Heat Pump Research Articles

Forecasting regional in-situ thermal conductivity of soil based on tree-based ensemble learning

Borehole heat exchanger is essential component in ground-source heat pumps (GSHPs) for developing geothermal energy, where device efficiency depends on the thermal conductivity of soil. Although the thermal response test is generally used to measure this parameter, its time-consuming and susceptibility to test conditions can impact the accuracy of the test. To address this issue, the study conducted shallow geothermal surveys to establish a comprehensive dataset, enabling the construction of the in-situ thermal conductivity predictive model. By selecting seven input features, four classic tree-based ensemble learning models and stacking algorithms were used. Among all the post-tuned models examined, XGBoost-RF emerged as the standout performer, boasting an impressive R2 value of 0.9809 along with the lowest RMSE and MAE. Notably, it demonstrated generalization capabilities, with errors consistently staying within 5 % during the validation process. Additionally, the SHapley Additive exPlanations (SHAP) was used to enhance the interpretability of the model. Among these, the weighted thermal conductivity of the geotechnical was the most influential feature, while groundwater conditions such as permeability coefficient and aquifer thickness were also significant factors. This study provides a rapid and precise prediction of regional in-situ thermal conductivity. It leads to effective decision-making in the design stage of GSHPs.

Extension of a low-tech Model Predictive Control (MPC) algorithm for grid-supportive heat pump operation

This paper presents the further development of a low-tech Model Predictive Control (MPC) for the grid-friendly operation of heat pumps. The developed algorithm is already available in the literature [1] and successfully implemented in multiple buildings. The overall goal is, to predictively optimize comfort parameters taking into account weather forecast data for 48 h. A simple mathematical building model and an optimization function are used to calculate the heating (or cooling) requirement and determine the optimum heating (cooling) output curve over time.Based on the initial results, the algorithm is extended to include an energy price forecast. This modification enables the simultaneous optimization of comfort and heat supply costs. This forecast-based cost & comfort function is designed for the use of heat pumps in buildings with thermally activated components (TAB). The extension enables the MPC to process day-ahead electricity prices or other price signals in addition to weather forecast data. This means that the operation of heat pumps can be shifted to periods that are beneficial to the grid.The algorithm is analysed and validated in a Matlab/Simulink building simulation for a heating period of one sample month. A case study with different price scenarios is the main part of this paper. Depending on the assumed price fluctuation, the simulation leads to cost savings between 6.65 % and 12.5 % for the observation period of one month. The simulation results thus show that heat generation can be shifted to times with lower electricity prices, which leads to a significant reduction in heating costs without any significant loss of comfort. In conclusion, the developed low-tech MPC enables grid-supportive operation of heat pumps.

Implementation and validation of optimal start control strategy for air conditioners and heat pumps

Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. The future work will look at using a different model for the days after weekends and holidays.

Clogging mechanism of injection wells in open-loop ground source heat pump systems clarified from flow rate and groundwater level

Clogging mechanism of injection wells in open-loop ground source heat pump systems clarified from flow rate and groundwater level

Development of ground source heat pump systems in agriculture and land-based aquaculture

Development of ground source heat pump systems in agriculture and land-based aquaculture

Technology Trends and Market Forecasts of Ground Source Heat Pump Systems

Technology Trends and Market Forecasts of Ground Source Heat Pump Systems

Research and development of ground source heat pump system for Installation in facilities with hot water supply load

Research and development of ground source heat pump system for Installation in facilities with hot water supply load

Regional-Scale Assessment of the Potential for Shallow Geothermal Energy Development Using Vertical Ground Source Heat Pumps

Shallow geothermal energy (SGE) is a widely prevalent geological resource underground, and its utilization offer significant energy conservation and emission reduction benefits, contributing to the achievement of carbon neutrality goals. Assessing the development potential of regional SGE can ensure sustainable development of these resources and prevent adverse effects induced by overexploitation. Jiangsu Province, a developed region in the eastern coastal area of China, has a strong demand for cooling and heating in urban buildings. The primary form of utilizing SGE in this area is through vertical ground source heat pumps (VGSHP). Based on the analysis of the impact of regional geological conditions on the development of SGE, this study specifically evaluated the suitability of developing SGE through VGSHP. After excluding areas unsuitable for development, the heat exchange capacity, heating or cooling area per unit area, and energy conservation and emission reduction benefits of VGSHP were calculated. The results indicate that the area suitable and moderately suitable for developing SGE through VGSHP in Jiangsu Province amounts to 76,453 km2. The total heat exchange capacity for summer is 1.21 × 109 kW, which can provide cooling for an area of 1.21 × 1010 m2. The total heat exchange capacity for winter is 8.70 × 108 kW, which can provide heating for an area of 1.09 × 1010 m2. The annual available resource amount is 2.68 × 1012 kWh, equivalent to 3.30 × 108 tons of standard coal, and a CO2 reduction of 7.86 × 108 tons.

