https://doi.org/10.5370/KIEE.2026.75.2.247

조건익(Kun-Yik Jo) ; 박현호(Hyun-Ho Park) ; 윤상윤(Sang-Yun Yun)

This study presents a reliability-based investment planning method for distribution networks considering both load and distributed generation (DG). A new reliability index is proposed to quantify the impacts of power interruptions on load consumption and DG output. The normalized sub-indices are integrated into a comprehensive reliability measure. In addition, a mixed-integer linear programming based service restoration model is formulated to estimate outage durations under realistic operating conditions, explicitly considering network constraints as well as the different operating times of remote-controlled and manual-controlled switches during fault restoration. Sensitivity analysis of the proposed index assesses the reliability improvement achieved by sectionalizing switch investments, leading to a priority-based investment procedure. The proposed index and planning framework are tested on a model of distribution system of KEPCO. The simulation results demonstrate the difference in reliability before and after DG integration and validate the effectiveness of the proposed method.

https://doi.org/10.5370/KIEE.2026.75.2.258

서동혁(Dong-Hyeok Seo) ; 위영민(Young-Min Wi)

This paper studies the optimization of training strategies for a Bi-LSTM (Bidirectional Long Short-Term Memory) model to improve real-time electricity demand forecasting accuracy. Unlike most existing research that emphasizes hyperparameter tuning, this work examines three key training strategy variables essential in practice: training period, window size, and retraining frequency. Using four years of South Korea’s power demand and weather data, a sequential search identifies the optimal configuration. Results show that a 24-month training period, a 7-day window, and a 3-day retraining cycle achieve the most accurate and stable forecasts, with an average MAPE of 0.84%. The study also assesses the trade-off between accuracy and computational cost, confirming the practicality of the proposed strategy and underscoring that training strategy optimization is as critical as model architecture tuning."

https://doi.org/10.5370/KIEE.2026.75.2.266

현동호(Dong-Ho Hyun) ; 반재필(Jaepil Ban)

The expanding adoption of distributed photovoltaic (PV) generators introduces uncertainties into power system operation. In particular, as distribution system operators often observe only substation net load, it can be a challenging issue to obtain the gross load by separating the unobserved behind-the-meter (BTM) PV from the net load. This paper proposes a hybrid DLinear?BiLSTM, model to estimate the gross load when BTM PV measurements are unavailable. The proposed model uses a DLinear-based decomposition to split the time series input data into trend and seasonal components. Then, a bidirectional LSTM jointly learns nonlinear correlations and long- and short-term dependencies. In particular, because it uses only accessible exogenous variables such as public meteorological data (solar irradiance, temperature, precipitation/snowfall), calendar factors, and a region identifier, the method is easy to implement and scale without detailed facility-level data. The proposed model is validated by the experiment using one-year dataset obtained from a substation.

https://doi.org/10.5370/KIEE.2026.75.2.276

송은채(Eunchae Song) ; 허진(Jin Hur)

Accurate power curve modeling is essential for reliable grid integration, but operational data often contain outliers caused by curtailment, turbine faults, and sensor errors. These outliers distort the wind speed?power relationship and reduce prediction accuracy. To address this, we propose an Adaptive DBSCAN outlier removal method designed to handle non-uniform data density. The approach first applies Zonal DBSCAN, which divides the data into wind speed segments using 3-quantiles and optimizes clustering parameters within each segment to detect outliers more effectively. A follow-up IQR refinement removes remaining extreme points. Using data from two wind farms, the method showed strong robustness across different conditions. When applied to polynomial regression, SVR, and spline interpolation, the cleaned data consistently improved model accuracy. Incorporating weather forecast data further demonstrated its usefulness for power generation forecasting and electricity market bidding. The proposed method provides a simple and practical preprocessing tool that enhances both operational decisions and economic performance for wind farm operators.

https://doi.org/10.5370/KIEE.2026.75.2.286

정윤수(Yun-Su Jeong) ; 백건(Keon Baek)

