http://doi.org/10.5207/JIEIE.2025.39.5.319

Younjoo Cho ; An-Seop Choi

Many logistics centers operate lighting continuously without considering occupancy or daylight conditions, resulting in significant energy consumption. Previous studies and overseas cases show that smart controls with occupancy and daylight sensing can reduce lighting energy consumption by up to 80%, indicating high applicability to logistics centers. This study categorized logistics operations into sorting, transportation, storage, and packaging to propose smart lighting control strategies for each work type. The proposed strategies integrate occupancy and daylight sensors, scheduling, and equipment signals to flexibly adjust lighting output while meeting required illuminance levels. Unlike one-size-fits-all approaches, these strategies reflect the specific characteristics of the work and the required illuminance levels, enabling flexible adaptation to various site conditions. Future research will quantitatively verify changes in power consumption and work efficiency by implementing the strategies in actual logistics centers, and will enhance control algorithms through on-site data collection and analysis.

http://doi.org/10.5207/JIEIE.2025.39.5.329

Kyung-Min Lee ; Chul-Won Park

When transient disturbances such as inrush and fault of the transformer occur, they can have negative effects on the power system, such as voltage drop, harmonic generation, CT distortion, and IED malfunction. Therefore, an appropriate model that considers the nonlinear characteristics of the CT magnetic body and an analysis of transient currents must be conducted in advance. This paper aims to analyze the transient phenomena of inrush and fault current using EMT tools in the process of developing a new transformer protection algorithm. First, the related theory of CT magnetic material based on Jiles-Atherton model is introduced. The CT modeling is performed using PSCAD, an EMT tool, for the corresponding model system based on single phase two wire distribution transformer. After verifying the accuracy of the model, the nonlinear characteristics of CT through Hysteresis curves are analyzed. Finally, the inrush and fault currents are analyzed.

http://doi.org/10.5207/JIEIE.2025.39.5.337

Pyeong-Kang Kim ; Seung-Ho Song

This paper proposes a method for estimating the output voltage and current by measuring the low-voltage side resonant current of a series resonant converter operating in discontinuous conduction mode(DCM) for filament power supply applications. The proposed estimation method does not require sensing on the output side, so the high voltage insulation problem of the filament power supply sensing circuit in which the output is connected to the high voltage terminal of several tens of kV is solved. Through operation mode analysis, a resonant current equation for each mode was derived, and a method was derived to estimate the output voltage and current using peak value information. The proposed estimation method achieved an error rate of less than 1.5% through simulation, and it was verified that the estimation method could be effectively applied.

http://doi.org/10.5207/JIEIE.2025.39.5.342

DaeSung Jung

In this paper, we study the design of the stator shape to reduce the copper loss of a permanent magnet motor. Generally, motor stator windings are made mostly of copper. To reduce copper loss, materials with higher conductivity and lower resistivity could be used. However, this approach is not desirable because it increases the cost of the motor. Therefore, increasing the coil diameter is considered to reduce copper loss. However, this leads to the problem of increased motor size. In this paper, we propose a stator shape design that addresses these constraints while effectively reducing copper loss. To verify the validity of the proposed design, simulation results were compared with experimental results.

http://doi.org/10.5207/JIEIE.2025.39.5.348

Jeong-Woo Park ; In-Woo Park

The study shows analysis of tribo-charging on the chemical treatment process machine of wet-line manufacturing site and the relaxation effects, so called static control on contact electrification by using an ionizer. When a product is loaded on a line type machine the product is affected by frictional contact of the multi-roller used in chemical treatment process machines of electro-component manufacturing processes such as PCB, MLCC, Camera module of mobile phone. If the charged products are discharged, It is affected on productivity efficiency of malfunction of the machine and has the possibility of an electric shock (displeasure or a second disaster) to a machine operator. This study verified of the static control efficiency of neutralization static charge build up on the multi-point roller conveyor machines of electro-component manufacturing processes.

