Search Results (195)

Ground source heat pump (GSHP) systems contribute to sustainable building decarbonization while confronting two intertwined challenges: long-term ground thermal imbalance in shallow borefields and the requirement for coordinated operation between thermal systems and electrical grid dynamics. Hybrid shallow–deep borefield configurations have been proposed to mitigate thermal imbalance for sustainable geothermal resource exploitation, yet their grid-interactive demand–response potential remains unexplored. Here, we develop a coupled thermal–electrical model for a shallow–deep mixed GSHP (SDBHE) system equipped with water-tank thermal storage, validated against scaled sand-tank experiments (3.5–8.3% error), and assess its year-round performance under time-of-use electricity tariffs for a 200,000 m² residential district in cold-climate conditions. The SDBHE system reduces the required shallow borehole count by 28% and total drilling length by 22% compared with a shallow-only baseline, saving 11% on operational electricity costs over 10 years. Integrating water-tank thermal storage with a 50% load-shifting strategy yields an additional 10.9–11% cost reduction without degrading the system’s coefficient of performance. Under higher load-shifting ratios, the combined capital and operational savings reach 19–29%, with the optimal allocation assigning the incremental high-price-period load preferentially to deep boreholes (COP 6.29 versus 5.25 for shallow). These results demonstrate that integrating shallow and deep geothermal tiers with thermal storage enables both capital-efficient borefield design and economically viable demand-side grid participation. The findings are bound by the cold-climate residential context and the rule-based control scheme; field-scale validation and lifecycle cost analysis are needed to generalize the conclusions. Full article

Residential buildings are central to decarbonisation because existing dwellings combine long service lives, high heating demand and heterogeneous constraints for retrofitting. This study investigates some retrofit strategies for a terraced house in Oxford, UK, to achieve the winter indoor air temperature set-point while reducing energy use, costs and CO₂ emissions. A calibrated dynamic simulation model was developed from on-site inspections, monitored temperatures, occupant schedules and energy-bill data. The analysis compares baseline configuration with scenarios including radiator power upgrading, envelope insulation, increased internal thermal mass and replacement of the condensing boiler with a high-temperature ground-source heat pump (GSHP). The results show that radiator upgrading enables the most critical rooms to reach the 20 °C set-point, while envelope insulation reduces heating energy and costs. Increased thermal mass improves night-time temperature stability, although its effect on annual energy demand is limited. The GSHP provides the largest primary energy reduction, lowering operational primary energy by 66.3% compared to the reference case and by 70.4% when combined with envelope and thermal-mass measures. Operational CO₂ emissions are reduced by 35.0–84.3%. The study highlights the need to evaluate the capacity of heat emitters, building envelope performance, thermal inertia and heat generator efficiency within a dynamic framework. Full article

This study extends an established bi-level dynamic optimization framework for grid-connected regional integrated energy systems (RIES) to address the escalating renewable energy penetration (REP) within integrated power systems (IPS). While traditional models treat REP as static, our approach integrates its dynamic growth into both the design and operational scheduling phases, utilizing a genetic algorithm paired with the Gurobi solver. Applied to a case study in Changsha, the extended model is systematically benchmarked against conventional static REP scenarios. The research shows that the introduction of REP growth factors in the optimization model can increase the installation capacity of ground source heat pumps (GSHPs), reduce the installation capacity of combined heat and power units and absorption chillers, and reduce the initial investment of the system by 12.20%. Affected by the difference in equipment capacity configuration, the primary energy consumption and total cost of the grid-connected RIES decrease during the planning period, while the cumulative carbon dioxide emissions show a slight increase. The primary energy consumption and total cost under winter operating conditions were reduced by 2.44% and 2.38%, respectively. In addition, with the increase of REP growth rate in IPS, the reductions in the system’s primary energy consumption, carbon dioxide emissions, and total cost all increase accordingly. Therefore, in macroscopic RIES planning, incorporating dynamic REP reveals a clear trade-off: improving economic and energy efficiency may temporarily increase carbon emissions when renewable penetration is low. Full article

