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Finite Volume Based Computer Program for Ground Source Heat Pump System

This report is a compilation of the work that has been done on the grant DE-EE0002805 entitled "Finite Volume Based Computer Program for Ground Source Heat Pump Systems." The goal of this project was to develop a detailed computer simulation tool for GSHP (ground source heat pump) heating and cooling systems. Two such tools were developed as part of this DOE (Department of Energy) grant; the first is a two-dimensional computer program called GEO2D and the second is a three-dimensional computer program called GEO3D. Both of these simulation tools provide an extensive array of results to the user. A unique aspect of both these simulation tools is the complete temperature profile information calculated and presented. Complete temperature profiles throughout the ground, casing, tube wall, and fluid are provided as a function of time.

15 GEOTHERMAL ENERGY↗

Recovery Act: Finite Volume Based Computer Program for Ground Source Heat Pump Systems

This report is a compilation of the work that has been done on the grant DE-EE0002805 entitled Finite Volume Based Computer Program for Ground Source Heat Pump Systems. The goal of this project was to develop a detailed computer simulation tool for GSHP (ground source heat pump) heating and cooling systems. Two such tools were developed as part of this DOE (Department of Energy) grant; the first is a two-dimensional computer program called GEO2D and the second is a three-dimensional computer program called GEO3D.

15 GEOTHERMAL ENERGY↗

GEO2D - Two-Dimensional Computer Model of a Ground Source Heat Pump System

This file contains a zipped file that contains many files required to run GEO2D. GEO2D is a computer code for simulating ground source heat pump (GSHP) systems in two-dimensions. GEO2D performs a detailed finite difference simulation of the heat transfer occurring within the working fluid, the tube wall, the grout, and the ground. Both horizontal and vertical wells can be simulated with this program, but it should be noted that the vertical wall is modeled as a single tube. This program also models the heat pump in conjunction with the heat transfer occurring. GEO2D simulates the heat pump and ground loop as a system. Many results are produced by GEO2D as a function of time and position, such as heat transfer rates, temperatures and heat pump performance. On top of this information from an economic comparison between the geothermal system simulated and a comparable air heat pump systems or a comparable gas, oil or propane heating systems with a vapor compression air conditioner. The version of GEO2D in the attached file has been coupled to the DOE heating and cooling load software called ENERGYPLUS. This is a great convenience for the user because heating and cooling loads are an input to GEO2D. GEO2D is a user friendly program that uses a graphical user interface for inputs and outputs. These make entering data simple and they produce many plotted results that are easy to understand. In order to run GEO2D access to MATLAB is required. If this program is not available on your computer you can download the program MCRInstaller.exe, the 64 bit version, from the MATLAB website or from the Geothermal Data Repository. This is a free download which will enable you to run GEO2D.

15 GEOTHERMAL ENERGY↗

Case Study for the ARRA-funded GSHP Demonstration at University at Albany

High initial costs and lack of public awareness of ground-source heat pump (GSHP) technology are the two major barriers preventing rapid deployment of this energy-saving technology in the United States. Under the American Recovery and Reinvestment Act (ARRA), 26 GSHP projects have been competitively selected and carried out to demonstrate the benefits of GSHP systems and innovative technologies for cost reduction and/or performance improvement. This report highlights the findings of a case study of one of the ARRA-funded GSHP demonstration projects—a distributed GSHP system at a new 500-bed apartment-style student residence hall at the University at Albany. This case study is based on the analysis of detailed design documents, measured performance data, published catalog data of heat pump equipment, and actual construction costs. Simulations with a calibrated computer model are performed for both the demonstrated GSHP system and a baseline heating, ventilation, and air-conditioning (HVAC) system to determine the energy savings and other related benefits achieved by the GSHP system. The evaluated performance metrics include the energy efficiency of the heat pump equipment and the overall GSHP system, as well as the pumping performance, energy savings, carbon emission reductions, and cost-effectiveness of the demonstrated GSHP system compared with the baseline HVAC system. This case study also identifies opportunities for improving the operational efficiency of the demonstrated GSHP system.

15 GEOTHERMAL ENERGY↗

GEO3D - Three-Dimensional Computer Model of a Ground Source Heat Pump System

This file is the setup file for GEO3D, a computer program written by Jim Menart to simulate vertical wells in conjunction with a heat pump for ground source heat pump (GSHP) systems. This is a very detailed three-dimensional computer model. This program produces detailed heat transfer and temperature field information for a vertical GSHP system.