In response to the global climate crisis, South Korea is pursuing reductions in coal-fired power generation and expansion of renewable energy to achieve its 2050 carbon neutrality goal and Nationally Determined Contributions (NDC). This calls for a quantitative assessment of the long-term operational viability and timing of business transition for thermal power plants. This study proposes a method for assessing the long-term transmission capacity of thermal power plants located along the North-South Power Flow Corridor, which supplies renewable energy from the Honam region and the southwestern maritime region to the Seoul metropolitan area. The study explicitly incorporates renewable energy site selection and North-South transmission constraints into the analysis. The analysis reveals that the transmission capacity of the targeted coal-fired power plants decreases by approximately 30.63-47.31% during daytime hours, when renewable energy output is concentrated, while it increases by approximately 1.2% during early morning and late-night hours. Furthermore, the maximum daily and annual combined transmission capacity was derived, and the patterns suggest that the transmission capacity of coal-fired power plants can vary significantly depending on the timing of grid reinforcement and the pace of renewable energy expansion. These results provide quantitative basis and key parameters for developing investment strategies for the closure, conversion, or continued operation of coal-fired power plants.

https://doi.org/10.5370/KIEE.2026.75.2.294

김은우(Eun-Woo Kim) ; 신한솔(Han-Sol Shin) ; 오효빈(Hyo-Bin Oh) ; 윤형석(Hyeong-Seok Yun) ; 윤효정(Hyo-Jeong Yoon) ; 김욱(Wook Kim)

As High Voltage Direct Current (HVDC) transmission systems expand globally, accurate modeling for power system operation and electricity market analysis becomes critical. Current electricity markets, including MISO, employ Direct Current Optimal Power Flow (DC OPF) with HVDC modeled as a transportation model?a simplification that fails to capture HVDC's characteristics. This study evaluates the adequacy of current market modeling by comparing it with Hybrid OPF, which explicitly incorporates the electrical characteristics of Line Commutated Converter and Voltage Source Converter based HVDC systems. Using the Jeju power system interconnected via HVDC lines, single-period OPF simulations reveal substantial differences: HVDC power flows differ by up to 257MW with reversed flow directions in some cases, and whether and where transmission congestion occurs differs significantly. Under high-load scenarios, these modeling differences lead to altered generator commitment decisions, total generation costs varying by 1.03%, and distinct locational marginal price distributions. The findings demonstrate that transportation-model-based DC OPF may inadequately represent actual power flows in HVDC-interconnected systems, particularly under congested conditions. This study provides evidence on the practical validity and limitations of current market modeling practices, suggesting Hybrid OPF necessity for accurate system operation analysis and reliable market outcomes.

https://doi.org/10.5370/KIEE.2026.75.2.306

김수현(Su-Hyeon Kim) ; 최승수(Seung-Su Choi) ; 조영재(Young-Jae Cho) ; 임성훈(Sung-Hun Lim)

As renewable energy sources are increasingly integrated into power systems to mitigate the climate crisis, the adoption of smart inverters?key devices for enhancing the stability of distributed generators like photovoltaic (PV) systems?is being encouraged. Consequently, research on the impact of smart inverters on potential power system fluctuations is also growing. In this paper, a simulated distribution system was constructed to model load power variations and undervoltage conditions caused by single-line-to-ground faults. By configuring various Volt-VAR curves for the smart inverter, its effects on voltage recovery and line loss in the distribution system were analyzed. Our findings confirmed that a smaller slope in the Volt-VAR curve provided a more significant compensation effect for overall voltage drops in the distribution system. Also, setting an excessively large slope could lead to voltage oscillation due to reactive power output, thereby negatively impacting the entire system's stability. Two causes for oscillation phenomena in smart inverters were identified, stemming from their computation and control methods. Despite these inherent operational characteristics, experimental results further confirmed that mitigating these oscillations was achievable by adjusting the slope of the Volt-VAR curve to a gentler setting.

https://doi.org/10.5370/KIEE.2026.75.2.316

양준원(Jun-Won Yang) ; 정우성(Woo-Sung Jung) ; 김태성(Tae-Seong Kim) ; 장준호(Jun-Ho Jang) ; 김연수(Yeon-Su Kim) ; 한철(Cheol Han) ; 김용주(Yong-Joo Kim) ; 신경훈(Kyung-Hun Shin) ; 최장영(Jang-Young Choi)

In this paper, the noise and vibration characteristics of axial flux permanent magnet synchronous motors were compared and analyzed according to different pole-slot combinations using an electromagnetic-structural coupled analysis. Under load conditions, finite element analysis was performed to evaluate torque ripple and the axial electromagnetic force imbalance acting on the stator tooth surface for each configuration. Modal analysis was then conducted to identify the natural frequencies of the stator. The electromagnetic forces were applied to a coupled electromagnetic-structural simulation to analyze their effects on vibration and noise responses in the frequency domain. Finally, the NVH characteristics of each pole-slot combination were compared using noise levels and waterfall diagrams at various operating speeds.

