when the set lower threshold is reached, as shown in the algorithm in Figure 4 [9].
When the GHP system is not operating, if the outlet chilled-water temperature of the GHP is above the setpoint, the GHP system will operate. The next operation of the GHP is determined by comparing the outlet chilled-water temperature and the setpoint. When the chilled-water outlet temperature of the GHP is below the setpoint, maintain the current state. When the GHP system is operating, if the chilled-water outlet temperature of the GHP is below the setpoint of the temperature, stop the GHP from operating. When the chilled-water outlet temperature of the GHP is above the setpoint, run the GHP for additional time to meet the setpoint. When the chilled-water outlet temperature of the GHP is lower than the setpoint of the temperature, the GHP stops running sequentially.

3.2. Variable Water Flow Control

VWF control is one of the ways to reduce the energy consumption of the GHP system [22,24]. In a system that controls the discharge pressure when the discharge flow rate changes, a flow-regulating valve can be installed at the discharge end of the pump to control it according to the flow rate to control the discharge pressure. This method of controlled operation compares unfavorably with variable-speed pump systems in terms of energy efficiency. A variable-speed pump system consists of a pump, an electric motor to drive it, and an inverter to drive the motor at a variable speed. Because the variable-speed driver, namely, the inverter, controls the motor at different speeds, the operating point of the pump varies on the flow–lift curve. Therefore, in a variable-speed pump system with a variable discharge flow rate, the speed can be varied according to the required flow rate, resulting in more efficient operational control than in a constant-speed pump system.
When a constant-speed pump, such as a circulation pump in a conventional hybrid GHP system, is required to provide 50% of the flow to meet the load at the time of load control, the pump will always run at a constant speed and operate at 100% power consumption. The change in pump power consumption does not change when the flow rate is 80%. The pump power can be reduced by the on/off control of pumps capable of delivering the flow to match the load. For example, if the range of flow that a single pump can deliver is 50%, then when a load occurs that requires 50% flow, logarithmic control can be used to start one pump and reduce the pump power by 50% for the other, which remains stationary. A variable-speed pump flow control system refers to a system that can minimize the energy consumption of pumps by adjusting the pump speed to meet the required flow rate in response to various load changes that occur during the operation of the heating and cooling system. Figure 5 presents the difference in pump power consumption as the flow rate changes [47]. Most existing water-loop systems of HVACs use bypass lines, throttle valves, or pump speed regulation to control flow. Of these, the most efficient control is pump speed control. Speed control by a frequency converter is the most efficient way to adjust the pump performance to change the required flow rate. The following equations ((Equations (5)–(7)) can be used to estimate the degree of change in the pump performance as the speed of the centrifugal pump changes [48].
Q 1 Q 2 = n 1 n 2
H 1 H 2 = n 1 n 2 2
P 1 P 2 = n 1 n 2 3
where Q : water flow rate, CMH; n : pump speed, Hz;   H : pump head, m; and P : pump power, kW.
The common law of pumps shows that pump flow ( Q ) is proportional to the pump speed ( n ). The head ( H ) is proportional to the square of the change in pump speed, and power ( P ) is proportional to the cube of the change in speed. The circulating pump power can be reduced through flow control by controlling the pump speed. The energy consumption of the circulating pump decreases as the water flow rate decreases. In the GHP, however, as the water flow rate increases, the differential temperature between the circulating water and the refrigerant decreases, and the heat transfer coefficient of the heat pump increases. As the water flow rate increases, the heat transfer coefficient of the heat pump increases, and the energy consumption decreases because the compressor has to do less work. Circulating pump flow control can save the pump energy by circulating less flow at partial load. On the other hand, it increases the energy consumption of the heat pump, so it is important to consider the energy consumption of the heat pump system when controlling flow (Figure 6).