Operating characterization and performance optimization of high-temperature heat pumps: A comparative energy, economic and environmental analysis

The high-temperature heat pump (HTHP) operates under severe conditions and there is a need for further research into its operating characteristics and performance optimization. In this study, the effect of three optimization strategies, namely vapor injection, subcooling and cascade type, on the system characteristics of the HTHP at varying ambient temperatures (Tam) was investigated. Subsequently, a comparative analysis focusing on energy, economy and environment was conducted. As the result shows: The introduction of vapor injection creates the presence of an optimal intermediate pressure and greatly improves the COP of HTHP by a range of 14.7–52.6 %, while the application of an economizer further elevates the COP by 0.6–7.0 %; The cascade cycle exists an optimal intermediate temperature and has operating performance advantages at lower Tam. As the condensing temperature increases from 120 °C to 130 °C to 140 °C, the turning Tam rises from 54 °C to 63 °C to 71 °C, respectively; HTHP requires a certain level of Tam to maintain a higher level of system performance to meet economic and environmental requirements. In the research framework, HTHP begins to show economic advantages at a Tam of 10 °C, while it can only generate benefits of emission reduction at a Tam of 65 °C or higher.

Economy and energy flexibility optimization of the photovoltaic heat pump system with thermal energy storage

Photovoltaic systems have been widely applied in building energy systems. However, with the sharp increase in demand of electricity in buildings during heating and cooling seasons, the uncertainty of photovoltaic generation further exacerbates the peak-valley difference in electricity use. To improve the economy and energy flexibility of buildings in hot summer and cold winter zones of China, a rule-based operation strategy was proposed for the photovoltaic heat pump with thermal energy storage system to optimize the size of the thermal energy storage system and system operation, with aims of minimizing the total annual cost of the system and maximizing the self-consumption rate of the photovoltaic generation. The effects of grid export power limits, grid import power limits, feed-in tariffs, and PV generation on the system operation optimization results were also investigated. The results indicated that by integrating the thermal energy storage system into the photovoltaic heat pump system, the self-consumption rate of the photovoltaic generation was reduced by 2.39 %, the total annual cost of the system was decreased by 6.61 %, and the payback period of the thermal energy storage system was 1.31 years. The optimum size of the thermal energy storage system and the self-consumption rate of the photovoltaic generation decreased with the increasing grid export power limits and grid import power limits. In contrast, higher grid export power limits, grid import power limits, feed-in tariffs, and PV generation all resulted in a lower total annual cost. This study provided a systematic design and operation optimization method for building energy systems.

The Benefits of Incorporating Vegetables and Fruits Flours into Grain-Based Foods

A study of food losses (flours) from vegetables and fruits obtained from production of juices from purple carrot, purple yams and red apple was conducted. The vegetables and fruits are with very good quality and good price. They are dried in a heat pump dryer, at an initial temperature of 45 ° C and circulating air with an initial moisture content of 20% at constant (5.6 m/s) and variable speed, in a thin layer, with transversely oriented air flow relative to the product layer.

Effects of temperature-dependent viscosity on thermal drawdown-induced fracture flow channeling in enhanced geothermal systems

Harnessing geothermal energy from an enhanced geothermal system (EGS) highly depends on fracture flow and heat transport processes. Thermal drawdown-induced thermal stress has been characterized as a major reason for severe fracture flow channeling (short-circuiting), which further leads to premature thermal breakthrough and impairs long-term thermal performance. In the present study, we quantitatively analyzed a potential flow channeling mitigation mechanism, i.e., the increase of water viscosity with temperature reduction. Through a field-scale single-fracture EGS model that incorporates thermal-hydro-mechanical coupled processes and temperature-dependent water viscosity, we demonstrate that the increase of water viscosity during heat extraction promotes a dispersed fracture flow pattern, which can effectively mitigate thermal drawdown-induced flow channeling and improve long-term thermal performance. The mitigation effect is more noticeable for homogeneous aperture scenarios than for heterogeneous aperture scenarios, especially in the early period of heat production. With a higher in-situ stress and smaller rock Young's modulus, the flow channeling effect of thermal stress becomes weak, and therefore the temperature-dependent viscosity exhibits a more significant flow channeling mitigation effect. The results from the current study provide valuable insights into the optimization of fracture flow and heat transport to achieve more efficient and sustainable energy production from EGSs.