https://doi.org/10.5370/KIEE.2026.75.2.324

최준이(Jun-I Choi) ; 김대훈(Dae-Hoon Kim) ; 임형민(Hyung-Min Im) ; 최원칠(Won-Chil Choi) ; 배원규(Won-Gyu Bae)

This study proposes a CNN (Convolutional Neural Network)-based fault diagnosis method for real-time detection of BLDC (Brushless DC) motor faults. A cost-effective experimental system using an STM32 microcontroller was constructed, and current data were collected under three conditions: normal operation, asymmetric load due to rotor imbalance, and foreign substance insertion in the bearing. The collected current signals were analyzed using FFT (Fast Fourier Transform), and a CNN model was employed to classify fault types, especially for cases where frequency-based analysis alone was insufficient, such as in the presence of foreign substances. The proposed model achieved an average classification accuracy of 91.8%, demonstrating particularly high performance in detecting normal and asymmetric conditions. These results suggest that the proposed method can contribute to improving the reliability and maintainability of BLDC motor systems in practical applications.

https://doi.org/10.5370/KIEE.2026.75.2.334

이상욱(Sang-Uk Lee) ; 문주형(Ju-Hyeong Moon) ; 강동우(Tae-Hyeong Kim) ; 김태형(Dong-Woo Kang)

This paper presents a quantitative investigation into the influence of rotor core lamination orientation on the electromagnetic performance of axial-flux motors (AFMs). Two rotor configurations?radially laminated and axially laminated?are designed with an identical stacking factor (0.95), material, and rotor-yoke thickness to ensure a fair comparison. The impact of lamination orientation is examined in terms of flux-distribution patterns, rotor-core eddy-current losses, and output characteristics, thereby providing a direct assessment of its role in key loss mechanisms and performance metrics relevant to AFM rotor manufacturing. Transient finite-element simulations are conducted using ANSYS Electronics Desktop 2024 R2. The results offer design guidelines for AFM rotor cores that explicitly account for lamination-orientation?dependent electromagnetic behavior while balancing manufacturability and performance.

https://doi.org/10.5370/KIEE.2026.75.2.340

한지훈(Ji-Hoon Han) ; 박종훈(Jong-Hoon Park) ; 홍선기(Sun-Ki Hong)

The geometry variation of the semi-hard magnetic material in the rotor of a hysteresis motor does not affect the magnetization pattern itself; however, it influences the poles of the hysteresis ring. In this paper, the magnetization pattern caused by the geometric variation of the rotor ring in a hysteresis motor is formulated, and the corresponding torque ripple and output characteristics are analyzed. Moreover, the number of notches in the rotor is determined analytically based on the developed formulation. The developed analytical model is expected to be effectively utilized for torque ripple reduction design in hysteresis motors.

https://doi.org/10.5370/KIEE.2026.75.2.346

권민관(Min-Gwan Gwon) ; 이기창(Ki-Chang Lee) ; 김영호(Young-Ho Kim) ; 정연호(Yeon-Ho Jeong) ; 김지원(Ji-Won Kim) ; 황돈하(Don-Ha Hwang) ; 김장목(Jang-Mok Kim)

This paper proposes the design and control strategy of a DC-DC converters for fuel cell hybrid power system(FCHPS), intended for application in a 1.8 MW-class, 19-seat short take-off and landing (STOL) commuter aircraft. To facilitate development and validation, the total power system is scaled down to 10 kW, comprising four 2.5 kW-class fuel cell modules and two 5 kW-class DC-DC converters. The proposed fuel cell hybrid power system is configured to simultaneously support inverter power supply and battery charging using power generated from hydrogen fuel cells. Each converter receives input from two fuel cell power stack modules and distributes its output through two separate channels: one for inverter operation and the other for battery charging. To implement this functionality, a hydrogen fuel cell DC-DC converter was designed using four buck converter circuits arranged into two sets, enabling two distinct output modes. A voltage control algorithm incorporating a dual-loop current controller for current balancing, along with a power distribution algorithm for mode switching, is introduced to drive the converter effectively. The performance of the proposed converter was validated through MATLAB/Simulink-based simulations and experiments using an actual hydrogen fuel cell system, confirming its applicability to hybrid power systems for aviation use.

