https://doi.org/10.5370/KIEE.2023.72.11.1329

김광원(Gwang Won Kim) ; 현승호(Seung Ho Hyun)

In this paper, we propose a model for load scheduling of industrial loads under time-of-use pricing schemes using linear programming. While industrial loads consume more electrical energy than residential or commercial loads, their characteristics and correlations are not as simple, leading to complex conditions that need to be considered compared to other types of loads. On the other hand, linear programming is a validated optimization method that guarantees global optimal solutions. However, applying it to load scheduling requires expressing all constraints of industrial loads as linear equations, which presents a challenge. In the proposed model, loads are categorized into fixed loads and demand response loads, allowing for the differentiation of interruptible loads among shiftable loads to account for load diversity. Control variables are set to enable the modeling of these loads, considering the potential sequential conditions and duplicate prohibition conditions among shiftable loads. By representing these conditions as linear equations of control variables, they can be incorporated into load scheduling using linear programming. Additionally, the model considers potential scenarios that may exist at the consumer site, such as the presence of solar power generation facilities or energy storage systems, the ability to sell excess power, and limitations on the available workforce for simultaneous operations. These factors are taken into account to provide a comprehensive reflection of possible situations. In this paper, the proposed model is implemented in MATLAB and applied to a sample problem consisting of 8 flexible loads and 2 interruptible loads. A case study is conducted, considering various situations, and the results are analyzed to confirm the effectiveness of the proposed model.

https://doi.org/10.5370/KIEE.2023.72.11.1340

이흥석(Heungseok Lee) ; 김종주(Jongju Kim) ; 박준호(June Ho Park) ; 정상화(Sang-Hwa Chung)

This paper proposes a deep learning based CNN(Convolutional Neural Network) model combining Saliency map for the transient stability assessment of power systems. The CNN model is learned using data obtained from PMU(Phasor Measurement Units) which are high-speed sampling devices to allowing us precisely grasp the dynamic characteristics of the power system. The use of Saliency map enables the visual representation of the most influential input features in the CNN model. The proposed model shows more accurate and rapid transient stability assessment of power systems. The performance of the proposed model is verified using simulation data obtained from the IEEE 39 bus system through MATLAB/Simulink.

https://doi.org/10.5370/KIEE.2023.72.11.1351

구본길(Koo Bon-gil) ; 문희성(Heesung Moon) ; 남수철(Suchul Nam) ; 서재완(Jaewan Suh)

This paper proposes a method to quantify ramp rate flexibility in power systems by estimating the density function of ramp rates using kernel density estimation (KDE). This method permits direct, percentage-based quantification of ramp rate flexibility and provides an intuitive comprehension of the grid's current flexibility. Using the proposed method, the ramp rate flexibility of the Korean power system in 2030 was compared to that of the Korean power system in 2020, and the impact of securing additional flexible resources on ramp rate flexibility was analyzed. The results of the analysis showed that in 2030, when the proportion of renewable energy increases, it will be necessary to secure the ramp rate with additional flexible resources, the value of which can differ depending on the power system condition and time.

https://doi.org/10.5370/KIEE.2023.72.11.1358

손영건(Yeong-Geon Son) ; 김성열(Sung-Yul Kim)

In this paper, the need for an enhanced Economic Dispatch (ED) model in the evolving landscape of power systems is addressed. As prominence is gained by Renewable Energy Sources (RES) due to carbon-neutral policies, economic losses for Independent Power Producers (IPP) and Renewable Energy Providers (REP) might be potentially led to by the traditional ED model. To ensure that participation is ensured by all stakeholders in the power system, they are categorized as the Independent System Operator (ISO), IPPs, and REPs, with specific target benefits being designed for each group. The integration of Power-to-Gas (P2G) technology from hydrogen infrastructure into the ED process is proposed to secure these target benefits. Centered on the Cost-Based Pool (CBP) market structure, the increasingly complex Mixed Integer Linear Programming (MILP) problem is tackled in our case study using Columns and Constraint Generation (C&CG) techniques.

https://doi.org/10.5370/KIEE.2023.72.11.1366

변범석(Beom-Seok Byeon) ; 박의종(Eui-Jong Park) ; 정상용(Sang-Yong Jung) ; 김용재(Yong-Jae Kim)

A permanent magnet was used to improve the torque density of the magnetic gear for gear ratio conversion, and a study was conducted to attach the permanent magnet to the tooth tip of the rotor. Through this, it was found that attaching a permanent magnet to the outer rotor is effective. In addition, in the case of gear ratio conversion, in this method, there is a part where the magnetization direction of the electromagnet and the permanent magnet are opposite, resulting in poor results. Therefore, when applied to teeth with coincident magnetization directions, good results were obtained in all cases even when the gear ratio was converted.

https://doi.org/10.5370/KIEE.2023.72.11.1372

임희성(Hee-Sung Lim) ; 이상혁(Sang-Hyuk Lee) ; 이교범(Kyo-Beum Lee)