Flow boiling in dimpled plate heat exchangers with different geometric parameters: Analysis of asymmetric channels

The evaporators of heat pumps extract heat from the environment. To improve the heat pump performance in cold environments, evaporators must operate with small temperature drops of the heat source, which requires large flow rates of the secondary fluid. This paper discusses dimpled plate heat exchangers (DPHEs) with flexible flow section areas. The flow boiling of R410A is measured in six channels. The flow section area ratios of neighboring channels are 0.86–2.83. To analyze outlet superheat, the two-phase and dryout zones are distinguished using infrared measurement. The dryout zone is a function of the superheat and mass flux, which is quantified. The heat transfer coefficients (HTCs) increase with increasing mass fluxes and heat fluxes. Compared with experimental results from a large scope, the present data fall into the combined regimes of convective boiling and nucleate boiling. Smaller hydraulic diameters slightly enhance the heat transfer. The experimental HTCs are accurately predicted by a correlation of chevron plate heat exchangers (CPHEs). The performances of the DPHEs and CPHE are compared for small temperature drops in cold environments. The DPHEs have superior performance by mitigating the unbalance of mass fluxes. The typical overall heat transfer coefficient is improved by 62%. The improvement depends on the flow section area ratios.

Energy and Exergy Analysis of Transcritical CO2 Cycles for Heat Pump Applications

Energy and Exergy Analysis of Transcritical CO2 Cycles for Heat Pump Applications

An analytical solution to optimal heat pump integration

Heat pump integration has a large potential for reducing carbon emissions and operating costs of industrial processes. The Break-even COP method determines the maximum economically- or environmentally feasible heat pump temperature and the level of process heat electrification under specified economic conditions. However, this method fails to capture the optimal heat pump temperature and the possible emissions- and costs reduction in sensible heat processes. The present work introduces an analytical equation based on the Lorenz efficiency approach to determine the optimal heat pump sink temperature, maximizing the operating costs savings or the emission savings. Furthermore, it advances the break-even method to account for heat pumps with a temperature glide by applying a Lorenz efficiency approach. The method is applied to a spray-drier case study, showing a reduction on operation costs of 7.8 % and emissions by 11.9 % by a partial process electrification of 32 %. A parameter study is conducted, underscoring the importance of accurate predictions of the Lorenz efficiency factor and the electricity-to-fuel price and emissions ratios in heat pump integration studies.

Experimental investigation of a small-scale reversible high-temperature heat pump − organic Rankine cycle system for industrial waste heat recovery

Innovative technologies are required to mitigate the challenges of climate change. A reversible high-temperature heat pump (HTHP) − organic Rankine cycle (ORC) system can be used for effective utilisation of industrial waste heat in the lower temperature band <100 °C. The system can provide useful process heat for industrial processes by operating in HTHP mode or generating power in ORC mode. This paper presents the experimental investigation of the reversible system in both HTHP and ORC modes. A single scroll unit was selected for the compressor (HTHP) and expander (ORC) roles, keeping the system compact. A HCFO refrigerant, R1233zd(E), with a low GWP value, was chosen as the working fluid for both operating modes. When operated in HTHP mode, a maximum compressor overall isentropic efficiency of 73.4 % and a COPmech of 4.8 (ΔTlift,rside = 41 K, Tsf,ev,in = 60 °C) was obtained. In ORC mode, the maximum net power output was 512.4 W (Tsf,ev,in = 90 °C, rp = 2.3), overall cycle efficiency was 3.01 %, and overall isentropic efficiency of the expander was 54.6 %. The technical limitations encountered, and solutions put in place during the experimental testing campaign are discussed in detail.

High-Temperature Heat Pumps for Electrification and Cost-Effective Decarbonization in the Tissue Paper Industry

High-Temperature Heat Pumps for Electrification and Cost-Effective Decarbonization in the Tissue Paper Industry

Urban Geothermal Resource Potential Mapping Using Data-Driven Models—A Case Study of Zhuhai City

