https://doi.org/10.5370/KIEE.2025.74.9.1433

우현(Hyeon Woo) ; 박성준(SeongJun Park) ; 최승연(Sungyun Choi)

The global transition to renewable energy has accelerated the adoption of offshore wind power. To ensure the stable transmission of large-scale offshore wind energy, hybrid AC/DC transmission expansion planning is essential. This paper proposes a hybrid AC/DC transmission expansion strategy to enhance the hosting and transmission capacity of offshore wind farms. This methodology accounts for the characteristics of embedded HVDC systems and considers both AC and DC contingencies. For DC grids, an optimal operating range determination methodology for multi-terminal DC (MTDC) systems is proposed from an operational planning perspective to improve transient stability. For AC grids, a FACTS placement methodology is introduced from a facility planning perspective to enhance AC line flow limits, conducting FV analysis. The proposed hybrid AC/DC transmission expansion framework is validated on the Korean power system, demonstrating its effectiveness in enhancing grid stability and capacity.

https://doi.org/10.5370/KIEE.2025.74.9.1440

김선혁(Seonhyeog Kim) ; 이일우(Il-woo LEE) ; 허태욱(Taewook Heo)

This paper proposes a method for load prediction and analysis in a factory energy management system (FEMS). Since the electricity demand of a factory is largely dependent on the type of products produced, the temperature and humidity inside the factory, seasonality, and the state of the process, the variability of the process data and the deviation of the electricity demand appear significantly, so a load prediction method that considers the manufacturing execution system (MES) that reflects and manages the characteristics of the process is necessary. In addition, since the process data includes process control charts and abnormal data outside the normal range, it is expected to improve the performance of the learning model by applying control chart analysis techniques to remove data that hinder the performance of load prediction. Understanding each process, utility, and equipment within the factory is also essential for effective energy analysis. The Shewhart individuals control chart can be utilized to eliminate anomalous data, thereby improving the performance of the training data-set. The successful implementation and operation of FEMS require data synchronization, missing value treatment, and periodicity analysis in the data refinement process. Additionally, an AI-based load forecasting model allows for more precise energy demand predictions, enabling factory operators to derive optimal energy-saving strategies. This study makes the following contributions: (1) it proposes a data preprocessing framework tailored to different industrial sectors such as biotechnology and paper manufacturing; (2) it integrates MES-based production schedules into load forecasting to reflect real-world operational variability; and (3) it demonstrates the practical applicability of LSTM-based prediction models with validated performance in actual factory datasets. This approach significantly contributes to reducing power consumption and enhancing energy efficiency in South Korea's industrial sector.

https://doi.org/10.5370/KIEE.2025.74.9.1451

이성전(Seong-Jeon Lee) ; 곽주식(Joosik Kwak) ; 이규섭(Gyu-Sub Lee)

With the growth of renewable energy sources (RES) and energy storage systems (ESS), the number of distributed generators (DGs) integrated into power systems via voltage source converters (VSCs) has been increasing. VSCs are operated either in grid-following (GFL) or grid-forming (GFM) control modes. While the GFM mode offers the advantage of not requiring a phase-locked loop (PLL) for grid synchronization, it exhibits a stability issue when the grid impedance decreases. To analyze the stability concerns of GFM inverters, a PSCAD simulation-based study was conducted considering the short-circuit ratio (SCR) and the grid impedance X/R ratio (the ratio of inductive to resistive impedance). The results demonstrate that GFM inverters become more unstable as the SCR increases and the X/R ratio decreases.

https://doi.org/10.5370/KIEE.2025.74.9.1457

김인수(Insu Kim)

The Finite Element Method (FEM) is a numerical analysis method for solving complicated problems with different geometric domains by varying the boundary conditions and dividing the domain into smaller ones. The objective of this study is to solve such a problem of current, voltage, active power and reactive power distribution on the lines using the FEM. For this purpose, this study derives the second-order differential governing equations in a transmission line. To validate the proposed methods, this study models radial systems in MATLAB and combines the Newton-Raphson method to find the boundary conditions. As a result, the proposed method can detect the increase of overvoltage and undervoltage in the transmission line connected by the constant heavy loads. This study showed that the Newton-Raphson method can be error-prone when the length of the transmission line increases significantly.