This paper proposes a method to estimate SOC(State of charge) by extracting parameters for each circuit element of an LFP(LiFePO4) battery equivalent circuit model and combining the Extended Kalman Filter and coulomb counting method. A lithium battery cell is generally modeled using an equivalent circuit, and parameters for each circuit element of the battery model can be extracted using pulse charging and discharging curves. Those curves are collected experimentally to characterize battery performance at various operating points. Numerical optimization algorithms are repeatedly performed in computer simulation to minimize errors in battery models and experimental data. SOC is estimated using extracted parameters and the Extended Kalman Filter algorithm.

https://doi.org/10.5370/KIEE.2023.72.11.1379

이정훈(Jung-Hoon Lee) ; 유재곤(Jae-Gon Yoo) ; 김종수(Jong-Soo Kim)

This paper describes the development of an LED indoor lighting system using the hot current balancing technique. In order to improve the power density, efficiency, and unit cost of an indoor lighting system, a current balancing technique through a thermal current balancing capacitor is presented. Simulations and experiments are conducted to verify the validity and performance evaluation of the proposed method. Simulations are performed using the PSIM simulation tool, and experiments are conducted by designing and manufacturing working sample-level hardware under the same conditions. As a result of the experiment, it was confirmed that 44.6% of current deviation, 10.5% of light efficiency, and 8.6% of annual power consumption were improved compared to the existing indoor lighting system.

https://doi.org/10.5370/KIEE.2023.72.11.1386

노수진(Sujin Noh) ; 신경훈(Kyung-Hun Shin) ; 방태경(Tae-Kyoung Bang) ; 조한욱(Han-Wook Cho)

The imperative of shifting the transportation sector towards environmentally sustainable electric propulsion has become unmistakable. Superconducting motors have emerged as a revolutionary solution, offering intrinsic benefits such as compactness, lightweight design, and exceptional efficiency in comparison to conventional motors. These attributes hold immense promise, particularly when harnessed in the propulsion systems of expansive maritime vessels and aviation crafts, opening up previously unattainable frontiers of power density. In this paper, a 2MW fully air-core superconducting motor was designed for electric propulsion applications. Subsequently, its characteristics were compared with those of an iron-core superconducting motor. Through the analysis of parameters such as weight, power density, and magnetic flux density, it was conclusively established that for aviation and marine propulsion systems, the more suitable motor is the fully air-core superconducting motor.

https://doi.org/10.5370/KIEE.2023.72.11.1393

하민우(Min-Woo Ha) ; 공소정(So-Jeong Kong) ; 이준영(Jun-Young Lee) ; 김민기(Min Kee Kim) ; 석오균(Ogyun Seok)

Multilayer ceramic capacitors (MLCCs) have been used in various electronics including electric vehicles. Dielectric absorption of BaTiO3-based X7R MLCCs is reported in the manuscript. We reviewed the dielectric absorption in detail which was not DC or AC characteristics. We fabricated the X7R MLCCs and measured the devices using an LCR meter, a test fixture, and two source measure units. The dielectric absorption was measured in the fabricated devices. And then the ω0, Cd, and Rd were altered by rms voltage of AC signals. However, these were not affected by the DC voltage. The C∞ from atomic or molecular polarization was not altered by the Vrms and VDC which means this study is right. When the operating frequency of the X7R MLCCs is less than the frequency when the dielectric absorption activates, the capacitance reduces from C∞ + Cd to C∞. We should suppress the dielectric absorption of the MLCCs which generates from an insulating layer. The dielectric absorption can be used to determine the mass production of commercial MLCCs.

https://doi.org/10.5370/KIEE.2023.72.11.1399

박재범(Jae-beom Park) ; 김민준(Min-jun Kim) ; 원형식(Hyeong-sik Won) ; 조현진(Hyun Chin Cho) ; 조현종(Hyun-chong Cho)

Gastric cancer has a high incidence in East Asians, and the risk increases over time. Often, gastric cancer presents no early symptoms, leading to missed treatments. Consequently, in Korea, support is provided to individuals over 40 years of age who undergo gastroscopy. However, as the number of gastroscopy patients increases, doctors' fatigue rises, becoming a factor that can lead to misdiagnosis. Therefore, this paper proposes a CADx (Computer-Aided Diagnosis) system for gastric lesion classification based on ConvNeXt and ViT (Vision Transformer), applying the SAM (Sharpness Aware Minimization) optimizer. ConvNeXt is a network that achieves high performance by incorporating techniques from Swin Transformer and the latest advancements, with ResNet-50 as the base model. ViT divides the image into smaller patches and uses these patches as input to the Transformer. This allows for learning relationships between patches and ultimately leads to image classification. To address the issue of limited data in medical images, the gastric abnormal dataset was augmented using the AutoAugment policy. The SAM Optimizer is an optimization technique that detects and minimizes the "sharpness" of the loss function that may occur during the deep learning model's learning process. Using this method, the sensitivity of classifying abnormal and normal gastroscopy images in ConvNeXt increased from 0.7167 to 0.9583 for the original dataset and from 0.7583 to 0.9833 for the augmented dataset. ViT exhibited a significant decrease from 0.9500 to 0.7750 in the original dataset but increased from 0.9500 to 0.9583 in the augmented dataset. This demonstrates that the SAM Optimizer can effectively enhance CADx performance.