Geothermal energy, with its promise of sustainability and a minimal environmental impact, offers a viable alternative to fossil fuels that can allow us to meet the increasing energy demands while mitigating concerns over climate change. Urban areas, with their large energy consumption, stand to benefit significantly from the integration of geothermal systems. With the growing need to harness renewable energy sources efficiently, the detection of urban subsurface resources represents a critical frontier in the pursuit of sustainability. The Guangdong Bay area, known for its abundant geothermal resources, stands at the forefront of this green energy revolution, so, in our study, we chose to evaluate Zhuhai City, which is a city representative of the resource-rich area of Guangdong. With the progress of geographic information system (GIS) technology, the land surface temperature (LST) has been used to monitor the spatial distribution characteristics of geothermal anomalies. However, relatively few studies have been conducted in the field of urban geothermal resources. In this study, we calculated the LST of Zhuhai City using Landsat 8 remote sensing data and then investigated the distributions of geothermal hot springs. Spatial data layers were constructed, including the geological structure, DEM and derivatives, lithology, and urban regions, and, based on technology with the integration of machine learning, their spatial correlations with geothermal anomalies were analyzed. The support vector machine (SVM) and the multilayer perceptron (MLP) were employed to produce maps of potential geothermal resources, and their susceptibility levels were divided into five classes: very low, low, moderate, high, and very high. Through model interpretation, we found the moderate-susceptibility class to dominate at 26.90% (SVM) and 46.27% (MLP) according to the two models. Considering the influence of artificial areas, we also corrected the original LST by identifying urban areas of thermal anomalies via the urban thermal anomaly leapfrog fusion extraction (UTALFE) method; following this augmentation, the results shifted to 24.16% (SVM) and 28.67% (MLP). Meanwhile, the area under the curve (AUC) values of all results were greater than 0.65, showing the superior performance and the high applicability of the chosen study area. This study demonstrates that data-driven models integrating thermal infrared remote sensing technology are a promising tool for the mapping of potential urban geothermal resources for further exploration. Moreover, after correction, the reclassified LST results of urban areas are more authentic and suitable for the mapping of potential geothermal resources. In the future, the method applied in this study may be considered in the exploration of more southeastern coastal cities in China.

Modeling the impact of natural roughness of tension joints on heat transport

The understanding of heat transport in fractures is crucial for mining geothermal systems. Studies of heat transport in natural fractures at scales comprised between those of laboratory experiments and those of field tracer tests are seldom. To bridge the gap, a joint surface with characteristic plumose was scanned in the field using LiDAR technology. The scanned surface was used to build a numerical model of mode 1 fracture. Fluid flow and heat transport were modeled solving the steady-state Stokes equation and assuming Fourier transport, respectively. We considered three different fracture apertures and varied systematically roughness in order to investigate the impact of plumose on fluid and heat transport. The 3D velocity flow fields were characterized by mean hydraulic aperture and by statistics on the directional components of the velocity vector. The method of temporal moments was used to extract first and second moments from temperature breakthrough curves. Heat transport parameters (local and macroscopic) were calculated from first and second moments.We show that hydraulic aperture and the longitudinal component of the velocity vector decrease with increasing roughness. The local variation of heat transport parameters is controlled by fracture roughness. For the macroscopic transport parameters, several transport regimes were identified. At low fracture aperture (i.e. 1 mm), conductive regime dominates heat transport in agreement with low Péclet numbers. In this case, fracture roughness affects the transport parameters via the loss of hydraulic aperture. With higher aperture (i.e. 3 mm) geometrical dispersion regime is dominant, roughness controlling the amplitude of transport parameters. At 5 mm aperture, transition from geometrical to Taylor dispersion occurs and the roughness tends to decrease dispersion and dispersivity according to the mean flow velocity.

Innovative approaches to overcome inadequate measurements in heat pumps with non-fluorinated refrigerants

As the transition away from fluorinated refrigerants occurs due to F-gas and PFAS regulations, heat pumps face the challenge of adapting to new non-fluorinated refrigerants. Evaluating heat pump performance during this transition is challenging due to limited operational data on the new refrigerants. Conducting long-term tests to fully understand a heat pump’s performance with all possible refrigerants is labor-intensive and economically burdensome. This study introduces two complementary reduced-parameter models to assess heat pump performance across multiple new natural refrigerants despite limited data. A transfer learning model, leveraging knowledge from existing data-rich refrigerants, has been developed to evaluate the performance of heat pumps using new, data-scarce natural refrigerants. However, due to the lack of transparency in transfer learning models, semi-empirical models are being developed in parallel. The semi-empirical models, across multiple natural refrigerants, are capable of analyzing the thermodynamics and heat transfer processes within the heat pump system by utilizing only limited easy-to-measure variables as inputs. The transfer learning model demonstrates high accuracy for all outputs across seven refrigerants with RRMSE all below 7%. In comparison, the semi-empirical models are less accurate, with RRMSE results under 25% for all parameters except compressor power. By integrating these two models, a comprehensive framework is established for assessing heat pump performance with both high accuracy and a deeper understanding of the system.