https://doi.org/10.5370/KIEE.2025.74.9.1466

조세빈(Sebin Cho) ; 허진(Jin Hur)

This study develops a simulation framework for quantitative assessment of power system stability and cascading failure risks under extreme temperature events. Extreme temperature scenarios are generated using Generalized Pareto Distribution (GPD) from meteorological observations, incorporating temperature-dependent load increases, power factor deterioration, and dynamic line rating reductions. The framework integrates equipment outage models based on overload rates and reactive power exceedance with undervoltage load shedding and generator redispatch to identify vulnerable components and quantify regional outage probabilities. Monte Carlo-based probabilistic assessment identifies critical transmission components and vulnerable equipment, providing quantitative risk evaluation for climate-resilient power system planning. This methodology enables practical analytical tools for developing climate adaptation strategies in power systems facing escalating extreme weather events.

https://doi.org/10.5370/KIEE.2025.74.9.1476

이호준(Ho-Jun Lee) ; 유석진(Seok-Jin Yoo) ; 김병호(Byoung-Ho Kim) ; 김홍래(Hongrae Kim)

PMUs(Phasor Measurement Units) provide observers with high-speed synchronized data, enabling real-time monitoring of power system dynamics. However, due to high installation costs, PMUs are typically installed only at key substations, limiting the practical applicability of traditional DSE(Dynamic State Estimation) methods that assume full PMU deployment. This study proposes a realistic and efficient technique for real-time DSE using a limited number of PMUs. System observability is ensured through graph-theoretic optimal PMU placement, and voltage phasors are reconstructed via LSE(Linear State Estimation). Generator rotor angles and speeds are then estimated using the CKF(Cubature Kalman Filter). The proposed method is validated on WSCC(Western Systems Coordinating Council) 9-bus and IEEE(Institute of Electrical and Electronics Engineers) 39-bus systems, showing accurate and stable performance even under disturbances such as generator and line outages. It also outperforms the UKF(Unscented Kalman Filter) in computational efficiency and numerical stability, making it suitable for practical deployment.

https://doi.org/10.5370/KIEE.2025.74.9.1483

심상우(Sangwoo Shim) ; 지용우(Yongwoo Jee) ; 김동현(Dong-Hyun Tony Kim) ; 유재근(Jaegeun Yu) ; 박차리(Cha-Ri Park) ; 김용식(Yong-Sik Kim) ; 정아영(Ah-Young Jeong) ; 김진호(Jinho Kim) ; 박종배(Jong-Bae Park)

The Duck Curve phenomenon caused by the volatility of renewable energy hinders the flexibility of grid operation and causes rapid output adjustments of generators. According to the 11th Basic Plan for Electricity Supply and Demand, the proportion of renewable energy is expected to continuously increase, and countermeasures are required. This paper examined the possibility of alleviating the Duck Curve through demand response based on the Time of Use rate system. The demand response potential in Gangwon and Jeonnam regions was applied to PLEXOS simulation to perform a benefit analysis. At this time, there were four load shift scenarios by demand response. Through simulation of each scenario, the benefits were calculated and compared from the perspectives of the country and power companies. This paper performed simulations for 2024 and 2030 and confirmed that load shifting through demand response is an effective means to secure economical grid flexibility without separate ESS investment.

https://doi.org/10.5370/KIEE.2025.74.9.1492

박용성(Young-Sung Park) ; 안선주(Seon-Ju Ahn)

Metering error is the major cause of non-technical loss in the power grid. To reduce metering error, utilities must effectively identify its cause, particularly among high-voltage customers. To this end, KEPCO has been conducting on-site inspections known as the Hot-line MOF Error Test. However, this Test presented several challenges, including worker safety risk, long inspection time, and lower accuracy under certain load conditions. To overcome these limitations, this study proposes an algorithm that analyzes the data from AMI(Advanced Metering Infrastructure), to help a utility shortlist the customers whose equipment are likely to be faulty. By doing so, a utility will be able to allocate its resources more efficiently, making the overall process of detecting metering error more efficiently. To validate the proposed algorithm, on-site inspections were conducted, and results therefrom were studied to determine the effectiveness of the proposed algorithm.

