Search

For the power system integrated with the doubly‐fed induction generators (DFIGs), the frequency regulation may be provided by the DFIGs in addition to the synchronous generators (SGs). With the model predictive control (MPC), the active power output of the DFIG is adjusted by predicting the system frequency with the dynamic power flow (DPF) algorithm. In this paper, the governor delay of the SGs is included to improve the accuracy of the DPF‐based prediction model. The DPF predicts the frequency response with the desired active power response of the DFIG. To reach the reference with the high accuracy and efficiency, the MPC‐based direct rotor current control is applied to adjust the active power output in coordination with the frequency regulation, forming the proposed hierarchical frequency control strategy. The mechanical transient of the DFIGs involving the shaft and pitch angle system is included in the DPF model to introduce the mechanical constraints of the DFIGs to the MPC. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents a deep neural network (DNN)‐based model to recognize fishing vessels. In Taiwan, the vast majority of small fishing vessels are not equipped with an automatic identification system (AIS). As a consequence, the staff in a fishing port administration become heavily loaded when monitoring and managing the fishing vessels accessing a port. The workload is expected to be eased using this work. For the first time in the literature, a captured fishing vessel image was converted to a 128‐dimensional embedding for recognition purposes. The presented model gave a false positive rate (FPR) as low as 1.13% and an accuracy up to 99.47% at threshold = 0.772379. Finally, all the performance metrics, namely, the true positive rate (TPR), the FPR, precision and accuracy, are actually functions of the threshold which can be specified by users to meet specific requirements. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With the rapid expansion of the scale of the power grid, the efficiency of fault diagnosis has been severely challenged by the large amount of inspection image data generated by intelligent devices such as drones and inspection robots. In order to improve the efficiency of fault diagnosis for power equipment in substations, a new method for intelligently diagnosing different types of faults in power equipment is proposed. For circuit breakers and insulators, YOLOv4 is selected as the target detection model. To improve the detection performance of the YOLOv4 model, this paper improves it: the Cross Stage Partial (CSP) structure is introduced in the Spatial Pyramid Pooling (SPP) module of the neck of the YOLOv4 model. The experimental results show that after using the optimal learning rate decay strategy, the mAP and frames per second (FPS) of the improved YOLOv4 model are better than the original YOLOv4 and PP‐YOLO model. Finally, an intelligent diagnosis terminal system for power equipment faults is developed. Through the target recognition and rapid extraction of equipment temperature, the intelligent diagnosis of thermal faults of equipment is realized. This method is especially suitable for accurate fault diagnosis of more power equipment, and has potential huge applicability in the field of power equipment diagnosis. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The fractional slot concentrated winding structure effectively solves the difficulty of low‐speed and high‐torque permanent magnet (PM) machines with a large number of poles and slots, but it also brings a wealth of magnetomotive force (MMF) harmonic. The winding function method is used to compare and analyze the stator MMF distribution and harmonic content of the fractional slot PM machines with different pole and slot combinations, and the cogging torque waveform and torque ripple are calculated by the finite element method. The influence of pole and slot combination on radial force and vibration modes of fractional slot PM machines is studied. The main vibration mode can be determined from the lowest order of radial force harmonics. The results show that in a fractional slot PM motor, the radial force is the main cause of noise and vibration, rather than the cogging torque and torque ripple. The dominant radial force is mainly produced by the interaction of rotor field harmonics and armature reaction field harmonics, and the vibration and noise will significantly increase with the decrease of the dominant vibration mode order, which largely depends on the pole and slot combination. This paper provides a certain reference for the selection of pole and slot combination in the electromagnetic design process of low speed high torque fractional slot PM motors. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, synthesis of a complex prototype filter including no inductors and its realization using Second Generation Current Conveyors (CCII's) are proposed. The proposed complex prototype filter is obtained through the frequency shifting method and an equivalent transformation. The proposed complex prototype filter includes no inductors and has fewer nodes connected to imaginary resistors than the conventional one. The proposed filter is compared with the conventional one from the viewpoints of the sensitivity characteristics and the number of the required elements. The frequency response is improved by compensating the parasitic resistors included in CCII's. The validity of the proposed method is confirmed through experiment. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