15 GEOTHERMAL ENERGY↗

Recent Experiences Calculating g-functions for Use in Simulation of Ground Heat Exchangers

Temperature response functions, known as g-functions, are a computationally efficient method for simulating ground heat exchangers (GHEs), used with ground-source heat pump (GSHP) systems, either as part of a whole-building energy simulation or as part of a dedicated ground heat exchanger design tool. In fact, at present, they are the only feasible way to simulate a ground-source heat pump system in a whole-building energy simulation. This paper summarizes recent developments in the field and recent experience using a new open-source g-function calculation tool known as pygfunction (Cimmino 2018a, 2018b). This experience includes accuracy, computation time, memory requirements and sensitivity to boundary conditions. With larger ground heat exchangers, e.g. in excess of 100 boreholes, the computational time and memory requirements can create challenges.

Spitler, Jeffery↗

Ground heat exchanger design tool with rowwise placement of boreholes

Simulation-based design tools have been used since the late 1980s for designing ground heat exchangers (GHE) used with ground source heat pump (GSHP) systems. The ground heat exchanger simulations used in these tools rely on thermal response functions known as g-functions. Because of the significant computational burden in computing g-functions for even a single configuration, the design tools have relied on libraries of pre-computed g-functions. These g-functions were available for standard configuration shapes, such as lines, rectangles, open rectangles, L-shapes, and U-shapes. Standard shapes are often sub-optimal. For any building on a site, the available land may preclude use of a standard shape. For large GSHP systems with significantly imbalanced annual heat rejection and extraction loads, large rectangular fields may experience significant heat build-up (or heat draw-down) in the interior of the field. This paper describes a new ground heat exchanger design tool capable of automatically selecting and sizing both standard and irregular configurations. The focus of this paper is a method for creating, selecting and sizing irregular configurations where the available land area and "no-go" zones are described as irregular polygons.

Spitler, Jeffery↗

A Preliminary Investigation on the Cost Reduction Potential of Optimizing Bore Fields for Commercial Ground Source Heat Pump Systems

The high initial cost of ground heat exchangers (GHE) is a primary hurdle preventing wider adoption of ground source heat pump (GSHP) systems. GHEs used for commercial GSHP systems commonly consist of vertical boreholes installed on a grid with equal spacing between boreholes. Significant thermal loads require a large number of boreholes to be present in the field. However, due to thermal interactions among boreholes, the ground formation in the center of a bore field can, over time, become thermally saturated when the thermal load is not balanced on an annual basis. The loss of effectiveness due to thermal saturation at the center boreholes in regularly spaced borehole fields suggests that larger spacing near the center of the bore field could be more optimal, and in return reduce initial costs. Through computer simulations using the latest development of a GHE modeling tool, this study evaluates the impacts of various unconventional designs of the borehole field on the performance and cost of the GHEs of a typical commercial GSHP system. The unconventional designs include irregular spacing among boreholes with decreased spacing around the perimeter and increased spacing in the interior of the field. The unconventional bore field design shortens the total drilling length by up to 42% while giving better heat transfer performance than a conventional bore field design. The significant total bore length reduction is due to improved heat transfer effectiveness of each borehole in the unconventional bore field.

Spitler, Jeffery↗

A dynamic 2D Borehole Thermal Energy Storage (BTES) model for enhanced computational efficiency

Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.

2D modeling↗

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. -- For the study of the effect of regional groundwater flow: see Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO_3D, commit c2a2d2a. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

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Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hybrid Geothermal Heat Pumps for Cooling Telecommunications Data Centers

The technical and economic performance of geothermal heat pump (GHP) systems supplying year-round cooling to representative small data centers with cooling loads less than 500 kWth were analyzed and compared to air-source heat pumps (ASHPs). A numerical model was developed in TRNSYS software to simulate the operation of air-source and geothermal heat pumps with and without supplementary air cooled heat exchangers - dry coolers (DCs). The model was validated using data measured at an experimental geothermal system installed in Ithaca, NY, USA. The coefficient of performance (COP) and cooling capacity of the GHPs were calculated over a 20-year lifetime and compared to the performance of ASHPs. The total cost of ownership (TCO) of each of the cooling systems was calculated to assess its economic performance. Both the length of the geothermal borehole heat exchangers (BHEs) and the dry cooler temperature set point were optimized to minimize the TCO of the geothermal systems. Lastly, a preliminary analysis of the performance of geothermal heat pumps for cooling dominated systems was performed for other locations including Dallas, TX, Sacramento, CA, and Minneapolis, MN.

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