https://doi.org/10.5370/KIEE.2025.74.9.1500

최영재(Yung-Jae Choi) ; 김철환(Chul-Hwan Kim)

In modern military operations, securing a stable and high-quality power supply is critical, particularly in air force airbases where autonomous power operation is essential under wartime conditions. The Republic of Korea Air Force has introduced a microgrid system incorporating intelligent switches, and mobile emergency generators (MEGs). These trailer-mounted MEGs are deployed flexibly according to operational demand. However, there remains a lack of research on systematically determining their optimal placement from a power system perspective. This study proposes an optimization methodology for the placement of MEGs in airbase microgrids, aiming to minimize power loss and improve voltage stability. Genetic algorithm(GA) is employed to determine the optimal generator positions. The simulation is conducted on a virtual airbase model reflecting realistic load profiles and distribution feeder configurations. The proposed method is expected to serve as a strategic decision-making tool for emergency generator deployment during wartime and can be extended to future microgrid planning for military bases.

https://doi.org/10.5370/KIEE.2025.74.9.1506

정재환(Jaehwan Jung) ; 김형우(Hyung-Woo Kim) ; 황영호(Young-Ho Hwang) ; 남택효(Taek-Hyo Nam) ; 정상용(Sang-Yong Jung)

This study analyzes the electomagnetic performances of a yokeless and segmented armature-type axial flux motor under no-load conditions, incorporating a Halbach magnet array and various skew structures. Halbach magnet array and skew structures exhibit trade-offs among cogging torque, total harmonic distortion of back-electromotive force, and average torque, necessitating an evaluation of their combined effects on design parameters. Finite element analysis was employed to investigate the no-load electromagnetic performance with respect to two key design parameters. The results confirm that different skew structures have distinct impacts on electromagnetic performances according to the key parameters.

https://doi.org/10.5370/KIEE.2025.74.9.1513

오승환(Seung-Hwan Oh) ; 이경호(Kyung-Ho Lee) ; 임동국(Dong-Kuk Lim)

This paper propose a robust design method that accounts for performance variation caused by manufacturing tolerances in the optimal design process of electric motors. To achieve this, a surrogate model based on machine learning is employed in conjunction with a genetic algorithm. During the optimization process, the electromagnetic performance of the motor is evaluated through finite element analysis, and the results are used to construct a surrogate model for robustness evaluation. The surrogate model is continuously updated as data accumulate throughout the genetic algorithm iterations, thereby enhancing the reliability of the robustness assessment. The proposed method is validated using both benchmark test functions and an actual motor application.

https://doi.org/10.5370/KIEE.2025.74.9.1521

박주홍(Joo-Hong Park) ; 노수진(Sujin Noh) ; 조한욱(Han-Wook Cho)

This paper proposes the application of a sliding mode controller (SMC), known for its robustness to nonlinearity, uncertainty, and external disturbances, to an axial magnetic bearing system that requires continuous support under high axial loads. Force and current coefficients are derived from magnetic circuit analysis and incorporated into the control parameters. The control input is designed based on Lyapunov stability theory. In addition, a full-state observer is developed to estimate the rotor speed, the derivative of displacement, and disturbances. Simulations and experiments conducted in MATLAB/Simulink verify that the proposed SMC provides excellent disturbance rejection and robustness.

https://doi.org/10.5370/KIEE.2025.74.9.1528

전진택(Jin-Taek Jeon) ; 최성문(Sung-Moon Choi) ; 유현상(Hyun-Sang You) ; 노성은(Seong-Eun Rho) ; 이중선(Joong-Seon Lee) ; 노대석(Dae-Seok Rho)