3.3. Relevant Study

Zhenjun [49] analyzed energy use by applying an optimal control strategy for variable-speed pumps to configure the HVAC system in a building. The pump power usage was reduced by approximately 12–32% by applying the sequence control of pumps using a control strategy that determined and operated the optimal number of pump operations considering the pump power consumption and maintenance cost. In addition, when operating multiple pump systems, the pump energy was reduced by selecting the efficiency values for efficiently switching the number of pump operations and controlling the appropriate number of pumps. Lu et al. [50] examined the interaction between the individual systems and components (chilled water supply temperature and differential pressure sensor) and optimized the differential pressure setpoint by receiving information from the components. The energy consumption of the circulation pump was minimized by analyzing the energy usage of the circulation system. The three strategies considered in previous studies were the following: (1) constant pressure differential controller (CPDC), (2) chilled water supply temperature (SWT), and (3) combined pressure and temperature control to analyze the building energy savings by changing the flow configuration of the system. Puttige et al. [51] proposed an ANN model to predict the long-term performance of a hybrid GHP system to ensure the long-term stability of the system performance uncertainty and ground temperature. They also proposed ways to improve the operation of hybrid GHP systems. When the ANN model was applied to a hospital building in northern Sweden, heating costs were reduced by EUR 64,000, and CO2 emissions were reduced by 92 tons. Lei et al. [52] developed a model to determine the optimal operating speed of a variable-speed pump in a GHP system. They reported that the proposed model-based strategy could achieve energy savings of 8.0% and 9.0% in the heating and cooling periods, respectively. The necessity of optimizing the design scheme and operation strategy of the hybrid PVT-GHP was identified. Miglani et al. [53] described an optimization scheme for the design and operation of a hybrid GHP system with solar thermal energy. The optimization scheme uses adiabatic objective optimization with an operation embedded within the multiobjective optimization of design parameters that minimize total annual cost and CO2 emissions. Zhao et al. [54] compare three schemes through simulation: a chiller and urban central heating system with a GHP system, a hybrid GHP system using a chiller, and urban central heating. As a result, the optimal control strategy aimed at the lowest annual operating cost was found, and the operation of the GHP system was analyzed according to the outlet water temperature of the GHP. Table 2 lists previous studies on flow control of GHP and hybrid GHP systems.
Among the circulating pumps on the heat-source side and the load side of the hybrid GHP system, various studies have examined the flow control of the heat-source-side circulating pump, but few studies have assessed the flow control of the load-side circulating pump. Relevant studies on flow control have mainly analyzed the pump energy and overall energy comparison and the heating and cooling performance of GHP systems based on conventional constant water flow control and VWF control of heat-source-side circulating pumps provided at a constant water flow rate of design maximum load, and performance analysis based on flow control is lacking. In existing hybrid GHP systems, the water flow rate control of the circulating water does not change with the flow rate increase and load fluctuation in the piping. As a result, the problem of pump energy wastage and efficiency decrease under partial load operation conditions occurs [46]. In general, hybrid GHP systems operate by using the inlet temperature of the heat source to determine whether the hybrid system should start the auxiliary heat source. When the source-side inlet temperature is higher than the setpoint of the temperature, the auxiliary heat source is operated by determining that the COP decreases [36]. This is an expected response of the COP to temperature changes, and it is difficult to see it as a direct response to the decrease in COP and the improvement in COP through hybrid operation.
Controlling the flow rate of a circulation pump that uses the least energy and shows the maximum performance requires an analysis of the energy of the pump, the energy of the heat pump, and the system COP that reflects both. Existing system COPs can be analyzed using measurement equipment or mathematical models. Various monitoring or measurement values and multiple sensors are required to analyze the COP using mathematical models, which is expensive [55]. The COP needs to be predicted using machine learning, which uses fewer monitoring sensors.