https://doi.org/10.5370/KIEE.2023.72.11.1406

박재범(Jae-beom Park) ; 신소영(So-young Shin) ; 조현종(Hyun-chong Cho)

Lung cancer ranked second in Korea domestic cancer incidence in 2020 and second in death rate. Lung cancer often has no early symptoms, so patients often miss the time of treatment. Accordingly, in Korea, lung cancer has been included in the national cancer screening since 2019. However, among misdiagnosis cases, lung cancer had the highest misdiagnosis rate, and the accuracy of screening may vary depending on the medical specialist's skill level and fatigue. Accordingly, this paper proposed a lung cancer CADx(Computer-Aided Diagnosis) system based on EfficientNetV2-L and ConvNeXt-B. EfficientNetV2 is a model that can have high classification performance with a small number of parameters using the Training-Aware NAS (Neural Architecture Search) method. ConvNeXt is a network that achieves higher performance than ViT(Vision Transformer) by combining the latest techniques with ResNet-50 as a base model. Medical imaging generally suffers from a data shortage problem. Therefore, we augmented the lung cancer dataset using AutoAugment using the ImageNet augmentation policy. Through this method, the sensitivity in classifying malignant(lung cancer) and normal improved from 0.8354 to 0.9638 in EfficientNetV2 and from 0.9796 to 0.9963 in ConvNeXt. AUC (Area Under the ROC Curve) also improved from 0.9967 to 0.9974 for EfficientNetV2 and from 0.9973 to 1.0000 for ConvNeXt. Additionally, noise that may generally occur in CT images was added and compared through Gaussian noise. EfficientNetV2's Sensitivity was 0.7417 in the original model and 0.8954 in the model to which AutoAugment was applied, representing a decrease of 9.37% and 6.84%, respectively. In contrast, ConvNeXt exhibited a Sensitivity of 0.9796 in the original model and 0.9963 in the model to which AutoAugment was applied, showing no decrease in performance. This led to the development of a CADx system that demonstrates excellent performance.

https://doi.org/10.5370/KIEE.2023.72.11.1412

손호선(Ho Sun Shon) ; Kong Vungsovanreach(Kong Vungsovanreach) ; 윤석중(Seok Joong Yun) ; 오진우(Jin Woo Oh) ; 강태건(Tae Gun Kang) ; 김경아(Kyung Ah Kim)

Utilizing gene expression data from kidney cancer patients, we have developed a machine learning-based deep learning algorithm to extract significant genes for predicting the patients' prognosis and enhance classification performance while addressing data imbalance issues. Particularly, classification based on tumor stage plays a crucial role in determining appropriate treatment approaches for kidney cancer patients and predicting post-treatment prognosis. We classified kidney cancer tumor stages into four categories and evaluated their performance. The results demonstrated that the SVM algorithm, utilizing an autoencoder for feature extraction and addressing data imbalance through the SMOTE technique, exhibited the best performance in terms of accuracy, recall, precision, F1-score, and AUC. These results can be utilized to choose the most suitable treatment strategy at the current state and for predicting the prognosis and enabling early diagnosis of kidney cancer.

https://doi.org/10.5370/KIEE.2023.72.11.1420

호종갑(Jong Gab Ho) ; 정아현(A Hyun Jung) ; 최지희(Ji Hee Choe) ; 민세동(Se Dong Min)

Gait analysis is an essential component of clinical examination. In particular, stride length is used as an important indicator in personal health management. In this study, an evaluation study was conducted on the feasibility of estimating stride length based on a deep-learning model using only plantar pressure data. For the experiment, 10 subjects were recruited and plantar pressure data and gait movies were collected while walking. From the gait data, one stride length of raw data, center of pressure, and gait cycle index were extracted. afterward, three datasets were built and used as input deep learning models. As a result, the performance of the 1D CNN model was the best, with MAE of 3.57 ± 2.64 cm and MARE of 2.82%, confirming the feasibility of step length estimation based on plantar pressure data. The results of this study can be used for personal health monitoring and PDR estimation research.

https://doi.org/10.5370/KIEE.2023.72.11.1427

임하민(Hamin Lim) ; 신항식(Hangsik Shin)

This study aims to categorize individual Activities of Daily Living (ADL) into activity categories by utilizing acceleration features. The research involves extracting time and frequency features from 10 different types of ADL acceleration data. These features are used to cluster each behavior through a bottom-up clustering approach, specifically the Ward Linkage method. The findings of this study reveal that bottom-up clustering, utilizing time-domain and frequency-domain acceleration features, provides insights into behavior characteristics such as magnitude, frequency, and repeatability, as indicated by metrics like acceleration magnitude and frequency distribution. This approach allows for the clustering of relatively similar and interconnected behaviors. Notably, various time and frequency domain characteristics, including magnitude per unit time and concentration at specific frequencies, were identified as effective indicators for behavior clustering, in addition to the commonly used total acceleration magnitude.

https://doi.org/10.5370/KIEE.2023.72.11.1434

배문규(Munkyu Bae) ; 김건태(Guntae Kim) ; 박이형(Yi-Hyeong Park) ; 강창묵(Chang Mook Kang)

