Horizontal Ground-coupled Heat Pump Research Articles

Influence of local geological data on the performance of horizontal ground-coupled heat pump system integrated with building thermal loads

Horizontal ground-couple heat pump (GCHP) system incurs lower installation cost compared with the vertical GCHP system. However, the shallow burial depth makes the heat transfer process susceptible to seasonal variations. This paper analyzes the short-term and annual performance of different geothermal heat exchangers’ (GHEs) configurations and geological conditions by developing 3D finite element models. Field monitored data of ground temperature and thermal property are incorporated. Six common types of GHE configurations are analyzed, from which the most efficient patterns are identified. The annual performance of optimal GCHP pattern integrated with different types of building loads are analyzed. Major conclusions include (1) application of soil temperature harmonic function as commonly done in the current practice will lead to overestimation of thermal build-up effects underground; (2) utilization of local geological data (i.e., field measured ground temperature and soil thermal properties) helps improve the annual performance of horizontal GCHP system; (3) shift of ground temperature is less significant for GCHP operating in heating dominant areas due to balanced heat injection and extraction. This study indicates incorporating local geological data reduce the GHE design length by 25%–60% and therefore is a viable strategy to achieve cost effectiveness.

Optimum design of horizontal ground-coupled heat pump systems using spiral-coil-loop heat exchangers

This paper deals with an optimum design of horizontal ground heat pump systems for spiral-coil-loop heat exchangers. A three dimensional numerical analysis model simulating the thermal behavior of a horizontal spiral-coil-loop heat exchanger was developed, and the accuracy of the model was verified through indoor thermal response tests. After that, a total of 160 parametric studies were conducted using numerical simulation models in order to grasp the degree of effects that key input parameters used in the model would have on the output. Then, an optimum design condition for horizontal ground coupled heat pump system was suggested using several economic analysis tools. Economic analysis factors, such as internal rate of return, savings to investment ratio, and simple payback period, show that certain design conditions (coil pitch: 0.08m, setting depth: 2.5m, circulating fluid velocity: 0.7ms−1) provide the most economic feasibility. However, this condition also varies with the unit cost of operation and initial investment.

Interactions between the physical soil environment and a horizontal ground coupled heat pump, for a domestic site in the UK

There is currently an increased interest of Government and Industry in the UK, as well as at the European Community level and International Agencies (i.e. Department of Energy, American International Energy Agency), to improve the performance and uptake of Ground Coupled Heat Pumps (GCHP), in order to meet the 2020 renewable energy target. A sound knowledge base is required to help inform the Government Agencies and advisory bodies; detailed site studies providing reliable data for model verification have an important role to play in this. In this study we summarise the effect of heat extraction by a horizontal ground heat exchanger (installed at 1 m depth) on the soil physical environment (between 0 and 1 m depth) for a site in the south of the UK. Our results show that the slinky influences the surrounding soil by significantly decreasing soil temperatures. Furthermore, soil moisture contents were lower for the GCHP soil profile, most likely due to temperature-gradient related soil moisture migration effects and a decreased hydraulic conductivity, the latter as a result of increased viscosity (caused by the lower temperatures for the GCHP soil profile). The effects also caused considerable differences in soil thermal properties. This is the first detailed mechanistic study conducted in the UK with the aim to understand the interactions between the soil, horizontal heat exchangers and the aboveground environment. An increased understanding of these interactions will help to achieve an optimum and sustainable use of the soil heat resources in the future. The results of this study will help to calibrate and verify a simulation model that will provide UK-wide recommendations to improve future GCHP uptake and performance, while safeguarding the soil physical resources. ► The ground heat exchanger modified heat and water transport in the soil. ► The GHE influence soil temperatures up to 0.9 m from the slinky installation depth. ► We observed transient soil temperature trend, due to anomalous winter conditions. ► Soil moisture migration effects caused differences in soil thermal properties.

Horizontal ground coupled heat pump: Thermal-economic modeling and optimization

The modeling and optimizing processes of a Ground Coupled Heat Pump (GCHP) with closed Horizontal Ground Heat eXchanger (HGHX) are presented in this paper. After thermal modeling of GCHP including HGHX, the optimum design parameters of the system were estimated by minimizing a defined objective function (total of investment and operation costs) subject to a list of constraints. This procedure was performed applying Genetic Algorithm technique. For given heating/cooling loads and various climatic conditions, the optimum values of saturated temperature/pressure of condenser and evaporator as well as inlet and outlet temperatures of the water source in cooling and heating modes were predicted. Then, for our case study, the design parameters as well as the configuration of HGHX were obtained. Furthermore, the sensitivity analysis of change in the total annual cost of the system and optimum design parameters with the climatic conditions, cooling/heating capacity, and soil type were discussed.

Performance prediction of a ground-coupled heat pump system using artificial neural networks

This paper describes the applicability of artificial neural networks (ANNs) to predict performance of a horizontal ground-coupled heat pump (GCHP) system. Performance forecasting is the precondition for the optimal control and energy saving operation of heat pump systems. ANNs have been used in varied applications and they have been shown to be particularly useful in system modelling and system identification. In order to train the ANN, limited experimental measurements were used as training data and test data. In this study, in input layer, there are air temperature entering condenser unit and air temperature leaving condenser unit, and ground temperatures (1 and 2m); coefficient of performance of system (COPS) is in output layer. The back propagation learning algorithm with three different variants, namely Levenberg-Marguardt (LM), Pola-Ribiere conjugate gradient (CGP), and scaled conjugate gradient (SCG), and tangent sigmoid transfer function were used in the network so that the best approach can find. The most suitable algorithm and neuron number in the hidden layer are found as LM with seven neurons. For this number level, after the training, it is found that Root-mean squared (RMS) value is 1%, and absolute fraction of variance (R^2) value is 99.999% and coefficient of variation in percent (COV) value is 28.62%. It is concluded that, ANNs can be used for prediction of COPS as an accurate method in the systems.

Numerical and experimental analysis of a horizontal ground-coupled heat pump system

The main objective of this work is to evaluate a heat pump system using the ground as a source of heat. A ground-coupled heat pump (GCHP) system has been installed and tested at the test room, University of Firat, Elazig, Turkey. Results obtained during experimental testing are presented and discussed here. The coefficient of performance (COP sys) of the GCHP system is determined from the measured data. A numerical model of heat transfer in the ground was developed for determining the temperature distribution in the vicinity of the pipe. The finite difference approximation is used for numerical analysis. It is observed that the numerical results agree with the experimental results.