• Energy Research

Ground-source heat pump (GSHP) systems coupled with borehole heat exchangers (BHEs) are widely used as a renewable energy source. However, the high initial costs to install the BHEs still acts as an obstacle in the expansion of these renewable energy source systems. Specifically, in South Korea, a typical residential type corresponds to an apartment building with a high building-to-land ratio for land efficiency, and thus the space to install the BHEs is usually insufficient. Furthermore, the high initial cost issue of BHEs makes it difficult to ensure the feasibility of GSHP projects in this type of a situation. This study proposes a novel BHE sizing method to support the process of sizing energy sources in the design development phase of a construction project. Life cycle cost (LCC) analysis was combined with a tool to optimize BHE sizing by considering various economic aspects. Entering water temperatures (EWT) to heat pumps in conjunction with the LCC were used to define objective functions. Consequently, Pareto optimal solutions were obtained on the EWT–LCC plot. A group of Pareto optimal solutions forms a Pareto-curve, and each point on the curve indicates a possible sizing scenario or alternative. Finally, it is possible for decision makers to compare the solutions that include both technical and economic information. The Pareto optimal solutions are expected to support proper decision making in the early design phase.

Abstract The duct storage (DST) model is one of the most widely used borehole heat exchanger (BHE) models owing to its fast calculation scheme and usability. However, the DST model can simulate only regularly placed BHEs, particularly in cylindrical borefield configurations. As a possibility to describe irregular borefield configurations by adjusting BHE spacing has been reported, we propose optimal values of BHE spacing for typical irregular BHE cases using the GenOpt optimization tool. A regression model based on a set of results obtained from the optimization is proposed to calculate the modified spacing for the DST model directly without optimization simulations. The proposed regression model fits to the datasets of the optimization with an accuracy of 96.5% in predicting the modified BHE spacing. The differences in time-averaged EWTs between the DST model with the proposed modified spacing and a reference model are close to zero, and they are less than 0.5 °C. However, other borefield configurations that have not been used for the model development can result in higher errors.

Abstract Renewable energy systems (RESs) in urban areas must meet high energy demands with a limited space and satisfy the institutional requirements to reduce greenhouse gas (GHG) emissions. This study derives the RES design options that covers all building loads, meet the institutional requirements, and minimize the initial investment cost for a community center in an urban residential apartment complex. To achieve this, a multi-objective optimization method was employed. TRNSYS was used for the RES system analysis, and the main design variables of the RES were optimized using the developed tool. The Pareto solutions were obtained by differentiation of the initial design and they were derived through optimization. The optimal solutions required an initial investment cost that was 13.5–20.9% less than the initial designs and yielded an RES generation 5.2–24.4% higher than the initial designs. Therefore, they can sufficiently meet the institutional requirements.

Installing renewable energy systems for zero-energy buildings has become increasingly common; building integrated photovoltaic (BIPV) systems, which integrate PV modules into the building envelope, are being widely selected as renewable systems. In particular, owing to the rapid growth of information and communication technology, the requirement for appropriate operation and control of energy systems has become an important issue. To meet these requirements, a computational model is essential; however, some unmeasurable parameters can result in inaccurate results. This work proposes a calibration method for unknown parameters of a well-known BIPV model based on in situ test data measured over eight days; this parameter calibration was conducted via an optimization algorithm. The unknown parameters were set such that the results obtained from the BIPV simulation model are similar to the in situ measurement data. Results of the calibrated model indicated a root mean square error (RMSE) of 3.39 °C and 0.26 kW in the BIPV cell temperature and total power production, respectively, whereas the noncalibrated model, which used typical default values for unknown parameters, showed an RMSE of 6.92 °C and 0.44 kW for the same outputs. This calibration performance was quantified using measuring data from the first four days; the error increased slightly when data from the remaining four days were compared for the model tests.

As the sizing of borehole heat exchangers (BHEs) is crucial for ground-source heat pump systems, which are becoming increasingly complex and diverse, novel sizing tools are required that can size both boreholes and connected systems. Thus, an optimization-based sizing method that runs in TRNSYS with other component models is proposed. With a focus on the feasibility of the method for typical BHEs, the sizing of irregularly placed boreholes using the well-known duct-storage (DST) model that inherently cannot describe irregular borefields is examined. Recently developed modification methods are used for the DST model. The proposed sizing method is compared with the existing ground loop heat exchanger (GLHE) sizing program. The results indicate that the proposed method has a genuine difference of approximately 3% compared with the GLHE, and the difference increases with the thermal-interference effects. A regression-based method selected to modify the DST model for describing irregular borefields exhibits acceptable sizing results (approximately 5% for test cases) despite the genuine difference. This study is the first to use the DST model for sizing BHEs under irregular borefield configurations, and the tests indicated acceptable results with an approximate difference of one borehole among a total of 30 boreholes in the test cases.

The earth provides a vast resource of groundwater from aquifers a few meters beneath the surface. Thus, buildings that use underground space must be equipped with dewatering wells to drain the permeated groundwater to the sewage pipelines to ensure the structural stability of the building. Although the inflowing groundwater temperatures and flow rates are stable enough for groundwater to be used as an energy source, 79% of the permeated groundwater is discarded through the sewers, generating significant sewerage expenses. This study introduced a novel heat exchanger module to utilize the permeated groundwater as an unused energy source using heat pumps, and the performance of the system was evaluated by TRNSYS simulations. First, the sizing of the unit heat exchanger module was proposed according to the mean inflow rate of the permeated groundwater. Second, the heat pump system was configured using multiple modules in the source-side loop. Finally, the performance of the proposed heat pump system was compared with that of a conventional air source heat pump using realistic load and temperature profiles. This preliminary study demonstrated interesting performance results, with a coefficient of performance for heating that was higher than that of a conventional heat pump system by 0.79. The results show the potential utilization of the systems for a construction project requiring large-scale underground spaces, where abundant groundwater is available.

This study proposes a simple ground heat exchanger design capacity that is applicable in the schematic-design stage for several configurations used for borehole heat exchangers (BHEs). Three configurations—single, compact, and irregular types—were selected, and the heat transfer rate per unit BHE was calculated considering heat interference. In a case study with a typical configuration and general range of ground thermal conductivity, the BHE heat transfer rate of the compact configuration decreased owing to heat interference as the number of BHEs increased. However, with respect to the irregular configuration, the heat transfer rate increased as the same number increased. This was attributed to the relatively large increment rate of the distance between the boreholes in the irregular configurations, making the heat recovery factor more dominant than the heat interference. The results show that the average heat transfer rate values per BHE applicable to each configuration type in the schematic-design stage were 12.1 kW for the single configuration, 5.8 kW for the compact type, and 10.3 kW for the irregular configuration. However, owing to the large range of results for each case study, the error needs to be reduced by maximally utilizing the information available at the schematic-design stage.

With increasing global concerns regarding indoor air quality (IAQ) and air pollution, concerns about regularly replacing ventilation devices, particularly high-efficiency particulate air (HEPA) filters, have increased. However, users cannot easily determine when to replace filters. This paper proposes models to estimate the dust loading levels of HEPA filters for an energy-recovery ventilation system that performs air purification. The models utilize filter pressure drops, the revolutions per minute (RPM) of supply fans, and rated airflow modes as variables for regression equations. The obtained results demonstrated that the filter dust loading level could be estimated once the filter pressure drops and RPM, and voltage for the rated airflow were input in the models, with a root mean square error of 5.1–12.9%. Despite current methods using fewer experimental datasets than the proposed models, our findings indicate that these models could be efficiently used in the development of filter replacement alarms to help users decide when to replace their filters.