https://doi.org/10.6110/KJACR.2026.38.2.65

Dong Sik Lee ; Min Ji Kwon ; Soo Hyun Na ; Jaehyeok Heo ; Rin Yun

When Power-to-Heat (P2H) technology is integrated with Phase Change Material (PCM)-based thermal energy storage, it enables load shifting and peak shaving. This study quantitatively evaluates and compares the performance of P2H systems utilizing air-source, water-source, and ground-source heat pumps integrated with PCM thermal storage for a poultry house in Jeju. Dynamic simulations were conducted using TRNSYS, incorporating an empirically validated PCM tank performance model derived from previous thermal response analyses. The water-source heat pump system exhibited the best overall performance, with daily average coefficients of performance (COPs) of 3.0 for heating and 4.8 for cooling, and corresponding system-level energy consumption of 113.2 kWh and 62.4 kWh, respectively. The air-source heat pump displayed the lowest COPs, at 2.4 for heating and 2.3 for cooling, with system energy consumption of 107.2 kWh and 84.5 kWh. The ground-source heat pump system achieved the highest cooling COP of 5.1 and a relatively high heating COP of 3.1, with system energy consumption of 112.2 kWh for heating and 82.2 kWh for cooling. Although the ground-source heat pump demonstrated superior efficiency in HP-only performance, its total energy use increased due to additional circulation pump loads. The PCM-based storage tank exhibited significantly enhanced thermal storage capacity?69.0 MJ for heating and 55.0 MJ for cooling?approximately twice that of a conventional water storage tank, which has capacities of 32.5 MJ for heating and 27.7 MJ for cooling, thereby contributing to peak load reduction.

https://doi.org/10.6110/KJACR.2026.38.2.75

Yul-Ho Kang ; Sang-Moo Woo ; Young-Chull Ahn

This study assesses thermal uniformity at the crop cultivation height of 1.5 m and the heating load of a 40-ft container-type smart farm (interior dimensions: 9,600 mm × 2,290 mm × 2,557 mm) maintained at an indoor setpoint of 25℃. Using computational fluid dynamics (CFD), we analyzed the impacts of outdoor temperatures (-30℃, -20℃, -10℃, and 0℃), insulation thicknesses (150 mm, 200 mm, 250 mm, and 300 mm), and the number of fan coil units (FCUs; 1, 2, and 3). As outdoor temperatures rose from -30℃ to 0℃, the temperature deviation at crop height decreased from 10.0℃ to 4.6℃, while the heating load decreased from 833.0 W to 378.8 W, representing a 54.5% reduction. Increasing insulation thickness from 150 mm to 300 mm lowered the temperature deviation from 10.0℃ to 5.3℃ and the heating load from 833.0 W to 433.4 W. Adding more FCUs?first from one to two, then to three?reduced the temperature deviation to 7.1℃ and 6.1℃, respectively. While changes in insulation thickness effectively decreased both heating load and temperature deviation, increasing the number of FCUs had minimal impact on heating load but provided a greater reduction in temperature deviation than increasing insulation thickness from 150 mm to 250 mm. In extremely cold conditions, optimizing insulation performance and internal airflow should be tailored to the container’s area and geometry.

https://doi.org/10.6110/KJACR.2026.38.2.86

Dong-Soon Jeon

Research and development efforts have been ongoing to replace fossil fuel-based energy systems with high-temperature heat pumps (HTHPs) in response to environmental challenges like global warming. This study investigates the use of hydrofluoroolefins (HFOs), hydrochlorofluoroolefins (HCFOs), and natural refrigerants in HTHPs operating at temperatures above 130℃. Performance evaluations were conducted based on thermophysical properties. A review of existing literature assessed the thermodynamic properties, ozone depletion potential (ODP), global warming potential (GWP), and safety group (SG) classifications of the candidate refrigerants. The findings suggest that R1336mzz(Z), R1130(E), and R718 are the most suitable refrigerants for operating temperatures above 160℃, while R1130(E) and R718 are the best choices for temperatures exceeding 200℃.

https://doi.org/10.6110/KJACR.2026.38.2.96

Ju Hong Oh ; Seon In Kim ; Eui Jong Kim

Building Energy Management Systems (BEMS) generate significant operational data, but this data is often underutilized for basic monitoring and does not lead to meaningful improvements in operational efficiency. This passive use of data results in unnecessary energy consumption and reduced occupant comfort, with overcooling being a common HVAC inefficiency. This study introduces a three-phase analytical framework that utilizes BEMS data to systematically diagnose overcooling issues and provide actionable operational recommendations. The framework consists of: (1) Data Preparation, (2) Problem Diagnosis, and (3) Operation Guidance. The main contribution is the causal identification of temporal patterns, spatial distribution, and root causes of overcooling through statistical analysis and data mining techniques. These insights are translated into conditional execution rules that enable non-expert operators to implement solutions. An application of this framework to summer cooling data from a Zero Energy Building revealed that overcooling occurred during 70.7% of cooling operation hours. Root cause analysis indicated that overcooling is a systematic issue, with hourly patterns correlated to external environmental conditions. This research offers managers a practical methodology to improve energy efficiency and occupant comfort by transforming passive BEMS data into actionable control strategies.

https://doi.org/10.6110/KJACR.2026.38.2.108

Youngsub An ; Haneol Kim ; Jongkyu Kim ; Min-Hwi Kim

This study developed an energy-sharing platform technology and conducted a long-term evaluation of the energy self-sufficiency ratio for a smart village community in Busan. This community serves as a large-scale demonstration site to assess the extent to which renewable energy installed in buildings can meet the electricity and thermal energy needs, thereby contributing to greenhouse gas reduction in the building sector. The community comprises 56 residential households, a cultural center, and a community data center. The self-sufficiency ratio for each building was analyzed using long-term data collected over 22 months, from March 2022 to December 2023. In the residential buildings, we examined the self-sufficiency ratio for five major energy loads?heating, cooling, domestic hot water, ventilation, and lighting?across the 56 households, in relation to the renewable energy produced by building-integrated photovoltaics (BIPV). We also assessed the self-sufficiency ratio for the electric vehicle (EV) load installed in the parking lot, which had a minimal impact on the total energy consumption of the residential households. The energy self-sufficiency ratio for the cultural center and the community data center was significantly influenced by their electricity consumption patterns.