https://doi.org/10.5370/KIEE.2026.75.2.356

신효준(Hyo-Jun Shin) ; 정민우(Min-Woo Jeong) ; 김형준(Hyeong-Jun Kim) ; 김용희(Yong-Hee Kim) ; 김채원(Chae-Won Kim) ; 이세희(Se-Hee Lee)

In power systems, cable arrangements strongly influence electrical, thermal, and spatial performance. Underground cables are typically installed in trefoil or flat configurations, with cleats placed at intervals to ensure stability under fault-induced electromagnetic forces. However, these arrangements may produce induced voltages and induced currents in the sheath, reducing reliability. Floating conductors, such as ungrounded cleats, can further enhance electromagnetic coupling and generate additional induced voltages. This study uses Finite Element Method (FEM) simulations on a cross-bonded trefoil cable model to analyze these effects. Results show that induced voltages arise from the combined action of electric and magnetic fields and are strongly affected by cleat conductivity. The findings indicate that induced voltages on floating conductors may accelerate insulation degradation and increase safety hazards, highlighting the need for proper cleat design and bonding practices.

https://doi.org/10.5370/KIEE.2026.75.2.362

서예슬(Ye-Seul Seo) ; 김가현(Ga-Hyun Kim) ; 박건희(Keon-Hee Park) ; 임문섭(Mun-Seop Lim) ; 최현준(Hyen-Jun Choi) ; 임장섭(Jang-Seob Lim)

This study evaluated the electrical and mechanical properties of wet design submarine cable insulation materials to improve long term reliability in offshore wind applications. XLPE, TR XLPE A, and TR XLPE B were evaluated through volume resistivity and AC dielectric breakdown measurements using 0.2mm thin specimens and accelerated aging specimens produced under ASTM D6097. TR XLPE B showed about 5.9 times higher volume resistivity than XLPE, and both TR XLPE types exhibited roughly a 2% increase in AC dielectric breakdown, with accelerated aging specimens showing an additional 5.4% improvement. Mechanical tests confirmed that XLPE had the highest tensile strength and elongation. These results provide baseline criteria for evaluating insulation degradation under frequency accelerated aging and serve as important evaluation guidelines when manufacturing factory joints, ultimately contributing to the long-term reliability of submarine power cables.

https://doi.org/10.5370/KIEE.2026.75.2.369

에르셀릭 우우르(Ugur Ercelik) ; 김거식(Keo Sik Kim) ; 박형준(Hyoung-Jun Park) ; 김경백(Kyungbaek Kim)

In transformer power equipment, major welding defects often cause oil leakage due to flaws such as porosity, spatter, undercuts, and overlaps, as well as cracks and leakage resulting from frequent electromagnetic vibrations. These issues typically arise from reduced weld quality, component fatigue, thermal overload, and long-term operational conditions, ultimately leading to shorter equipment lifespan and serious safety risks. To address these challenges, in this paper, we propose an improved YOLOv8 model with a Convolutional Block Attention Module(CBAM) to detect and resolve multiple types of small defects on weld beads. The CBAM module is integrated into the neck part of the YOLOv8 network to enhance target features from both channel and spatial dimensions. The proposed YOLOv8-CBAM model demonstrated the most balanced performance across all metrics, reaching the highest precision (75.2%) and recall (77.6%). Although its mAP@50 (81.0%) was slightly lower than YOLOv5, it still outperformed YOLOv10 and YOLOv11, and its competitive mAP@50-95 (49.0%) confirmed its robustness in detecting defects of varying sizes.

https://doi.org/10.5370/KIEE.2026.75.2.376

윤민호(Min-Ho Yoon) ; 박찬묵(Chan-Muk Park) ; 조유정(Yu-Jung Cho) ; 임성훈(Sung-Hun Lim)

The risk of series arc faults presents a growing safety concern, as they are inherently undetectable by conventional overcurrent circuit breakers. This paper proposes a real-time series-arc detection technique based on principal component analysis(PCA). From current signals sampled at 100[kHz], we extract nine time-domain features once per 60[Hz] cycle (mean, variance, skewness, kurtosis, maximum, minimum, interquartile range, RMS, and peak-to-peak). These features are z-score standardized using parameters derived from a baseline of normal operational data and then projected onto the top three principal components. We define the Q-statistic (PCA residual variance) as the anomaly score and declare a series arc when it exceeds a predefined threshold for three consecutive cycles. Experiments show that incorporating RMS current variation enables reliable discrimination between series arcs and inrush currents demonstrating robust performance suitable for practical deployment.