Geothermal energy is a clean, stable, and low-carbon renewable resource with increasing strategic importance in sustainable energy transitions. In recent years, machine learning has been progressively applied in geothermal systems, including resource exploration, reservoir characterization, drilling and operational optimization, heat-transfer performance prediction, and ground source heat pump (GSHP) control. Machine learning enables high-dimensional data mining, complex mapping, and surrogate modeling. While it can often deliver higher efficiency and accuracy compared to conventional methods, these advantages are not absolute; rather, they are highly contingent upon the quality and scale of the dataset, the rigorousness of the validation method, and the appropriateness of the selected algorithm. This review systematically summarizes major machine learning applications in geothermal energy, highlighting representative methods, data sources, target tasks, and research features. It identifies critical limitations in current studies, including dataset scale and quality, model generalization, physical consistency, interpretability, and deployment feasibility. The review further emphasizes the evolution of geothermal machine learning from pointwise prediction tools to frameworks supporting intelligent analysis, optimization, and decision-making. Future directions include multi-source heterogeneous data fusion, embedding of physical mechanisms, interpretable modeling, and integration with digital twin systems. These approaches aim to shift machine learning from high-accuracy prediction toward trustworthy and deployable decision support for geothermal energy systems. Full article

The open-source Python package Geoloop introduces a novel, semi-analytical model for predicting the performance of deep (>500 m depth) vertical borehole heat exchangers (BHEs), with a focus on capturing depth-dependent variations in subsurface thermal properties, i.e., geothermal gradient and thermal conductivity. Conventional computationally efficient semi-analytical models based on load-aggregation of g-functions often assume uniform subsurface thermal properties. Geoloop addresses this gap by implementing a vertically stacked approach, allowing for realistic simulation of depth-variability in both the subsurface and borehole material properties. The model is benchmarked in the shallow domain against standard depth-uniform g-function implementations (up to 100 m depth) and for deeper conditions with a numerical finite volume model, demonstrating strong agreement and validating its accuracy and efficiency. Simulations for typical Dutch conditions show that deeper BHEs (up to 2000 m) can achieve significantly higher thermal power supply than shallower systems, and results in terms of resulting inlet/outlet temperatures for given heat extraction rates can strongly deviate (>4 °C) from results obtained by depth-uniform assumptions in thermal properties. Application of the model to the Dutch context reveals a non-linear increase in heat extraction potential with depth, surpassing values assumed in common practice by Dutch industry. The results highlight the importance of considering local geological heterogeneity and depth-dependent properties for accurate deep borehole heat exchanger (BHE) performance assessment and system optimization. Geoloop thus offers a robust, versatile platform for advancing the design and analysis of deep vertical BHE systems. Full article

This study focuses on optimizing backfill materials to enhance the heat transfer performance of ground heat exchangers (GHEs) in ground source heat pump (GSHP) systems. A series of composite phase change material/original sand soil (CPCM/OSS) backfill materials was prepared using capric acid–myristic acid/expanded graphite (CA-MA/EG) at mass ratios of 5%, 10%, 15%, and 20%. Thermal conductivity testing, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), laboratory heat transfer tests, and 3D numerical simulations under typical intermittent summer conditions were systematically conducted. The results show that thermal conductivity, specific heat capacity, and thermal storage coefficient all increase with rising moisture content and CPCM dosage. The newly developed CPCM/OSS backfill material significantly improves the heat transfer performance of GHEs. Comprehensive thermophysical characterization indicates that the 10 wt% CPCM sample is the optimal formulation. Laboratory tests demonstrate that, relative to pure OSS backfill, the 10 wt% CPCM-doped CPCM/OSS raises the average soil temperature by approximately 2.5–2.8 °C. Numerical simulations over three consecutive days show that, relative to pure OSS backfill, the 10 wt% CPCM-doped composite enhances the heat exchange capacity per linear meter of the GHEs by 8.8%. The newly developed CPCM/OSS backfill material significantly improves the heat transfer performance of GHEs. It provides a feasible material solution and technical reference for GSHP system design. Full article