In this paper, we present a transfer learning-based human motion capture and classification system using multiple IMU and flex sensors without camera. The proposed system consists of 6 low-cost IMUs and 12 flex pressure sensors. For the human motion classification, the signals of multiple IMUs were reconstructed into images using wavelet transform. The transformed image is designed to be used as an input to the convolution neural network. The network was designed using Inception V3-based transfer learning. For motion capture without using a camera, the presented system was constructed through a combination of IMUs (MPU6050) and flex pressure sensors (thin film pressure sensors) rather than multiple IMUs. The proposed method showed 86.67% accuracy and 0.869 points of f1-score. The proposed system is expected to be applicable to a healthcare system that can provide exercise coaching without cameras, and without space restrictions.

https://doi.org/10.5370/KIEE.2023.72.11.1441

왕창원(Changwon Wang) ; 신항식(Hangsik Shin)

The COVID-19 pandemic has fueled a growing interest in non-face-to-face medical care, prompting numerous hospitals in South Korea to embark on the journey towards becoming smart hospitals. This study conducts a thorough examination of the concept of smart hospitals, evaluating their definition, the prevailing situation regarding these institutions in South Korea and globally, the core technologies integral to their functioning, and practical instances of their implementation. Additionally, the study engages in a discussion concerning the constraints of smart hospitals and delineates the paths for their future development.

https://doi.org/10.5370/KIEE.2023.72.11.1449

이수연(Su-Yeon Lee) ; 문종민(Jong-Min Moon) ; 이상엽(Sang-Yeob Lee) ; 윤종서(Jong-Seo Yoon) ; 이진수(Jin-Su Lee) ; 이정은(Jung-Eun Lee) ; 이정환(Jeong-Whan Lee)

In this study, we aim to investigate the correlation between changes in arterial blood pressure and the Photoplethysmography (PPG) signal, which is one of the most commonly utilized physiological signals, alongside electrocardiography (ECG) signals. We will use the PPG signal, which reflects changes in blood flow due to external pressure, in conjunction with ECG to examine the variations in arterial blood pressure. Similar to oscillometric methods, during the gradual increment and decrement of external pressure, the PPG signal is influenced by the external pressure, leading to turbulence in the blood vessels. Consequently, vascular dilation occurs, and changes in vascular volume due to this dilation are estimated through PPG. The portion where turbulence occurs during the increase in external pressure is defined as the first turbulence onset region, while the region where turbulence occurs as external pressure decreases is termed the second turbulence onset region. To examine changes in the PPG waveform, inflection points expected to be due to turbulence were detected in the envelope formed by connecting the peaks of the PPG signal. In the first turbulence onset region, where turbulence is induced by an increase in external pressure, a high correlation was observed with systolic blood pressure. In the second turbulence onset region, where turbulence occurs as external pressure decreases, a high correlation was found with diastolic blood pressure. To identify inflection points in the envelopes formed by connecting the peaks of the PPG signal measured during the turbulence onset regions, we investigated the correlation with systolic and diastolic blood pressure by varying the interpolation method and adjusting the window size of the smoothing filter. When examining the correlation with diastolic blood pressure in the second turbulence onset region, it was visually discernible that the amplitude changes in the PPG signal, and certain inflection points showed a very high correlation with blood pressure. This resulted in minimal errors and a narrow range in the estimated diastolic blood pressure. When a shorter window length(100 samples) is used for the smoothing filter, an average RMSE error was approximately 4.6812±5.73 mmHg / 2.7722± 3.59 mmHg (SYS/DIA) were observed. This level of accuracy is comparable to commercially available at-home blood pressure measurement devices (including cuffs), which have an accuracy of ±5mmHg. The method proposed in this study involved the application of a smoothing filter with an appropriate window size and utilized the correlation between inflection points and turbulence onset regions to estimate arterial blood pressure. It demonstrated a higher accuracy in estimating diastolic blood pressure compared to systolic blood pressure. When complemented with the PTT (Pulse Transit Time)-based systolic blood pressure estimation method known for its high accuracy, it holds the potential for estimating blood pressure, potentially replacing wearable devices or home blood pressure monitors in the future. Although the study was conducted with a small number of participants, it exhibited significant similarities, and while the arterial pressure estimation based on turbulence induced by external pressure is not yet conclusive, the resemblance to blood pressure in response to the proposed idea appears promising. Therefore, it was confirmed that further research is needed to validate its effectiveness in the future.

https://doi.org/10.5370/KIEE.2023.72.11.1463

장승완(Seungwan Jang) ; 이현영(Hyun Young Lee) ; 이경은(Gyeongeun Lee) ; 김훈(Hoon Kim) ; 김영(Young Kim) ; 민세동(Se Dong Min)

