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A Study on Prediction and Accuracy Improvement of SVR Voltage Control in Distribution System Based on Machine Learning

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Transactions of the Korean Institute of electrical Engineers 2025年第1期74卷 7-14页

作者： Yoo, Byungchan Choi, Wonna Jung, Seungmin Dept. of Electrical and Computer Engineering University of Seoul Korea Republic of

The proportion of distributed energy sources in the distribution network is rapidly increasing. Along with this, voltage management is becoming more difficult, and stability issues in the power system are being reported. Until recently, the voltage of distribution lines has generally been regulated using voltage regulators, predominantly deployed in sections where rapid voltage drops occur. However, as the characteristics of distributed energy sources are reflected, the efficiency of the voltage regulator diminishes. Therefore, cooperation with substations is necessary for stable operation of the distribution network. This paper aims to predict the operation of a machine learning-based voltage regulator to evaluate voltage fluctuations occurring in distribution lines and the corresponding control operations in advance. Long Short-Term Memory is capable of prediction on time scales. Therefore, the output characteristics of distributed energy sources can be considered. Additionally, to improve prediction accuracy, cases are generated in the OpenDSS-Python environment and additional training is performed on the LSTM model. As a result, it was confirmed that the prediction accuracy improved when the proposed method was applied. The machine learning model was verified using four evaluation indices. © 2025 Korean Institute of electrical Engineers. All rights reserved.

关键词： Power distribution lines

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Analysis of Iron Loss Characteristics of PM-Assisted and Fluid-Shaped Synchronous Reluctance Machines for Micro EVs

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Transactions of the Korean Institute of electrical Engineers 2025年第3期74卷 425-431页

作者： Choi, Jaesung Choi, Gilsu Dept. of Electrical and Computer Engineering Inha University Korea Republic of

This paper examines the iron loss characteristics of a permanent magnet-assisted synchronous reluctance machine (PMa-SynRM) and a fluid-shape synchronous reluctance machine (FS-SynRM) for micro EV applications, emphasizing the impact of DC bias fields and minor loops on iron loss estimation. Iron losses are comparatively evaluated using three methods: the Steinmetz method with constant coefficients, the loss separation method with varying coefficients and FFT, and the hysteresis-based model that accounts for minor loops and DC bias fields. The results show that iron losses per unit stack length are higher in the PMa-SynRM, where the effects of DC bias fields and minor loops are more pronounced. Moreover, the Steinmetz and loss separation methods, which neglect these effects, overestimate motor efficiency by up to 1.5% and 0.3%, respectively. This study highlights the importance of incorporating DC bias and minor loops in iron loss and efficiency calculations for micro EV traction machines. © The Korean Institute of electrical Engineers.

关键词： Permanent magnets

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Study on a Regression Model for the Electromagnetic Characteristics of SPMSM Based on Convolutional Neural Network with Attention Mechanism

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Transactions of the Korean Institute of electrical Engineers 2025年第2期74卷 302-309页

作者： Ji, Tae-Hyuk Song, In Seok Kim, Hyung-Woo Jung, Sang-Yong Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Surface-mounted permanent magnet synchronous motors (SPMSMs) are widely used in high-performance system. However, they suffer from torque ripple and cogging torque, which degrade output quality and cause noise and vibration, necessitating optimized design. While finite element analysis offers high accuracy for optimization, it comes with significant computational cost. To address this limitation, this paper proposes an attention mechanism-based convolutional neural network (CNN) regression model to predict SPMSM electromagnetic performance. CNNs capture spatial structures of motor designs, while attention mechanisms highlight key design features, boosting prediction accuracy and efficiency. This study analyzes the effects of attention mechanisms and proposes a CNN-based regression model incorporating them, confirming the effectiveness of the attention mechanism through comparisons with conventional CNN models. © The Korean Institute of electrical Engineers.