https://doi.org/10.5370/KIEE.2026.75.2.383

조영만(Young-Maan Cho) ; 이재호(Jae-Ho Rhee) ; 이건아(Kun-A Lee)

The over-current is inflows to the power system due to various internal and external factors, which cause damage and malfunction of the installed device and lower the stability of the system, resulting in power loss. Therefore, in order to prevent these failures, the circuit breaker with appropriate specifications are installed in the system according to capacity. Among them, the Molded Case Circuit Breaker is the closest to the consumer and the largest quantity is installed in the distribution system. Pre-installation performance of the circuit breaker is verified by the product standards, but no consideration has been made for variations in the use environment. In this paper, a study is conducted on the performance change of MCCB due to repeated inflow of the over-current, and in particular, the effect on the energy consumption section according to the adsorption of hot-gas in the splitter plate is analyzed. As a result, it is experimentally confirmed that the energy consumption time and amount decreased as the hot-gas formed when the circuit breaker is operation by repeated over-current inflow is adsorbed to the splitter plate. Based on these results, it is expected to help develop maintenance, replacement timing and diagnostic methods according to the installation environment and operation frequency.

https://doi.org/10.5370/KIEE.2026.75.2.390

장주희(Ju-Hee Jang) ; 김종민(Chong-Min Kim) ; 오수정(Su-Jeong Oh) ; 강해권(Hae-Gweon Kang)

Nowadays, the installation of photovoltaic(PV) systems has increased. Also, there are many mountainous PV systems based on mountainous terrain. On March, there are large wildfires occurred in Korea, which could affect the PV systems. Therefore, the effect of fire of mountainous PV systems have to examine. In this paper, performance of PV module depending on wildfires is confirmed through the performance ratio(PR), Power Performance Index(PPI). Also, degradation of PV modules is measured using Infrared(IR) camera, I-V curve tracer and Electroluminescence(EL) devices. Through this study, decreased performance of PV systems due to wildfires is confirmed. Also, Hot spots and chess pattern EL images of PV strings depending on degradation are confirmed. However, degradation of PV modules is difficult to confirm using I-V curve tracer or performance factors. Therefore, the degradation due to wildfires should have to anlayze using EL devices and performance is monitored continuously for safety of PV systems.

https://doi.org/10.5370/KIEE.2026.75.2.397

홍태윤(Tae-Yun Hong) ; 권두경(Du-Kyeong Kwon) ; 윤영우(Young-Woo Youn) ; 선종호(Jong-Ho Sun) ; 김진규(Jin-Gyu Kim)

This paper proposes an acoustic emission-based anomaly detection and statistical analysis method to detect partial discharges caused by insulation degradation inside cast resin transformers. While high-frequency current transformers and ultra-high frequency sensors offer high accuracy, they are expensive and require complex signal interpretation. In contrast, acoustic emission sensors can measure elastic waves generated within the insulation at a relatively low cost. By applying artificial intelligence techniques, data-driven anomaly detection can be achieved without complicated analysis procedures. In this study, an acoustic emission sensor was attached to the outer enclosure of a 22.9 kV cast resin transformer to acquire signals under both normal and faulty conditions. The Hilbert transform was applied to enhance impulsive characteristics, and a one-dimensional convolutional long short-term memory autoencoder model was developed for anomaly detection. Using a threshold based on the interquartile range, normal and fault signals were classified with 100% accuracy in the laboratory environment. The proposed method provides an efficient data-driven analytical framework for diagnosing insulation degradation and offers potential applications in condition monitoring and predictive maintenance of cast resin transformers.

https://doi.org/10.5370/KIEE.2026.75.2.403

김주욱(Joouk Kim) ; 곽민호(Minho Kwak) ; 임지원(Jiwon Lee) ; 박영(Young Park)

This paper proposes an axle driven self generation system with an Energy Storage System (ESS) to supply power to refrigerated containers on freight trains. Instead of sizing the generator and ESS from a conservative worst case peak load, a probabilistic design based on a Long Short-Term Memory (LSTM) quantile model is adopted. The model predicts short term reefer load profiles and provides design values at selected quantiles, in particular the 95th percentile (P95). Using these results, capacity trends for peak load, generator rating and ESS energy are derived as functions of the consist size. For 20 and 33 car trains, the P95 based design reduces the required generator rating by about 30 percent compared with a deterministic peak load design, while the ESS covers occasional demand spikes and short stops without external power. The proposed approach therefore avoids excessive overdesign, yet maintains a specified reliability level for reefer power supply in long freight consists.