Alternative shoes (Crocsⓡ, C) are shoes often used in Daily life for comfort and fashion purposes. However, alternative shoes do not support the back of the foot, reducing athletic ability, and lowering the height of the foot can cause loss of balance and fall if caught by an obstacle. Therefore, in this study, we compared alternative shoes and sneakers (S) to determine the difference in foot height when passing an obstacle, and implemented an IMU sensor in the form of an accessory that can be conveniently used in alternative shoes. The implemented sensors were compared and evaluated through motion capture. in this study, a gait track with a mixture of curves and straight lines was created to simulate situations that may occur in real daily life, and obstacles of 1 cm, 10 cm, 20 cm, and 26 cm were used. Through this, obstacle gait was performed according to the height of the obstacle and the type of shoe. Comparison of obstacle heights according to shoe type was analyzed using an independent samples t-test. As a result of the analysis, it was found to be 1 cm (C = 9.63 ± 2.06 cm, S = 10.94 ± 2.03 cm, t = -2.115, p < 0.05) and 26 cm (C = 41.3 ± 3.71 cm, S = 43.04 ± 3.92 cm, t = -2.075, p < 0.05) indicated a statistically significant difference. This confirmed that the alternative shoes lifted the foot lower than the sneakers at the obstacle. This indicates that alternative shoes do not support the back of the foot, which tends to lower the height of the foot when passing obstacles. A comparative evaluation of motion capture and IMU sensors was performed using Bland-Altman plots and Pearson Correlation. As a result of comparative evaluation, alternative shoes were found to have a positive correlation with r values of 0.543*, 0.434**, and 0.464** at 1 cm, 10 cm, and 26 cm, excluding 20 cm. However, sneakers show no correlation for all obstacles. This suggests that the IMU sensor can be used by attaching it to an alternative shoe and measuring foot height. In the case of sneakers, it was discovered that the reflective marker attached to the tongue area was affected by the movement of the instep and ankle and curved gait, causing the foot to move when leaving the ground and passing an obstacle. To compensate for this phenomenon, additional research is needed in which reflective markers are attached to areas that are not affected by instep and ankle movements and curved gait. Additionally, the noise removal function due to the impact of the IMU sensor and the drift error filtering function due to integration must be improved.

https://doi.org/10.5370/KIEE.2023.72.11.1470

김태훈(Tae-Hoon Kim) ; 박종진(Jong-Jin Park)

In this paper, using teeth data set provided by AIHub individual tooth semantic segmentation was carried out through layered UNet. AIHub's dental data set is provided as 2D panoramic X-ray images and 3D CBCT images to develop dental AI models. The layered UNet proposed in the previous paper showed that it also learned excellently on teeth data sets that are distinguished for each tooth by assigning tooth numbers. As a result of the simulation, the learning results by the layered UNet model showed loss function values of 0.005 and 0.006 for training and validation data, respectively. Accuracy and IoU used as other evaluation indicators showed results of (0.99, 0.99) and (0.89, 0.88) for （training and validation data）, respectively. the learned layered UNet was applied to the existing tooth data to segment the teeth and stack the results for each slice to extract the 3D tooth shape. Although there are some parts where the learning was not done well, the teeth were extracted being well distinguished by tooth, and it was shown that individual tooth could also be extracted.

https://doi.org/10.5370/KIEE.2023.72.11.1477

홍윤성(Younseung Hong) ; 홍석주(Seokju Hong) ; 강병주(Byeongju Kang) ; 황윤형(Yunhyoung Hwang)

For the autonomous driving safety, it is important to know the future trajectories of surrounding vehicles, especially during the transition period where the autonomous and non-autonomous vehicles are mixed each other. In this regard, neural-network models including the long short-term memory(LSTM) have demonstrated outstanding performance in the field of vehicle trajectory prediction, but their accuracy significantly decreases in the prediction for abnormal situations, because the dataset for them are usually small-scaled and the prediction results tend to be biased to the maneuvers of large portion. To tackle this problem, we propose a trajectory prediction framework that incorporates classification-based switching mechanism. After the maneuver was classified by the radial basis function(RBF) kernel-based support vector machine(SVM), the prediction results were selectively obtained from multiple LSTM-based prediction models in the proposed framework, where each prediction model was trained with dataset for each maneuver. In this way, the future trajectories could be predicted successfully even for the abnormal maneuvers because the small-scale dataset for them could train the model independently in the proposed framework. The proposed framework was trained and validated with the real trajectory dataset collected at Bang-I Station intersection. The sequence of vehicles’ speed, yaw-rate, latitude and longitude coordinate were used as inputs in the proposed framework.

https://doi.org/10.5370/KIEE.2023.72.11.1485

남의석(Eui-Seok Nahm)

In this paper, an energy saving method for wastewater treatment biological process is proposed. In the wastewater treatment biological process, the effect on the output according to the change in input takes 4 to 6 hours due to the characteristics of the biological reaction. However, existing studies did not take this into consideration and implemented a prediction system for input versus output using data from the same time. In order to solve this problem, this paper 1) generates input/output data considering the biological reaction time of output by input, 2) builds an artificial neural network prediction model using this data, and 3) determines the minimum water quality from this model to achieve the target water quality. The blower was controlled by calculating the blowing volume. We proposed a mathematical method that considers the biological response time of output by input, and in this case, a method of implementing an artificial neural network model and a method of controlling actual airflow volume were proposed. As a result, it was possible to reduce the power consumption that occurred when trying to achieve the target water quality by unconditionally increasing the existing DO.