Recently, renewable energy sources have been continuously installed by the 2050 Carbon Neutral and the Green New Deal policy in Korea, and the capacity of PV systems has been rapidly increased due to low costs and short construction periods. However, it is reported that the output of PV systems varies significantly depending on the weather and surrounding conditions and the operation efficiency is reduced because of the shading in some PV modules. Therefore, this paper presents an operation algorithm of energy harvesting device for PV modules to improve operation efficiency by preventing the shutdown of grid-connected inverter due to the partial shading in the PV string. In addition, this paper performs a modeling of energy harvesting device, which is composed of circuit reconfiguration device section, voltage compensation device section, monitoring and control device section, etc, using PSCAD/EMTDC, and also implements 20[kW] energy harvesting device based on the modeling. From the simulation and test results for the proposed energy harvesting device, it is confirmed that the device can prevent the shutdown of grid-connected inverter by re-combining the PV string with the circuit reconfiguration and voltage compensation devices depending on the shading conditions. And also, it is found that the proposed energy harvesting device for PV modules is useful tool to improve the operation efficiency of PV system, because the operation characteristics of PSCAD/EMTDC modeling is nearly equivalent with one of the device.

https://doi.org/10.5370/KIEE.2025.74.9.1541

김예찬(Yechan Kim) ; 정민경(Minkyung Jeong) ; 구본혁(Bonhyuk Ku) ; 김재상(Jaesang Kim) ; 박훈양(Hoonyang Park) ; 강형구(Hyoungku Kangark)

This paper investigates international trends in asset management with a focus on life extension as a means to enhance operational efficiency and support carbon neutrality in the power sector. Global utilities are increasingly facing pressure to manage capital expenditures (CAPEX), operational expenditures (OPEX), and sustainability challenges. The UK’s RIIO (Revenue=Incentives+Innovation+Outputs) model incorporates CNAIM (Common Network Asset Indices Methodology) to promote risk-based interventions, while Japan’s OCCTO (Organization for Cross-regional Coordination of Transmission Operators) coordinates similar efforts across utilities. By analyzing how life extension strategies are integrated into national policies overseas, this study offers insights into a more sustainable and cost-effective path for Korean power utilities. The findings highlight the importance of data-driven asset decisions and phased life extension strategies in modern infrastructure management.

https://doi.org/10.5370/KIEE.2025.74.9.1549

김예찬(Yechan Kim) ; 정민경(Minkyung Jeong) ; 구본혁(Bonhyuk Ku) ; 김재상(Jaesang Kim) ; 박성희(Sunghee Park) ; 강형구(Hyoungku Kangark)

This study proposes a life extension strategy for GIS (Gas-Insulated Switchgear) in response to the growing economic and environmental pressures faced by the Korean power industry. Based on an analysis of ageing mechanisms and field condition assessments for components in GIS, each component was classified into three tiers: repairable, refurbishable, or requiring replacement. Additionally, Economic and environmental sustainability were quantitatively evaluated. Results show that extending the service life by ten years reduces depreciation costs by over 30%, while deferring CO₂ emissions by approximately 10.2 tons per GIS bay. The study also addresses limitations due to outdated specifications, suggesting practical solutions such as operational condition verification and overseas market expansion. Building upon insights from Part 1, this paper offers a technical framework that supports Korea’s carbon neutrality and capital efficiency goals through systematic of life extension.

https://doi.org/10.5370/KIEE.2025.74.9.1561

임토우(Towoo Lim) ; 김영민(Youngmin Kimark)

This paper presents a wireless sensor system that utilizes vibrational energy harvesting to monitor the structural integrity of bridges. Piezoelectric materials, combined with an optimized energy harvesting circuit, convert bridge vibrations into electrical energy, generating voltages of up to 7 V under low vibration conditions (< 0.2 g). Given the high internal resistance of piezoelectric materials, the harvesting circuit was optimized for the maximum voltage output. The system integrates a low-power three-axis accelerometer, a micro-controller and a 2.4 GHz RF transceiver, enabling autonomous energy harvesting and active operations. Under low vibration conditions, the system harvested 7 mJ energy over a 3-minute period that is sufficient to support multiple sensor measurements and wireless data transmissions. During an active mode of 200 ms, 100 bytes of sensed data were successfully transmitted, demonstrating the feasibility of a self-powered wireless sensor for monitoring a bridge structure.