4. Prediction of COP for Water Flow Control

Monitoring the current COP and predicting the next stage of COP as the hybrid GHP system is operated is necessary for optimal water flow control to achieve the maximum COP [56]. In a typical system installation, short-term COP measurements are made to verify the performance of system, and long-term COP monitoring is not performed. Performance factor monitoring and prediction of the next level of COP can be checked based on mathematical models using measured operational data. However, mathematical models require many inputs and require the installation of many measurement sensors. If any of the required input factors are missing, the predicted COP will be inaccurate or unpredictable. Predictive models using machine learning utilize various theoretical methods to find and predict the relationship between input and output data, and compared to mathematical methods, they can predict with relatively few input factors and require big data [57]. In building energy systems, various data are collected using a building automation system (BAS) for system operation, and monitoring and can be utilized to develop predictive models through machine learning. Therefore, it is necessary to predict the COP using machine learning that can predict the COP with a small number of monitoring sensors. In previous studies of hybrid GHP systems, machine learning used for performance prediction models include the artificial neural network (ANN) model [58,59,60,61,62,63,64], support vector machine (SVM) [65,66,67,68], random forest (RF) [69], and K-nearest neighbor [69].
Existing hybrid GHP systems waste energy by providing a constant flow rate of maximum design load. To prevent this, VWF control is required. It is necessary to control the flow rate of the heat source and circulating water on the load side of the hybrid GHP system. Control studies to reach maximum system performance and energy saving of the hybrid GHP system according to flow rate control are being conducted. To this end, it is necessary to develop a predictive model to check the COP of the hybrid GHP system. Accordingly, in this chapter, a study of the COP prediction model for flow control of a hybrid GHP system was reviewed.
The accurate prediction of the GHP system COP is essential for optimal control and energy savings in HVAC systems. The COPs of GHPs can be calculated theoretically using mathematical models, simulations, machine learning, or measuring instruments. Theoretical calculations using mathematical models are expensive because of the large number of input values required and the need for various measuring instruments to measure them, such as temperature, heat pump power consumption, pressure, water flow rate, and refrigerant flow rate [55]. Long-term field monitoring is the most accurate and reliable method to check operational status to maintain proper performance. But long-term monitoring methods are time-consuming and expensive.
The simulation is accomplished using a dynamic energy simulation tool, such as EnergyPlus, TRNSYS, and theoretical models. Simulation results are often higher in number than field experiments because the boundary conditions of a simulation are simplified and theoretical, ignoring uncertainties of real condition. The simulation requires specialized knowledge and information-gathering about the various conditions for the simulation. Also, it is time-consuming. In the case of predicting the COP through machine learning, the dynamic characteristic of the HVAC system is represented by the measured data, which does not require a high level of theoretical knowledge of the system compared to other methods and can be predicted with a few variables. The prediction methods using mathematical models, such as linear regression, calculation of the COP through a simulation tool, and various machine learning models, such as random forest (RF), artificial neural networks (ANNs), and support vector machines (SVMs), for predicting the COP of GHP systems have been studied in previous research.
Simon et al. [70] used simulation data to model the COP of a GHP. They described a simplified method to predict the COP of GHPs using an MLR model that can be applied to the manufacturer’s data. For the three GHPs studied, the external prediction errors of the MLR model determined by the methodology are 1%, 0.9%, and 0.2% for heating capacity predictions and 3.2%, 4.9%, and 2.6% for COP predictions. Akhlaghi [71] developed a statistical model based on MLR to predict the performance of dew point evaporative cooling systems, bypassing the details of the performance process. The inlet air conditions (e.g., temperature, relative humidity, air flow rate, and the ratio of working air to inlet air) are selected as operating parameters, and the cooling capacity, COP, dew point, wet bulb efficiency, and pressure drop are selected as input parameters. Park et al. [72] developed ANN models to evaluate the optimal variables for predicting the COP of a GHP system in a hospital building. Kim [73] used a mathematical model to predict the COP of a GHP system, and Esen et al. [62] developed a COP prediction model using support vector machines with the heating capacity as input. In addition, prediction studies using an adaptive neuro-fuzzy inference system [74], multilayered feed forward neural network [75], and back propagation neural network [76] were conducted to predict GHP performance such as heating load, energy consumption, and water flow rate.
Existing COP prediction studies use various methods to predict COPs. COP prediction through machine learning is performed mainly by utilizing directly related inputs to calculate the COP, such as power consumption and water flow rate. And input data that are measured through multiple monitoring sensors or are measured as difficult during operation are used. Also, COP prediction models have been developed using data in a limited operational range provided by the manufacturer or data limited for use in simulation.