https://doi.org/10.5370/KIEE.2023.72.11.1491

오찬혁(Chan-Hyeok Oh) ; 이기연(Ki?Yeon Lee) ; 채동주(Dong?Ju Chae) ; 임승택(Seung?Taek Lim)

In recent years, many studies have been conducted on DC distribution systems and commercialization attempts have been made, but they suffer from the lack of requirements for low-voltage direct current. This paper proposes a short-circuit capacity calculation method for low-voltage direct current systems by considering the short-circuit characteristics of DC/DC converters. In order to consider the different short-circuit fault behaviors of each converter, the equivalent capacitor capacity of the output terminal of the converter and the maximum output current of the converter are provided by the converter manufacturer. Using this, the short-circuit capacity is calculated by mixing the short-circuit characteristics of the converter output terminal capacitor and the short-circuit current supply characteristics due to the switching control of the converter. The proposed method is verified using Matlab/Simulink simulation to examine the appropriateness of the short-circuit capacity calculation method using the proposed method.

https://doi.org/10.5370/KIEE.2023.72.11.1498

이훈서(Hunseo Lee) ; 강현일(Hyunil Kang) ; 박영(Young Park)

A low-power UV camera and software for ESS safety monitoring are proposed. The UV camera can detect UV in the wavelength range of 285 to 375 nm and has a power consumption of less than 4.4 W. The software is developed using LabVIEW in Windows environment and provides real-time image display, storage, exposure control, and filtering functions. The proposed UV camera is expected to be able to detect corona discharge in the interior of ESS, which is often not directly exposed due to the complex structure including the housing and various devices. This paper proposes a software for ESS safety monitoring using a low-power UV camera developed by combining a 1/2.3-inch CMOS sensor that can detect UV in the wavelength range of 285 to 375 nm and a 25mm f/2.8 lens. The software was developed using LabVIEW in Windows environment.

https://doi.org/10.5370/KIEE.2023.72.11.1502

김권철(Kwonchul Kim) ; 김인수(Insu Kim)

Yeongjongdo Island, where Incheon Airport is located, has six 154 kV substations, including Yeongjong, Jungsan and Eurwang substations, which are under the control of Korea Electric Power Corporation (KEPCO), and A, B and C substations, which are under the control of Incheon Airport Corp. Since Incheon Airport Corp. is not a "district power supplier," it cannot supply power to KEPCO. Therefore, Incheon Airport Corp. has to pay the electricity bill, including the unused electricity, when the reverse transmission occurs. When the load of Eulwang substation, which is located at the end of the system, increases, reverse transmission of power from "C" to Eulwang substation may occur. To prevent reverse transmission power, power flow analysis and countermeasures are required. In this paper, ETAP, a power system analysis program, was used to present the modeling of six 154 kV substations and transmission lines in Yeongjongdo area, and to confirm the conditions and preventive measures for reverse power transmission.

https://doi.org/10.5370/KIEE.2023.72.11.1507

오민성(Min-Sung OH) ; 황승혜(Seung-Hae Hwang) ; 신경희(Kyung-hee Shin) ; 진창수(Chang-Soo Jin) ; 김성수(Sung-soo Kim)

Redox flow batteries have received much attention due to their long cycle life and safety. However, in order to improve the problem of relatively low energy density and the use of strong acid electrolytes such as sulfuric acid, research on all organic redox flow batteries (AORFB) is actively underway. In this paper, an ester group and an ammine group were introduced to improve solubility through hydrogen bonding at the two N positions of 4,4`-bipyridyl, respectively. The synthesized material exhibited high solubility at 2.24 M, which surpassed that of previously reported materials (1.4 ∼ 1.6 M). In the cell test, the initial discharge capacity was 1.8 [Ah/L]. After 500 cycles, both Coulombic efficiency and capacity retention remained at 99.1% and 90.5%., respectively.

https://doi.org/10.5370/KIEE.2023.72.11.1512

박정수(Jung-Soo Park) ; 최유림(Yu-Rim Choi)

Recently, the adoption of new and renewable energy sources such as solar and wind power has increased, and the importance of direct current-based systems to increase energy efficiency is increasing. Accordingly, various studies related to Low Voltage Direct Current(LVDC) distribution are in progress, the industry related to low voltage direct current distribution is developing, and related systems are also in progress. As the industry increases, safety issues such as load protection and electric shock to humans are continuously being raised when implementing low voltage direct current distribution networks. To solve this problem, research on direct residual current detectors (RCDs) and residual current monitors (RCMs) is in progress, and product commercialization is also in progress. However, since RCDs and RCMs are monitoring devices, they cannot be shut off in situations where quick shutoff is required. has. Accordingly, it is necessary to develop a DC earth leakage circuit breaker that can cut off the electric circuit as quickly as possible when a DC leakage occurs. [1-3]. The studies related to direct current electric shock that have been studied so far include research on the effects of electric shock on the human body in direct current in IEC 60479 and research on direct current leakage protection devices in IEC TS 63053 [4, 5]. IEC, an international standards organization, has formed a working group and is conducting research and standardization. However, in implementing actual direct current distribution, research on human electric shock protection within customers is not active and research is still insufficient [6].