https://doi.org/10.5370/KIEE.2025.74.9.1566

오귀운(Gwi-Un Oh) ; 홍창완(Chang-Wan Hong) ; 고종선(Jong-Sun Ko)

This paper presents a rotor speed estimation method for sensorless control of induction motors, based on a discrete-time flux observer. Although V/f control offers simplicity and ease of implementation, it is typically configured as an open-loop system, which limits its accuracy under varying load conditions. To address this issue, this study proposes a real-time rotor speed estimation approach by calculating slip using flux information, thereby laying the foundation for future extension to closed-loop control. The proposed method estimates the slip frequency from the observed stator flux, and consequently determines the rotor speed. The effectiveness of the proposed approach is validated through MATLAB/Simulink-based simulations under various load conditions and experimental results using a 5.5 kW M-G(Motor-Generator) set.

https://doi.org/10.5370/KIEE.2025.74.9.1575

김민규(Mingyu Kim) ; 김경수(Gyeongsu Kim) ; 서기성(Kisung Seo)

Image segmentation aims to classify each pixel into a specific category, separating object regions from the background, and is widely used in applications such as autonomous driving and medical imaging. Popular models include PSPNet and DeepLab V3, with many studies focusing on performance enhancement. Knowledge distillation (KD), where a student model learns from a teacher model’s output distribution, has been applied to reduce model size or improve performance. However, most KD methods rely on large, complex teacher models and are difficult to apply when the teacher and student architectures differ. Moreover, in segmentation tasks, KD is more challenging due to the lack of standardized methods and the need to consider task-specific characteristics. To address these issues, we propose applying two single-model-based KD methods to segmentation: Self-Knowledge Distillation (Self-KD), which enables distillation within a single model, and Mutual-Knowledge Distillation (Mutual-KD), where two identical models exchange knowledge. We integrate both methods into the PSPNet architecture and validate their effectiveness on the Pascal VOC 2012 dataset, achieving mIoU improvements of 0.56 percentage points with Self-KD and 1.06 percentage points with Mutual-KD compared to the baseline.

https://doi.org/10.5370/KIEE.2025.74.9.1581

김주명(Ju-Myung Kim) ; 김재혁(Jae-Hyeok Kim) ; 박소윤(So-Yun Park) ; 유진우(Jin-Woo Yoo)

While the Swin Transformer effectively reduces computational cost using window-based attention, it struggles to model global dependencies across windows. Prior work, such as the Refined Transformer, attempts to overcome this limitation by incorporating CBAM-style channel and spatial attention mechanisms. However, these sequential attention operations often introduce representational bias by overemphasizing specific features. To address this, we propose two key components: (1) the Efficient Head Self-Attention (EHSA) module, which dynamically calibrates the relative contribution of each attention head within a window, and (2) the Hierarchical Local-to-Global Spatial Attention (HLSA) module, which captures long-range interactions across windows in a hierarchical manner. By integrating these into a Swin-T backbone, our architecture improves both local detail modeling and global context aggregation. Experiments on ImageNet-1K and ImageNet100 demonstrate that our model surpasses the Refined Transformer and other window-based approaches in accuracy, while maintaining a comparable level of computational efficiency. These results validate the effectiveness of our design in enhancing local-global interactions within Vision Transformers.

https://doi.org/10.5370/KIEE.2025.74.9.1591

김민수(Min-Su Kim) ; 박수민(Su-Min Park) ; 조우성(Woo-Sung Cho) ; 박태근(Tae-Geun Park)