关键词： Convolutional neural networks

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A Study on Rotor Shape for Reducing Low-Order Radial Force in Interior Permanent Magnet Synchronous Motors for Air Compressor

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Transactions of the Korean Institute of electrical Engineers 2025年第1期74卷 56-63页

作者： Cheo, Daeseon Kim, Nam-Ho Cho, Jae-Hoon Kwon, Yong-Jun Jung, Sang-Yong Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

In this paper, a rotor design to reduce low order raidal force and electromagnetic vibration in interier permanent magnet synchronous motor (IPMSM) for an air compressor is proposed. First, according to the analysis results of radial force and no-load air-gap flux density of V-type 1-layer and 2-layer models, 2-layer model is selected as the initial model since it exhibits lower low radial force than 1-layer model. Additionally, the no-load air-gap flux density of the 2-layer model is further analyzed, confirming that the low order radial forces affected by 20th order harmonic and the fundamental component of no-load air-gap flux density have a 180° phase difference, canceling each other out. Moreover, the sensitivity anlysis of rotor notches reveals that the 3-Notch model effectively increases magnitude of 20th order harmonic. Based on the aformentionted analysis, as a result, by applying notches to the 2-layer model rotor, the low order radial force and electromagnetic vibration are reduced. Copyright © The Korean Institute of electrical Engineers.

关键词： Permanent magnets

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Multi-Objective Optimization of Torque and Torque Ripple in Double V-Type IPMSM Using a Random Forest-Based Modified PSO-GA Hybrid Method

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Transactions of the Korean Institute of electrical Engineers 2025年第2期74卷 266-272页

作者： Kwon, Yong-Jun Choi, Dae-Sun Wang, Chang-Hyeon Oh, Ho-Jin Yoon, Han-Joon Jung, Sang-Yong Dept. of Electrical and Computer Engineering SungkyunKwan University Korea Republic of

Interior Permanent Magnet Synchronous Machines (IPMSMs) are widely used not only as drive motors for Electric Vehicles (EVs) but also in various industrial fields due to their high efficiency and high power output characteristics. However, because of the embedded magnets, IPMSMs exhibit significant torque ripple during operation, necessitating the use of optimization algorithms to address this issue. For IPMSMs, which have a large number of design variables, the feasible design space is defined by multiple constraints, increasing the complexity of the design optimization process. Therefore, this paper proposes a Random Forest-based Modified PSO-GA hybrid method to perform optimization in the presence of multiple constraints and applies it to the torque and torque ripple improvement design of a Double V-Type IPMSM. ©The Korean Institute of electrical Engineers.

关键词： Permanent magnets

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Research on Rotor Topology of Consequent Pole Motor Based on the Electromagnetic Parameter Analysis

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Transactions of the Korean Institute of electrical Engineers 2024年第4期73卷 682-689页

作者： Yoon, Han-Joon Cho, Jae-Hoon Kim, Yong-Jae Jung, Sang-Yong Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Dept. of Electrical Engineering Chosun University Korea Republic of

This paper researches the electromagnetic parameters of consequent-pole motors (CPMs) considering the rotor topology. First, the concept of electromagnetic parameter analysis is introduced. Second, the CPM is compared with the interior permanent magnet synchronous motors (IPMSMs), focusing the differences of the rotor topology characteristics. With the comparison, the proper rotor type is proposed. Third, we conducted an optimal design to improve the torque characteristics by applying an optimization algorithm. Finally, the demagnetization and stress characteristics are analyzed. Copyright © The Korean Institute of electrical Engineers.

关键词： Topology

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MOPO-HBT: A movie poster dataset for title extraction and recognition

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Multimedia Tools and Applications 2024年第18期83卷 54545-54568页

作者： Ghosh, Mridul Roy, Sayan Saha Banik, Bivan Mukherjee, Himadri Obaidullah, Sk Md Roy, Kaushik Dept. of Computer Science Shyampur Siddheswari Mahavidyalaya Howrah India Dept. of Computer Science & Engineering Aliah University Kolkata India Dept. of Electronics & Electrical Communication Engineering IIT Kharagpur Kharagpur India TISA Lab Dept. of Computer Science West Bengal State University Barasat India