https://doi.org/10.5370/KIEE.2023.72.11.1520

창상훈(Sang-Hoon Chang)

This paper is verified the lightning shielding effect of overhead ground wire(OHGW) on high-speed railway catenary systems. The simulation results show that OHGW can effectively shield lightning current, resulting in a significant reduction in leakage current and improved lightning protection performance. The simulation was conducted using EMTP-ATP, which are widely used to analyze transient phenomena in power systems. The ground resistivity was assumed to be 1,000 [Ω·m]. The lightning shock withstand voltage of the catenary insulator was set to 250 [kV] and 380 [kV]. The lightning current was varied from 1 to 30 [kA]. As a result, when OHGW is installed in a bridge section where there is a risk of lightning, the minimum flashover current increases from 8 [kV] to 10 [kV] when the catenary insulator is 250 [kV]. At 380 [kV], the minimum flashover current increases from 14 [kV] to 17 [kV]. The results of this study suggest that OHGW is an effective way to improve the lightning protection performance of high-speed railway catenary systems.

https://doi.org/10.5370/KIEE.2023.72.11.1526

한가람(Ga-Ram Han) ; 방준호(Jun-Ho Bang) ; 유인호(In-Ho Ryu) ; 김태형(Tae-Hyung Kim) ; 소병문(Byung-Moon So) ; 송제호(Je-Ho Song)

According to electrical accident statistics, transformer types account for a large proportion of accidents in high-voltage electrical facilities. Various methods are used to diagnose the condition of electrical facility in on-line(uninterrupted), such as detecting infrared thermal imaging, ultraviolet, and ultrasonic sound. However, it is difficult to detect internal defects in cast-resin transformer because the outside is sealed with epoxy. This problem can be solved by utilizing the characteristics of the transmission, reflection, and propagation speed of ultrasonic waves. This paper proposes a temperature estimation method using ultrasonic waves to detect a small temperature rise in the early stage of internal short at the primary winding. Ultrasonic propagation characteristics according to the thickness and temperature changes of epoxy was obtained through experimentation and analysis.

https://doi.org/10.5370/KIEE.2023.72.11.1534

김용희(Yonghee Kim) ; 이세희(Se-Hee Lee)

Internal resistances (IR) of lithium-ion battery as one of critical parameters for safety diagnosis of energy storage system (ESS) were analyzed based on a time ratio for characterizing the performance of batteries by using the direct current ? internal resistance (DC-IR) method after solving electro-chemical governing equations with the finite element analysis (FEA). Recently, the IR has been interested to check the status of lithium-ion battery related to a safety issue, but the specific definition is relatively ambiguous for ESS. To test the characteristics of IR, here we adopted a numerical approach and tried to show the variety of IR due to a time ratio. Until now, the numerical analysis technique has been developed for analyzing the lithium-ion battery and we have also implemented the DC-IR process incorporating with FEA. By using this numerical setup, the various values of IR were calculated with the different time ratios of voltage and interpreted based on the electro-chemical process. The values of IR were different from the time ratio and IR should be properly defined as its application areas. Additionally, a brief diagnostic process was also proposed for safety considering an online-monitoring system. It is believed that IR will be more strictly defined once defect data becomes available.

https://doi.org/10.5370/KIEE.2023.72.11.1540

강자윤(Ja-Yoon Kang) ; 문영채(Young-Chae Mun) ; 박지만(Ji-Man Park) ; 전정채(Jeong-Chay Jeon)

Solid insulators such as XLPE and epoxy are used in extra-high voltage electrical equipment and have excellent resistance and insulation properties. However, if the insulation is destroyed due to long-term use or manufacturing defects, it can lead to a major accident, so abnormal signals can be detected through various online sensors such as UHF, HFCT and diagnostic equipment such as ultrasonic, ultraviolet corona measurement equipment and thermal imaging cameras. Efforts to prevent accidents by detecting them in advance are continuing. However, these diagnostic techniques based on acquisition and analysis of abnormal signals depend on the user's expert knowledge, and in particular, even if abnormal signals for internal defects in the insulator are detected, there are limitations in identifying the exact physical cause or location. In this paper, terahertz waves were applied to detect internal defects in solid insulated electrical equipment as images rather than signals, and the results were described. First, terahertz waves were applied to XLPE power cables, and the mold transformer was cut to a size convenient for testing and a terahertz wave penetration test was also performed. In addition, to confirm the transmission characteristics of waves, terahertz waves were applied to an epoxy plate, a representative insulating material, and the results were analyzed.

https://doi.org/10.5370/KIEE.2023.72.11.1546

박지만(Ji-Man Park) ; 강자윤(Ja-Yoon Kang) ; 문영채(Young-Chae Moon) ; 이진식(Jin-Sik Lee) ; 전정채(Jeong-Chay Jeon)