In this paper, a real-time optical flow system based on the Lucas-Kanade algorithm was designed. In order to improve hardware complexity and design efficiency, optimal bit allocation was performed through error rate analysis. Also real-time processing performance was achieved through parallel/pipeline structure and overlapping scheduling. By optimizing the memory cycle so that even and odd data can be read and written at the same time, data utilization was maximized. In the Lucas-Kanade algorithm, the output data of the pre-calculated intermediate kernel is frequently reused. So data were updated by applying optimal overlapping scheduling using minimal memory and the required amount of computation and memory space were reduced. The proposed architecture was designed and synthesized with a DB HiTek 110nm standard cell library with an error rate of 3.70% for Yosemite Sequence and a maximum operating frequency of 268MHz (264.6Mpixel/s), using 71.59K gates and 15.43KB of memory.

https://doi.org/10.5370/KIEE.2025.74.9.1599

신승권(Seung-Kwon Shin)

To secure fundamental data necessary for developing the Railway Station Energy Control Virtual Testbed (RS-ECVTB), this study conducted a systematic meta-analysis of AI·ML-based Heating, Ventilation, and Air Conditioning (HVAC) control effects in large public facilities. Railway stations face limitations with conventional control methods due to unique operational conditions such as 24-hour continuous operation and fluctuating passenger density, necessitating quantitative analysis of implementation effects of AI·ML-based intelligent control techniques. Following PRISMA guidelines, studies published from 2015 to 2024 were collected, and through rigorous selection processes, 267 studies were finally selected for meta-analysis from an initial 1,385 papers. Among these, 134 studies (50.2%) directly targeted railway stations, while the remainder consisted of research on large public facilities with similar characteristics. The meta-analysis revealed that AI·ML-based HVAC control techniques achieved an average energy reduction of 17.4% compared to conventional control methods (95% CI: 15.8-19.0%). Performance analysis by technique revealed that hybrid approaches (RL+MPC) demonstrated the best performance at 34.2%, followed by Model Predictive Control (MPC) at 28.3%, and Deep Reinforcement Learning (DRL) at 26.8%. Notably, above-ground stations demonstrated higher effectiveness than underground stations (24.8% vs 19.3%), and BEMS-integrated systems achieved 28.7% reduction, representing an 8.9 percentage point improvement over non-integrated systems. The average energy reduction of 17.4% and superior performance of hybrid approaches (34.2%) derived from this study can serve as reference data for setting performance targets and selecting algorithms when developing RS-ECVTB. Particularly, the additional 8.9%p effect from BEMS integration and the importance of high-resolution data should be reflected as core requirements in RS-ECVTB system design. The average payback period of 3.2 years from economic analysis provides investment feasibility evidence for responding to the mandatory ZEB certification policy for railway stations in 2025.

https://doi.org/10.5370/KIEE.2025.74.9.1605

양인준(In-Jun Yang) ; 신양진(Yangjin Shin) ; 이주(Ju Lee) ; 정동훈(Dong-Hoon Jung)

Permanent Magnet (PM) motors are widely used across various industries such as automotive, aerospace, home appliances, and defense, due to their wide operating range, high power density, and precise controllability. In particular, slotless motors, characterized by the absence of teeth and slots, offer various electromagnetic and structural advantages over slotted types and are commonly used in servo and drive motor applications that demand high precision control and low vibration. However, in slotless motor design, a rotor with high inertia can degrade acceleration and deceleration performance, potentially leading to reduced responsiveness in dynamic systems. Therefore, this paper presents a design approach for a BLDC slotless PM motor considering both electromagnetic characteristics and rotor inertia. An optimal design was performed using Response Surface Methodology (RSM) and three-dimensional Finite Element Analysis (3D FEA) to maximize the torque constant while minimizing rotor inertia. Additionally, effective design strategies based on magnetic and electric loading were proposed. Finally, the feasibility of the proposed design method and the output performance of the BLDC slotless PM motor were validated through experimental testing of a prototype.

https://doi.org/10.5370/KIEE.2025.74.9.1611

이동우(Dong-Woo Lee)