Ground-source heat pump (GSHP) systems are widely used because of their energy-saving and environmentally friendly characteristics. However, the long-term operation of a standalone GSHP system leads to heat accumulation in the soil for cooling load-dominated buildings, which results in a decline in system performance. To address this issue, in this study, a high-speed railway station in Jinan was considered as the research object, and a hybrid system scheme in which a GSHP is coupled with an air-source heat pump (ASHP) was developed. The system uses the outdoor dry-bulb temperature as the control parameter and establishes a multi-unit operation control strategy. A dynamic simulation model of the hybrid system was constructed using TRNSYS software, and then the energy consumption, soil thermal balance, economics and environmental benefits of the system under various schemes and operating conditions were simulated and analyzed. Through a comparative analysis of the operating strategies, the optimal strategy that achieved the best performance was determined. Under the optimal strategy, the soil thermal imbalance rate after 10 years of operation was only 1%, the total energy consumption was significantly lower than that of a standalone ASHP system, and the initial investment was clearly lower than that of a standalone GSHP system. The results demonstrate that the hybrid system ensures soil thermal balance and high-efficiency operation while providing significant energy savings (a 28% primary energy savings rate compared to a standalone ASHP) and environmental benefits (reducing annual CO₂, SO₂, NOx, and dust emissions by 56.5 t, 384.2 kg, 361.6 kg, and 339 kg, respectively). Therefore, the emission of atmospheric pollutants such as CO₂, SO₂, NOx, and dust can be effectively reduced, thus providing an important reference for the development of building energy-saving technologies under the “dual carbon” goals. Full article

To address the issue of performance degradation resulting from continuous thermal accumulation in the soil for conventional ground source heat pump (GSHP) systems in cooling-dominated regions, a hybrid ground source heat pump–domestic hot water system (HGSHP-DHW) is proposed, along with a corresponding mode-switching control strategy. The heat pumps for cooling, heating, and domestic hot water in the HGSHP-DHW share the same ground heat exchanger (GHE) group. To accommodate varying energy demands in different seasons, the configuration of the ground source/side loop is switched according to signals from the control strategy. The average soil temperature rise, the coefficient of performance (COP) of the heat pump units, the system performance factor (SPF), the life cycle climate performance (LCCP), and the net present value (NPV) are selected as comprehensive evaluation indicators for fifteen years of operation. A comparative analysis with traditional systems, including chiller–boiler (CB), cooling tower coupled hybrid ground source heat pump (CT-HGSHP) and GSHP, which are all equipped with an air source heat pump (ASHP) for DHW, is also conducted. By the 15th year, the average soil temperature rise in the HGSHP-DHWs is 4.94 °C, a reduction of 55.5%, effectively alleviating soil thermal accumulation. In terms of energy efficiency, the SPF is 3.79, an increase of 70.8% with 43% reduction in the accumulation of energy consumption (P_ac), achieving high-efficiency and energy-saving operation. For environmental performance, the LCCP is 2,435,587 kgCO₂, a reduction 38.8% in carbon emissions, showing a remarkable emission reduction effect. In respect of economic returns, the NPV is 644,867 CNY, which is positive and indicates favorable investment viability. Full article

Ground source heat pump (GSHP) systems, while energy-efficient, often face persistent soil thermal imbalance in heating-dominated severe cold regions, which undermines their long-term performance and sustainability. This study proposes a TRNSYS-GenOpt framework for the life-cycle cost optimization of hybrid GSHP systems integrating electric boilers and geothermal regulation towers. A transient model for a 5650 m² fire station in Changchun was developed, employing the Hooke–Jeeves algorithm to co-optimize boiler capacity, borehole depth, and geothermal regulation tower airflow under constraints on heating supply temperature and soil thermal balance. Time-of-use electricity pricing was incorporated for realistic operational economics. The optimized configuration (148 m, 864.8 kW, 290,400 m³/h) achieved a minimum 20-year life-cycle cost of CNY 1.13 million. Sensitivity analysis revealed “rigid design, flexible cost” characteristics: optimal parameters remained invariant across discount rate variations (3.5–7.5%) and equipment costs (±20%), while life-cycle cost showed the highest sensitivity to electricity pricing and discount rates. The long-term simulation confirmed compliance with all physical constraints. This methodology demonstrates that thermodynamic constraints supersede economic trade-offs in severe cold climates, providing engineers with a reliable tool for sustainable hybrid geothermal system design. Full article