https://doi.org/10.5370/KIEE.2026.75.2.408

노수영(Soo-Young Noh) ; 김창현(Chang-Hyun Kim)

This study addresses the performance degradation of Brushless direct current motors caused by parameter drift and sensor noise. Conventional proportional-integral-derivative controllers struggle with these issues, as they amplify noise and cannot adapt to system changes. We propose a state-space proportional-integral-derivative controller with an online tuning framework that uses a deep deterministic policy gradient reinforcement learning agent. This approach avoids noise amplification by using observer-based state estimation instead of a direct derivative path, while the reinforcement learning agent adapts to parameter drift in real-time. Simulations confirm our method provides superior speed-tracking and reduced error compared to conventional methods, ensuring robust, long-term performance even under degraded conditions.

https://doi.org/10.5370/KIEE.2026.75.2.417

임준수(Joonsu Im) ; 김진성(Jin Sung Kim) ; 김청훈(Chunghun Kim)

This paper presents a multi-objective model predictive control (MPC) strategy for a grid-connected battery energy storage system (BESS) that simultaneously accounts for voltage regulation, battery degradation, and price-based arbitrage in a weak low-voltage distribution feeder. The controller leverages a linear voltage?power sensitivity model and a physics-based battery aging model to predict system behavior and optimize BESS dispatch over a receding horizon. The proposed MPC framework is implemented and validated through a CYME Python co-simulation platform, where a Python-based MPC optimizer interacts with CYME’s detailed load-flow engine at each simulation step. Case studies on a 380-V radial feeder demonstrate that the BESS operating pattern is highly sensitive to the weighting of voltage, degradation, and price objectives. When PV and load forecasts are incorporated, the MPC adopts a more conservative and smoother power schedule that mitigates rapid voltage excursions and tends to reduce cumulative battery degradation, while slightly lowering energy-arbitrage revenue compared with a persistence-based MPC. These results highlight the importance of forecast-informed control in balancing grid-support performance, battery lifetime, and economic profitability. The proposed framework provides a practical and deployable solution for operating BESS units in PV-rich weak distribution networks.

https://doi.org/10.5370/KIEE.2026.75.2.426

임준수(Joonsu Im) ; 김청훈(Chunghun Kim) ; 김진성(Jin Sung Kim)

This paper presents a constrained optimal time-varying sliding mode control strategy based on a receding horizon approach. While traditional sliding mode control provides robust performance in the presence of uncertainties, it lacks a systematic mechanism for explicitly handling constraints. To overcome these challenges, the proposed method formulates the design of the time-varying sliding surface as a constrained optimization problem. The proposed method casts the problem as a quadratic programming formulation within a model predictive control framework. Consequently, the controller can explicitly handle hard constraints. The effectiveness of the proposed algorithm is validated through MATLAB/Simulink simulations applied to a vehicle longitudinal control system. A comparative study using the linear time-varying method demonstrates that the proposed technique achieves optimal time-varying sliding while strictly satisfying all imposed constraints.

https://doi.org/10.5370/KIEE.2026.75.2.433

박대현(Dae-Hyun Park) ; 박혜연(Hae-Yeon Park) ; 최성산(Sung-San Choi) ; 이영호(Young-Ho Lee) ; 박성원(Sung-Won Park)

This study evaluates the economic feasibility of integrating an energy storage system (ESS) into a self-consumption photovoltaic (PV)-based on-site power purchase agreement (PPA) model for RE100 consumers. To this end, the optimal ESS capacity was derived under a 1:1 PPA structure, using actual electricity rate structures, contract demand, and historical electricity consumption data from a real consumer. A case study was conducted for an RE100 consumer with an annual electricity consumption of approximately 383 GWh. The results showed that economic can be achieved even with a fixed contract price of 200 KRW/kWh, based on the 2025 energy charge structure. In addition, the integration of ESS was found to be economically infeasible due to high initial investment and O&M costs. However, participation in multiple demand response programs showed that economic feasibility can be achieved, with a maximum net profit of 9.8 billion KRW and a benefit?cost ratio of 1,812, over the life of the battery.