http://doi.org/10.5207/JIEIE.2025.39.5.355

Jae-Chun Kim ; Kwang-Hyun Ro

This study examined the possibility of developing a time-series-based electricity demand response model by applying a VSM data set model generated from 30,000 household on BSEM in Quebec, Canada, to the demand response of the domestic electricity market. The CBL method, which has been adopted as a conventional demand forecasting method, has limitations in sufficiently reflecting the nonlinearity of maximum power demand and demand response because it calculates based on the average of past power consumption data. Therefore, in this study, the structure of the VSM data set which generated BSEM and the TRNSYS-CREST simulation were analyzed, and the applicability of the demand response was evaluated through the verification of the LSTM, GRU, and CNN-LSTM models using the VSM data set. As the results , the LSTM and GRU models showed slightly higher error index than the CBL, while the CNN-LSTM structure effectively predicted short-term fluctuations through convolutional features combined with time dependency. This confirmed the possibility of more precise DR if the conventional CBL method and the AI prediction model were combined. In conclusion, this study confirmed the possibility of constructing a Korean VSM data set that reflects institutional factors such as BSEM-based energy prediction, TOU rate system, and DR, focusing on apartment complexes in Korea, and the possibility of follow-up research on simulation and empirical models based on RSM data.

http://doi.org/10.5207/JIEIE.2025.39.5.365

Hoon Jung ; Min Seok Seo ; Jong Chan Lee ; Joon Ho Ahn

Recently, Transformers, being critical components in power systems, require accurate condition monitoring to prevent failures. However, conventional diagnostic approaches often rely on periodic inspections or failure analyses, limiting real time responsiveness. This study proposes a regression based condition prediction model using an Autoregressive Neural Network (AR-Net), which effectively captures dynamic patterns in time-series data. The model utilizes composite sensor data specifically temperature and vibration collected under normal operation, enabling non-intrusive diagnostics. Compared to traditional regression and RNN models, AR-Net offers improved adaptability to shifting operational trends. Experimental results show excellent prediction accuracy, with Mean Absolute Percentage Error (MAPE) of 0.93% for temperature and 5.09% for vibration each. These results show the feasibility of applying AR-Net for real time transformer condition prediction and support its integration into intelligent predictive maintenance systems.

http://doi.org/10.5207/JIEIE.2025.39.5.371

Seok-Gu Kang

Recently, electrical equipment in detached houses include various power conversion devices such as LED lighting, HVAC systems, electric vehicle chargers, and photovoltaic (PV) systems. This study systematically analyzed the harmonic characteristics of major electrical appliances used in detached houses and verified the effectiveness of filter application for harmonic mitigation based on measurement data at the main circuit breaker. The results of individual measurements of major appliances showed that the voltage total harmonic distortion () satisfied the IEEE 519 standard (≤8%). However, the current total harmonic distortion () and current total demand distortion () exhibited relatively high values in appliances such as refrigerators and HVAC systems, and the measured at the main circuit breaker ranged from 23% to 29%, exceeding the IEEE standard limit of 15%. To resolve this issue, the passive low-pass Bessel filters were designed and fabricated. Measurement results indicated that was reduced by approximately 12%?16%, and was reduced by up to 47%. In particular, during periods without PV generation, the decreased to below 15%, satisfying the standard, and power factor improvement was also confirmed. This study empirically identified harmonic problems occurring in detached houses and demonstrated that cost-effective passive filters can serve as an effective solution.

http://doi.org/10.5207/JIEIE.2025.39.5.382

Tae-Wan Kim ; Keon-Hee Park ; Mun-Seop Lim ; Jang-Seob Lim

This paper studied the rectangular method for classifying faults in power transformers based on dissolved gas analysis(DGA) data collected from Korea. Conventional international approaches, such as the Duval triangle and pentagon, have shown limited accuracy for Korean transformers due to environmental and operational differences. To address this issue, the proposed model normalizes the concentrations of four key gases and determines a representative location using the centroid of a constructed quadrilateral. Two model variations were evaluated against detailed inspection results, with the C₂H2;-based model reducing overlapping classifications by 11% and improving diagnostic reliability. Compared to traditional methods, the proposed approach demonstrates better alignment with inspection outcomes and offers enhanced applicability for transformer diagnostics in Korea. This method contributes to more accurate condition monitoring and asset management in power systems.

http://doi.org/10.5207/JIEIE.2025.39.5.389

Nam-Hoon Jo

In this paper, we study the design of a reduced-order disturbance observer (DOB) controller for robust stabilization of systems with model uncertainties. In previous research, the high-frequency gain of the nominal model had to be carefully selected so that system stability is guaranteed. However, in this study, we propose a new Q-filter and show that, by employing it, the system can be stabilized even when an arbitrary high-frequency gain is used. The autonomy of such a design can be effectively utilized to enhance control performance, such as disturbance attenuation. From the simulation study, we verified an enhancement in disturbance-rejection performance: MAPE decreased from 4.44% (conventional controller) to 1.68% (proposed controller).