This study investigates the soil thermal imbalance of ground-source heat pump (GSHP) systems in residential buildings in cold regions and evaluates their economic and low-carbon performance. A case study is presented of a two-star green-certified residential building in Qingdao. The building exhibits a high heating load in winter, a low cooling load in summer, a long heating season, and large load fluctuations. To tackle these characteristics, a composite energy system combining a ground-source heat pump, a peak-shaving chiller, and a peak-shaving boiler is proposed. Three scenarios are designed, in which the ground-source heat pump covers 45%, 50%, and 52.6% of the winter peak heating load, respectively. These are compared with a conventional municipal heating scheme. Load simulation, techno-economic analysis, and carbon emission assessment are performed. The results show that the scheme in which the ground-source heat pump handles 50% of the peak heating load achieves the best overall performance. It reduces the soil thermal imbalance rate from 34.47% to 7.1% and obtains the lowest 10-year life-cycle cost. The annual carbon emission reaches 32.58 kgCO₂/(m²·a), representing a 33% reduction compared with municipal heating. Seasonal and diurnal optimized operation strategies are further proposed based on the optimal solution. The results provide theoretical and engineering guidance for the design and operation of low-carbon energy systems in green residential buildings in cold regions. Full article

This study analyzes the feasibility of increasing the energy and economic efficiency of a residential heating and domestic hot water (DHW) preparation system with a solar-assisted air-to-water heat pump (AWHP), implemented in southeast Romania. The following options are evaluated from the sustainability point of view (energy, economic and CO₂ emissions): renovation of the building and modernization of the system by integrating an electric accumulator, increasing the capacity of photovoltaic panels (PV) and solar thermal collectors (STCs), and the option of replacing the AWHP with a ground-source heat pump (GSHP) with a vertical loop (GSHP-VL) and a GSHP with a horizontal loop (GSHP-HL). The energy performance of heating systems was simulated using GeoT*SOL software. The results show that by renovating a home, the energy requirement for heating decreased by about 58%; therefore, following the current financial rules applied to prosumers, the GSHP-VL system has the best energy performance (electricity consumption and solar coverage rate of this consumption), economic performance (investment recovery period and annual operating cost) and environmental performance (lowest CO₂ emissions) and that through a government program that promotes energy efficiency and the use of renewable energy sources in homes, capital costs can be reduced by (43–57)% in the case of systems with HP, PV and electric storage. This study shows that a 5 kW PV system combined with 5 kWh battery cannot cover the full heat demand of a medium-to-large house during the winter, and for full energy independence, a larger PV array paired with a higher-capacity battery is necessary. Generous government subsidies amounting to 50% can reduce the payback period for such investments from (11.26–14.68) years to (5.86–7.26) years. Full article

In ground-source heat-pump (GSHP) systems equipped with a single U-tube borehole heat exchanger (BHE), the heat-carrier fluid in the return leg may release heat to the surrounding ground in the shallow part of the borehole. From a fluid energy balance perspective, this is an exothermic process; however, it is detrimental during heating operation: It lowers the effective source temperature available to the heat pump and therefore degrades the overall coefficient of performance (COP). This study proposes a measurement-driven procedure to determine the exothermic transition depth $z_{\uparrow }^{*}$ from temperature profiles recorded at multiple depths along the ascending (return) pipe. The borehole is discretized into axial segments and, assuming a constant mass flow rate, the linear heat-exchange rate is estimated from the segment-wise enthalpy change. Time integration yields the segment-wise net energy exchange $Q_{\uparrow ,i}$, which is then classified as exothermic or endothermic using an uncertainty-based threshold derived from the standard uncertainty of the temperature sensors. The exothermic transition depth $z_{\uparrow }^{*}$ is defined as the first statistically stable sign change in the integrated segment energy (from exothermic to endothermic) and is obtained by linear interpolation between adjacent segment centres. By summing the exothermic energy exchange and the corresponding average loss power, an equivalent change in source-side outlet temperature $∆T_{out}$ is estimated and interpreted in terms of COP impact using a Carnot-scaled surrogate model. For two representative operating conditions, $z_{\uparrow }^{*}$ was found at $31.17 \mathrm{m}$ and $24.01 \mathrm{m}$, respectively, while the average exothermic loss power remained approximately 0.48 kW. The estimated $∆T_{out}$ ranged from $0.52$ to $0.75 \mathrm{K}$, corresponding to a diagnostic COP improvement if this parasitic exothermic exchange could be mitigated. The present results should therefore be interpreted as a case study-based demonstration of the method on one instrumented borehole rather than as a universal quantitative prediction for other sites or borehole fields. Full article