The transient performance of sensorless control for an interior permanent magnet synchronous motor (IPMSM) based on back-electromotive force (back-EMF) estimation is a critical factor in ensuring high drive system reliability. Although the rotor speed and position can be estimated accurately in steady-state conditions, estimation errors tend to increase during transients such as acceleration, deceleration, and load torque variations. Improving transient stability depends on reducing the overshoot in estimated position and speed errors. In this paper, the maximum overshoot of the estimated position and speed errors during transient states is analyzed, and compensation methods are proposed to reduce these overshoots. The effectiveness of the proposed sensorless control strategy is verified through experimental results.

https://doi.org/10.5370/KIEE.2025.74.9.1619

윤현재(Hyunjae Yoon) ; 공영민(Youngmin Gong) ; 임승진(Seungjin Lim) ; 김인수(Insu Kim)

The efforts of the South Korea government to establish electric vehicle (EV) charging stations have led to the construction of a significant number of EV infrastructure charging facilities. However, due to administrative shortcomings and insufficient research, this has resulted in a proliferation of charging stations without proper consideration for optimal locations. In response, this paper analyzes the factors influencing EV charging demand, focusing on Yeonsu-gu, Incheon, and argues for the necessity of relocating underutilized EV charging stations. Furthermore, an algorithm for the administrative procedures of dismantling EV charging stations is introduced to facilitate such relocation decisions. Additionally, detailed rules for the algorithm are developed, and an explanation of the process is provided to ensure greater precision in administrative procedures. Moreover, a regression model predicting EV charging demand is constructed to support the algorithm for dismantling administrative procedures in the context of EV charging station relocation decisions. It is hoped that this paper’s administrative procedure algorithm model will contribute to the efficient implementation of administrative efforts when discussions on the relocation of underutilized EV charging infrastructure facilities are actively pursued at the government level in the future.

https://doi.org/10.5370/KIEE.2025.74.9.1628

최원칠(Won-Chil Choi) ; 강일호(Il-Ho Kang) ; 배원규(Won-Gyu Bae)

This study presents a quantitative framework for analyzing test-bench, facility, and environmental variables from fuel-cell test-bench data. Of 200+ channels, 29 variables were grouped into controlled, pressure?temperature, and lab/external streams. After detecting load steps, anomalies, and skewed distributions via line plots and histograms, IQR-based outlier removal and standardization were applied. Dependency analysis using Pearson’s r, Spearman’s ρ, and Kendall’s τ revealed that stack voltage is a complex function of load, supply pressure, and coolant-outlet temperature, that control-system variables exhibit near-perfect rank agreement, and that environmental variations significantly affect pressure and flow stability. Overall, this methodology provides essential data for real-time anomaly detection and operational-logic optimization in fuel-cell evaluation equipment.

https://doi.org/10.5370/KIEE.2025.74.9.1636

강휘준(Huijune Kang) ; 장유나(Youna Jang) ; 안달(Dal Ahn)

With the rapid advancement of wireless communication technologies, the importance of RF and microwave systems has significantly increased. Among various components within these systems, the power divider plays a critical role in efficiently distributing and combining signals across transmission and reception paths. In high-power environments such as satellite communication, radar systems, broadcast transmitters, and military communication equipment, power dividers must not only handle high power levels but also maintain low insertion loss and excellent reflection characteristics. To meet these demanding requirements, various power divider structures have been developed, with the Gysel power divider emerging as a promising solution due to its high power-handling capability, superior isolation, and efficient thermal dissipation characteristics. By utilizing grounded resistors, the Gysel structure offers high circuit stability and thermal performance. However, in high-frequency applications, high-power resistors exhibit parasitic inductance and capacitance due to their physical structure, causing performance degradation. These parasitic elements must be considered to ensure accurate circuit operation. In this paper, the impact of parasitic components in high-power resistors on the performance of a Gysel power divider is analyzed. A compensation circuit is proposed to mitigate these effects and improve impedance matching. To verify the approach, a Gysel power divider operating at 400[MHz] is designed. The design achieves reflection loss and isolation loss below -20[dB] while maintaining equal in-phase output signals. Measurement results confirm that the compensation circuit effectively reduces the impact of parasitics, enhancing overall performance in high-power applications.