Real-world images often encompass embedded texts that adhere to disparate disciplines like business, education, and amusement, to name a few. Such images are graphically rich in terms of font attributes, color distribution, foreground-background similarity, and component organization. This aggravates the difficulty of recognizing texts from these images. Such characteristics are very prominent in the case of movie posters. One of the first pieces of information on movie posters is the title. Automatic recognition of movie titles from images can aid in efficient indexing as well as information conveyance. However, it is accompanied by other texts like the names of actors, producers, taglines, dates, etc. Though the organization of components is somewhat similar across different film industries like Tollywood (West Bengal), Bollywood (Mumbai), and Hollywood (Los Angeles), the graffiti patterns differ in multifarious instances. To address the problem of movie title understanding, we propose a dataset named MOvie POsters-Hollywood Bollywood Tollywood (MOPO-HBT) that encompasses movie posters from the aforementioned industries. The entire dataset is publicly available (http://***/11564) for research purposes. The baseline results of title identification and recognition were obtained with a CNN-based (Convolutional Neural Network) approach, wherein the titles were extracted using the M-EAST (Modified-Efficient and Accurate Scene Text) detector model. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Character recognition

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Analysis of Shaft Voltage Characteristics According to Rotor Overhang of Wound-Field Rotor Synchronous Motor for Electric Vehicle

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Transactions of the Korean Institute of electrical Engineers 2024年第10期73卷 1648-1653页

作者： Lee, Jin-Hwan Yoon, Han-Joon Kim, Yong-Jae Jung, Sang-Yong Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Dept. of Electrical Engineering Chonnam National University Korea Republic of Dept. of Electrical Engineering Chosun University Korea Republic of

This study analyzes the characteristics of shaft voltage due to rotor overhang in a wound-field rotor synchronous motor(WRSM) for electric vehicle. Recently, WRSM have gained significant attention as alternatives to permanent magnet motors. However, they exhibit disadvantages in torque density compared to permanent magnet motors, since they do not utilize permanent magnets. To solve this drawback, rotor overhang is commonly applied, but this can adversely affect voltage insulation due to end leakage flux. To verify this, models without and with rotor overhang are separately modeled to analyze shaft voltage characteristics. The results confirm the impact of rotor overhang on shaft voltage in the design of WRSM. Copyright © The Korean Institute of electrical Engineers.

关键词： Permanent magnets

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Analysis of Magnetization Characteristic Based B-H Curve Fitting According to the Operation Conditions for Traction Motor

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Transactions of the Korean Institute of electrical Engineers 2025年第2期74卷 310-315页

作者： Kim, Young-Hyun Lee, Jung-Ho Dept. of Electrical Engineering Hanbat University Korea Republic of Dept. of Electrical Engineering Daejeon Institute of Science and Technology Korea Republic of

This paper examines the demagnetization characteristics of rare earth permanent magnets (PMs) used in electric machinery. An analytical model was designed considering a controllable shape, temperature, and the external magnetic field in PMs used in the rotor of an interior permanent magnet synchronous motor (IPMSM) for driving an electric railway vehicle (ERV). The demagnetization process was analysed based on the magnetization and demagnetization theory for PM materials in computer simulation. The result of the analysis can be used to calculate the magnetization and demagnetization phenomenon according to the input B-H curves. So, this paper presents the conditions of demagnetization by the external magnetic field in the running and stopped states and proposes a simulation method that can analyse demagnetization phenomena according to each condition and be used to design the IPMSM that maximizes efficiency and torque characteristics. This was experimentally verified. Copyright © The Korean Institute of electrical Engineers.

关键词： Permanent magnets

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Development of a Reinforcement Learning-Based Control Education Platform Using Python and LW-RCP

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Transactions of the Korean Institute of electrical Engineers 2025年第1期74卷 118-126页

作者： Lee, Jongbeom Lee, Taegun Ju, Doyoon Sam Lee, Young Dept. of Electrical and Computer Engineering Inha University Incheon Korea Republic of

This paper proposes a reinforcement learning-based control education platform utilizing Python and light-weight rapid control prototyping (LW-RCP). The platform employs the Sim-to-Real technique, in which neural networks are trained in a Python-based simulation environment and applied to real systems. The trained networks are converted into a format compatible with Matlab/Simulink. The lab-built LW-RCP is used to implement a real-time controller under the Simulink environment by incorporating the converted networks. The proposed platform allows students to easily apply reinforcement learning theory to real systems, contributing to the integration of reinforcement learning control into control curriculum. The effectiveness of the proposed platform is demonstrated by implementing a reinforcement learning controller for the pendubot system. The implemented controller performs the swing-up and transition control and exhibits strong disturbance rejection and recovery properties. © 2025 Korean Institute of electrical Engineers. All rights reserved.

关键词： Python

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