Since installation of power cables in EHV(extra-high voltage) distribution switchboard should be considered for tension and length of cables, termination processing is performed on-site and most of them are done manually, which can lead to unexpected defects. This paper investigates the partial discharge (PD) characteristics of artificially generated defect in a 22.9kV CN-CV cable termination. First, a 22.9kV CN-CV power cable was cut to a length of 3m for a partial discharge test, and both ends were terminated. One terminal was separated by about 5mm between the end of the stress-cone and the plate washer in the waterproof cap to create a artificial defect. For comparison under the same environment, PD measurement was executed on a defective cables with two normal cables, and the voltage was applied of 13.2 [kV], 18 [kV] and 20 [kV], respectively. PD measurements were performed by installing a high frequency current transformer (HFCT) to the ground wire. As a result of PD measurement, insignificant surface discharge occurred at 13.2 [kV] in the defect cable, internal discharge was detected at 18 [kV], and internal discharge switching to surface discharge were detected at 20 [kV]. On the other hand, few surface discharge (mostly noise) was detected only at 20 [kV] in two normal cables.

https://doi.org/10.5370/KIEE.2023.72.11.1554

박중성(Jung-Sung Park) ; 김발호(Bal-Ho Kim)

The purpose of this paper is to summarize and share the field experiment results of KEPCO's project consortium to create a TSO-DSO-DERA interaction scheme. The field experiment was conducted based on the prequalification algorithm proposed in the previous research from the same consortium and was designed to verify the validity of the algorithm under realistic grid conditions. In addition, during the course of the field experiment, it was found that points that were missed or not given much importance in the existing prequalification algorithm could affect the completeness of the overall system, and then practical improvements were made to improve it. The demonstration results confirm that the proposed algorithm is effective in real-world grid environments and can help DSOs ensure the reliability of the distribution system while supporting DERA's participation in the wholesale market using the proposed prequalification scheme.

https://doi.org/10.5370/KIEE.2023.72.11.1568

조호령(Ho-Ryung Cho) ; 남한석(Han-Seok Nam) ; 김종남(Jong-Nam Kim) ; 유홍국(Hong-Kuk You) ; 나영재(Young-Jae Na) ; 김재문(Jae-Moon Kim)

In the event of loss of roadbed on an electric railway line due to typhoon or heavy rain damage caused by abnormal weather, or damage to a subway pole due to an unexpected train derailment, installation of catenary poles for emergency recovery is necessary to restore the electric railways. Conventional emergency catenary poles are made of steel, so they are very heavy, and the length per unit is large, making transportation and installation inconvenient. Also, there is a risk of industrial accidents due to workers' musculoskeletal disorders. In this study, we developed an emergency recovery catenary pole using aluminum, a lightweight material, and researched and developed a slimmer rail fastening device that can also be applied to concrete ballast. The developed product underwent factory testing and reference testing, was assembled and installed on a field test, and then a safety test was performed. The product developed is expected to minimize disruption to train operations and prevent industrial accidents for related workers by safety and quickly restoring electric railways.

https://doi.org/10.5370/KIEE.2023.72.11.1575

강병욱(Byungwook Kang) ; 이종우(Jongwoo Lee)

In Railway, The interlocking is safety essential systems, and if it malfunction, they can cause major accidents, so high safety requirements must be met. In order to prevent interlock design errors and verify safety, the need for research on the introduction of formal methods has been raised, and in the case of Europe, projects for standardization are underway. This paper modeled the interlocking logic for signal, point machine, and routes configuration by applying the Petrinet model, one of the formal methods, and verified the safety of interlocking devices.

https://doi.org/10.5370/KIEE.2023.72.11.1581

김효상(Hyosang Kim) ; 이종우(Jongwoo Lee)

High-speed trains often experience minor and major collisions during the process of stopping at towing lines and stations at the end of vehicle operations. Damage to vehicles due to high-speed train accidents cause disruptions in operational driving, which leads to physical and human damage. Therefore, there is a need for a system that can stop at a precise location when docking or stopping within a station for high-speed trains. For conventional railways, substantial costs are incurred because they use the coils called ATO (Automatic Train Operation) to control the stopping position of vehicles through an internal communication network. In this study, we verified the applicability considering distance errors due to front vehicle curvature and diffuse reflection, as well as gaps with forward trains through real-time location (distance) analysis for a precise positioning stop system using laser distance sensors.

https://doi.org/10.5370/KIEE.2023.72.11.1586

권경빈(Kyung-bin Kwon) ; 박종영(Jong-young Park) ; 정호성(Hosung Jung) ; 홍수민(Sumin Hong) ; 허재행(Jae-Haeng Heo)

In this paper, we design a framework of the energy storage system (ESS) controller in virtual power plant (VPP) that maximize the profit. We consider the VPP that includes photovoltaics, wind turbines and demand along with ESSs and describe the environment based on Markov decision process (MDP). To find the best policy for ESS charging and discharging control, we implement a deep Q-network (DQN) method that trains a neural network which estimates Q-function values for each possible discrete actions. In the numerical test utilizing real-world data of Namgwangju Station, ERCOT and US government, we train the DQN and demonstrate that the proposed algorithm converges. Through the test with the trained policy, we showcase that the policy functions effectively in the scenario with uncertainty from renewable generations and load, as it responds adaptively to electricity prices.