The pursuit of carbon neutrality demands advanced low-carbon energy processes and their effective integration into building systems. Ground-source heat pumps (GSHPs) offer a key pathway for decarbonizing heating, yet their cold-climate application is compromised by soil thermal imbalance, which degrades their long-term efficiency. This study proposes and evaluates an innovative air-assisted GSHP system that integrates a vegetable greenhouse with a zoned borehole configuration for seasonal thermal storage to achieve carbon neutrality. The system segregates boreholes into core and peripheral zones to establish a controlled soil temperature gradient, enabling cascaded heat storage and thermal optimization. A comprehensive year-long field test was conducted on a residential building in Harbin, China. The results demonstrate that the system reliably maintains comfortable indoor conditions during severe winters, achieving average seasonal COPs of 3.82 for the heat pump unit and 2.85 for the overall system. The zoned operation strategy successfully generated a significant intra-field soil temperature gradient, with a maximum differential of 5.9 °C between the core and peripheral boreholes during charging. The measured heat extraction-to-storage ratio was 0.598, confirming effective cascaded utilization. From an environmental perspective aligned with low-carbon energy technologies, the system achieves annual savings of 8.66 tons of standard coal and a net CO₂ reduction of 1.3 tons when accounting for regional grid carbon intensity. This research provides empirical validation and practical design guidance for implementing efficient GSHP systems in severely cold regions, thereby contributing substantively to building sector decarbonization. Full article

For ground source heat pump (GSHP) systems, conventional control strategies often suffer from significant hysteresis, leading to energy waste and occupant discomfort. This study proposes and validates a novel Prediction Self-Adaptive Control (PSAC) technology that hybridizes deep learning foresight with robust engineering feedback loops. The architecture integrates a CNN-LSTM model to forecast building thermal loads with high fidelity, and this prediction drives a macro-scale unit commitment module that optimizes chiller sequencing. Simultaneously, a micro-scale self-adaptive feedback mechanism dynamically resets the chilled water supply temperature and modulates pump frequency to eliminate the residual error between the predicted state and the actual building demand, ensuring precise load matching. Field implementation in a 62,500 m² residential complex in Shanghai demonstrated that the CNN-LSTM model achieved a load forecasting accuracy within a ±10% error margin, the PSAC strategy significantly outperformed baseline constant-temperature controls, maintaining indoor temperatures between 23 and 26 °C and relative humidity between 30 and 55% and the system achieved a weekly average System Coefficient of Performance (SCOP) of 3.91 compared to the baseline of 3.30, resulting in an 15.6% reduction in total energy consumption. By decoupling predictive planning from adaptive execution, the system offers a scalable, robust, and highly efficient solution for the decarbonization of HVAC systems in complex climate zones. Full article

This study evaluates the feasibility of using a ground-coupled ammonia heat pump as a heat source for the district heating system in Ustka, Poland. A three-dimensional transient thermal model of a 122-borehole field was developed in ANSYS 2023 R1 using local geological data and hourly meteorological inputs. Three extraction loads—0.50, 0.75, and 1.00 MW—were analysed, together with regeneration periods of one month (August) and six months following the heating season. Ground temperatures were assessed across all geological layers down to 250 m. The simulations show that each of the tested loads leads to a noticeable and lasting reduction in ground temperature. For 1.00 MW, the temperature in the main heat-exchange layers remains more than 2 K below the initial value even after six months of regeneration. At 0.75 MW the deficit is smaller but still persists in the layers that dominate heat transfer. Even the 0.50 MW scenario does not return to thermal balance: the active layers stay more than 1 K cooler after the regeneration period, indicating cumulative long-term cooling. Although the model includes standard engineering simplifications, the large-scale thermal behaviour is consistent across all scenarios. The analysis shows that the analysed GSHP (ground-source heat pump) configuration cannot serve as a primary heat source for the Ustka network in the analysed configuration. Alternative low-emission solutions, such as air-source heat pumps supported by renewable electricity, are more suitable for this site. Full article