5. Future Research of Hybrid GHP

As we reviewed the hybrid GHP research, the optimal methods proposed by hybrid GHP researchers serve as the advanced research. They mainly contain the following:
(1)
It is possible to design a hybrid system that combines the GHP system with existing heat sources and other new heat sources. Research can be conducted on theoretical analysis and performance evaluation according to hybrid system combinations.
(2)
The hybrid GHP system and the interlocking control plan of the HVAC system can contribute to indoor comfort and energy saving.
(3)
Prediction models of monitoring and control parameters can be materialized for improved control technology of HGHP systems. In addition, predictive model optimization, predictive-model-based control technology, and FDD technology can be developed according to the model development method.
(4)
HGHP research was mainly conducted through theoretical analysis and simulation. Field applications, experiments, and verification studies can be conducted for the advancement of technology.
Based on existing research, practical research will be gradually conducted. A variety of feasible building energy system technologies will be developed and implemented through various combinations of existing distributed renewable systems and existing heat source systems.

6. Conclusions

This study evaluated the concept of a hybrid GHP system, flow control of a hybrid GHP system, and a machine learning-based COP prediction model through a literature survey. The following conclusions were drawn:
(1)
The heat accumulation phenomenon caused by an imbalance of heating and cooling loads in a building confirmed that the heat source temperature increases as the operating age of the GHP system increases. As a result, the performance degradation of the GHP system and the need for a hybrid GHP system to improve it were identified. The characteristics of the hybrid GHP system and existing research trends were analyzed. In the study of the design and application of hybrid GHP systems, the focus has been on the analysis of the heating and cooling performance under different heating and cooling heat source systems and the configuration of the GHP system. Compared to the many studies on the design and cooling and heating performance analysis of hybrid GHP systems, there is a lack of research on the development of operating conditions and measures to improve the performance of hybrid GHP systems. For efficient operation of the hybrid GHP system, it is necessary to analyze the COPs during system operation. However, previous studies only analyzed the performance of the developed operation method and did not confirm the COPs during operation, so the economic analysis of the operation method is lacking.
(2)
An analysis of the theoretical and existing research on flow control in hybrid GHP systems shows that in hybrid GHP systems, the circulating pump has been subjected to constant flow control, which provides a constant flow rate of design maximum load. Pump energy, total energy comparison, and heating and cooling performance of geothermal heat pump systems based on conventional constant flow control and VRF control have been analyzed, but performance analysis based on flow control is lacking. Existing studies have analyzed the frequency of the compressor and derived the differential pressure setpoint or temperature setpoint for flow control to save energy. Flow rate control may cause energy waste and decrease the overall system COP in partial load situations. This is because the hybrid GHP system is used mainly as a heating and cooling heat source system for part of the building load rather than the entire load. Hence, the need for flow rate control in the hybrid GHP system is confirmed.
(3)
This study investigated the theory and existing research trends on machine learning-based COP prediction models that can predict COPs with a small number of monitoring sensors. Existing studies on predicting COPs of GHP systems have developed prediction models by selecting input values based on mathematical models, collecting data through multiple measurement points, and utilizing data from the production environment. However, the application of such models may be limited by the field environment, and it is confirmed that it is necessary to predict the COP using machine learning based on existing field monitoring data. Through previous research, we confirmed the feasibility of developing a COP prediction model for hybrid GHP systems based on machine learning. It is necessary to develop a COP prediction model that shows high precision at low cost by utilizing input data that are commonly observed during the operation of GHP systems and are easy to measure.

Author Contributions

All authors contributed to this work. J.-H.S. investigated and wrote the original draft. H.-J.K. wrote the paper for review and editing. H.-G.L. performed visualization. Y.-H.C. carried out project administration and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the 2020 Yeungnam University Research Grant (220A380176).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Schematic diagram of a GHP system.
Figure 1. Schematic diagram of a GHP system.
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Figure 2. Ground temperature change by number of elapsed years due to unbalanced cooling and heating loads.
Figure 2. Ground temperature change by number of elapsed years due to unbalanced cooling and heating loads.
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Figure 3. Schematic diagram of the hybrid GHP system: (a) cooling hybrid GHP system that utilizes a cooling tower; and (b) heating hybrid GHP system that utilizes a solar collector.
Figure 3. Schematic diagram of the hybrid GHP system: (a) cooling hybrid GHP system that utilizes a cooling tower; and (b) heating hybrid GHP system that utilizes a solar collector.
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Figure 4. Constant-control algorithm of GHP.
Figure 4. Constant-control algorithm of GHP.
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Figure 5. Pump power consumption as the water flow rate changes.
Figure 5. Pump power consumption as the water flow rate changes.
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Figure 6. Energy consumption and COPs based on flow control of hybrid GHP system.
Figure 6. Energy consumption and COPs based on flow control of hybrid GHP system.
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Table 1. Existing studies of hybrid GHP systems.
Table 1. Existing studies of hybrid GHP systems.
CategoryContentsAuthor
Design of hybrid geothermal
heat pump system
  • The design of a hybrid GHP system combining a GHP system and a chiller considering the difficulties and operation cost of HVAC.
Albert [37]
  • Development of simulation tools for the optimal design of hybrid GHP systems data.
Hackel et al. [38]
Performance analysis of hybrid GHP systemGeothermal +
cooling tower
geothermal +
boiler
  • Performance verification by monitoring three buildings with hybrid GHP systems.
Hackel et al. [39]
  • Analysis of hybrid GHP system control strategies.
Qing et al. [41]
  • Analysis of hybrid GHP system control strategies.
Xu [42]
Geothermal +
photovoltaic/thermal
  • Performance analysis of hybrid GHP using dynamic energy simulation.
Wang [40]
Table 2. Existing studies of water flow control of hybrid GHP systems.
Table 2. Existing studies of water flow control of hybrid GHP systems.
ContentsNecessityAuthor
  • Using a mathematical model when operating multiple pump systems, select efficiency values to convert the number of pumps operated efficiently.
  • Verification through simulation of pump energy-saving effect by controlling the proper number of pumps.
  • Requires a variety of information to construct a mathematical model.
  • Field application evaluation required.
Zhenjun Ma et al. [49]
  • Analyze the characteristics of cold water supply temperature and differential pressure sensor to minimize energy consumption.
  • VRF control by resetting the differential pressure setting value.
  • Verification of development technology through energy simulation.
  • Requires a variety of information to construct a mathematical model.
  • Need to analyze the COP through flow control.
L. Lu et al. [50]
  • Propose an ANN model to predict the long-term performance of a hybrid GHP system.
  • Analyze how to improve the operation of a hybrid GHP system.
Puttige et al. [51]
  • Describe optimization measures for the design and operation of a hybrid GHP system utilizing solar thermal.
  • Model the thermal characteristic of the BHE, operating system constraints, and seasonal impact of solar generation within an optimization system.
Miglani et al. [53]
  • Comparison of chiller and city central heating systems with GHP systems, and hybrid GHP systems using chiller and city central heating as auxiliary heat sources and sinks.
  • Analyze optimal control strategy for lowest annual operating cost.
Zhao et al. [54]
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Shin, J.-H.; Kim, H.-J.; Lee, H.-G.; Cho, Y.-H. Variable Water Flow Control of Hybrid Geothermal Heat Pump System. Energies 2023, 16, 6113. https://doi.org/10.3390/en16176113

AMA Style

Shin J-H, Kim H-J, Lee H-G, Cho Y-H. Variable Water Flow Control of Hybrid Geothermal Heat Pump System. Energies. 2023; 16(17):6113. https://doi.org/10.3390/en16176113

Chicago/Turabian Style

Shin, Ji-Hyun, Hyo-Jun Kim, Han-Gyeol Lee, and Young-Hum Cho. 2023. "Variable Water Flow Control of Hybrid Geothermal Heat Pump System" Energies 16, no. 17: 6113. https://doi.org/10.3390/en16176113

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