A compressed arc extinguishing device for power distribution network is developed to solve the problem of existing anti‐lightning of power distribution network transmission lines. This paper first introduces the arc extinguishing principle of the arc extinguishing device, and then designs the lightning impulse voltage test around the 10 kV transmission line. The test results show that the U50% Lightning impulse voltage of the arc extinguishing device is 112.4 kV considering the atmospheric correction factor. In order to verify the feasibility of the arc extinguishing device, the power frequency continuous current interruption test is designed. The test shows that the arc extinguishing device can extinguish the arc with a peak value of 1.131 kA in 2 ms and does not reignite in the following time. Finally, the device is applied to a 10 kV power distribution network transmission line of China Southern Power Grid. The lightning trip‐out rate of the transmission line per 100 km is reduced from 12.5 (times/year) to 1.1 (times/year), which fully verifies the feasibility of the arc extinguishing device. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In recent years, electric vehicles have developed rapidly. However, as the power source of electric vehicles, lithium battery has poor performance at low temperature, and has some problems such as reduced capacity and increased internal resistance. In this paper, two thermal environments, including natural convection condition and near‐adiabatic condition, are established, and discharge capacity test and cyclic dynamic stress test (DST) are conducted for lithium iron phosphate batteries. The actual effect of near‐adiabatic conditions is analyzed from three perspectives: battery surface temperature, terminal voltage and EIS. The results show that the near‐adiabatic working condition has almost no effect on the discharge capacity at the standard discharge current (0.5 °C) under the same temperature conditions, ranging from −15 to 25 °C. In the low‐temperature − 10 and − 15 °C cyclic dynamic stress test, compared with the natural convection working condition, the near‐adiabatic condition has a rapid rise in terminal voltage one cycle earlier, causing the cycle to stop. Also, the polarization impedance increases at least twice after the cycle under the near‐adiabatic condition. Finally, according to the analysis of variance (ANOVA), the near‐adiabatic condition has a significant effect on voltage and polarization resistance at low temperatures. Still, it has almost no effect on ohmic resistance and discharge capacity. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

An interleaved parallel high step‐up DC‐DC converter with cross‐coupled inductors for low current/voltage ripple and auto‐current sharing was proposed in this paper. This converter applies interleaved parallel input which decreases the input current ripple significantly. Due to the interleaved coupling effect of three coils of the cross‐coupled inductors, this converter can realize automatic current sharing under asymmetric distribution of duty ratio of switch control signal or coupled inductors. By using the leakage inductance of coupled inductors, the proposed DC‐DC converter has high voltage gains and small voltage stress of the main switches and output diodes. Moreover, the proposed converter solves the reverse recovery problem of the output diodes at the minimum loss. In addition, its power switches realize zero‐current turn on. In this paper, working principle is analyzed thoroughly and performance of this topological circuit is verified through a prototype with 1 kW output. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With increasing amounts of wind power generation installed, the steep fluctuation of wind power generation output, called ramp events, causes serious problems for power system operation. Controlling fluctuations is an important issue for increasing the amount of wind power generation as a wind farm (WF) in the future. The authors reported the scheduled operation method of WF using a battery energy storage system (BESS) and forecast data of wind power generation output. In this paper, the authors propose a new scheduled operation method of WF. In particular, we propose the application of deep reinforcement learning to decide the output schedule of WF. Moreover, we compare the conventional method, the reinforcement learning method, and the deep reinforcement learning method in terms of the number of ramp events. In addition, we calculate the reducing effect of the storage capacity of BESS. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Gas insulated metal enclosed switchgear (GIS) has been widely used in the world because of its compact structure and adaption to the environment. However, due to frequent operation and other reasons, GIS disconnector is prone to mechanical failure with poor contact, leading to abnormal vibration signals. In this paper, a GIS disconnector contact fault simulation platform is built to collect vibration signals in three states: normal contact, moderate poor contact and severe poor contact of disconnector contact. The Ensemble Empirical Mode Decomposition (EEMD) method is used to decompose the vibration signals, and the IMF decomposition signals are screened by Kurtosis criterion (a numerical statistic method). Finally, the vibration signal features of GIS under different conditions are obtained by reconstructing the screening signals. The results indicate that, under the normal contact, the frequency of GIS vibration signal mainly presents the distribution of 100 Hz and its integer multiple frequency component, when there is a contact defect, the high frequency component in the vibration signal spectrum increases significantly, and the tripling frequency component is present, and the amplitude of component will increase with the severity of the fault. Therefore, this study provides a theoretical reference for on‐line monitoring of GIS disconnecting switch contact fault. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Electromagnetic coil launcher is a kind of special linear motor. In order to study the trigger principles of multi‐stage electromagnetic coil launcher, based on the electromagnetic field theory, the paper deduced the field‐circuit coupling magnetic field control equations of multi‐stage synchronous inductive coil with the consideration of inter‐stage coupling, and analyzed the distribution law of magnetic lines of force, air‐gap magnetic field and current density for multi‐stage electromagnetic coil launcher. The following conclusions were reached: the largest part of magnetic flux was at the intermediate stages of multi‐stage electromagnetic coil launcher; each stage of drive coil compensates for the magnetic field of the upper coil, thus making a stable air‐gap magnetic field; the induced current density was mainly distributed in the tail and surface of the armature; according to anti‐electromagnetic shock design principle of multi‐stage electromagnetic coil launcher (namely, the requirement for small fluctuation of electromagnetic force), the basic principle of multistage trigger was summarized, that is the principle of keeping air‐gap magnetic field and induced current constant. Thus, the design foundation was laid for the operation of multistage electromagnetic coil launcher. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The problem of shafting torsional vibrations has been increasingly emerging due to the increasing capacity of turbo‐generator and the complexity of power grid. Therefore, how to reduce the torsional vibration of the turbo‐generator shaft and improve the stability of the power system has become the focus of our research. First, in order to solve the problem and alleviate the torsional vibrations of turbo‐generator shafts, this paper proposed a new shafting structure model of Double‐ended Driving and Dual‐Excited Turbo‐Generator set (DDDETG). A static excitation mode is used for the excitation of the DDDETG and the mechanical power is supplied symmetrically and synchronously from both ends of the generator rotor. Then, in order to improve the output characteristic of the generator and further suppress the torsional vibrations of the turbo‐generator shafts, combined with the nonlinear control design method of partial feedback linearization, a Multi‐Index Nonlinear Coordinated Control (MINCC) strategy for the double‐ended driving and dual‐excited turbo‐generator is proposed to ensure good dynamic and static state performances of each state in the system. Finally, the simulation results on a single‐machine infinite bus system demonstrate the effectiveness of the proposed control strategy. In addition, this paper compares the performance of DDDETG and the traditional Single‐ended Drive and Single‐Excited Turbo Generator (SDSETG), the simulation results show that the restraint effect of the DDDETG structure on shafting torsional vibrations is more obvious under the proposed control strategy. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

A novel single antenna interference cancellation algorithm of frequency shift keying (FSK) signal based on virtual multi‐input multi‐output (MIMO) is proposed in this paper. The idea is to form a virtual MIMO detection model from one‐dimensional signal through over‐sampling, then the pseudo‐Inverse matrix of transfer matrix can be used to complete demodulation. Simulation results are presented to indicate the symbol error rate performance with gaussian white noise and frequency sweeping interference of the proposed algorithm, and the performances of non‐synchronous reception and multi‐component separation are also analyzed in simulation. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The integrated power system (IPS) with pulse load involves the dynamic processes of millisecond‐level switching period and second‐level pulse period. The characteristics of this kind of multicycle dynamic process cause much difficulty in analyzing system stability. For this reason, this paper presents a multicycle coupling mathematical model of the IPS with pulse load and proposes an algorithm based on the state variables for analyzing the sensitivity of the preceding switching period which can rapidly and accurately calculate the periodic orbit and stability margin of the system. Considering a little change in the system state variables under small disturbance, this paper uses the pulse‐period average model to simplify the calculation. The simulation analysis shows that the pulse‐period average model has the same stability margin with the multicycle coupling model. The critical pulse power calculated by the above models is 5.5 and 17 kW when the constant power is 20 and 14 kW respectively, which is consistent with the time domain simulation. It may provide technical support for the stability analysis of the IPS with pulse load. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Due to the low voltage transmission (no more than 0.866) and weak anti‐interference ability of the Four‐leg Matrix Converter (4LMC), its application in grid‐connected transformation is limited. Therefore, this paper proposes a new modulation strategy of the Four‐leg Matrix Converter (4LMC) based on quasi‐Z source (QZS). Firstly, the boost principle of QZS‐4LMC and three‐dimensional space vector modulation strategy are analyzed. Secondly, on the basis of the three‐dimensional space vector modulation, the shoot‐through zero vector is inserted into the three‐dimensional space vector modulation by dividing the shoot‐through zero vector into 16 equal parts by using the shoot‐through state instead of some zero vectors, so as to obtain a new modulation strategy. Then, the simulation model of QZS‐4LMC is built in MATLAB/Simulink to analyze the control strategy. Finally, the experimental results verify the correctness and effectiveness of this new modulation strategy. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With the wide use of new energy vehicles, the research and development of high‐performance generators become more important. The claw pole machine is very suitable to be used as an automobile generator because of its unique characteristics. However, its development is limited by the disadvantage of abundant harmonic content, especially when used with fractional slot concentrated winding layout. A novel dual‐direction hybrid excitation generator (DDHEG) is proposed in this paper. It has dual 3‐phase winding layout to reduce spatial subharmonic magnet motive force (MMF). Also, it uses dual 3‐phase rectifier bridge circuit to reduce armature current, so as to reduce copper loss. It uses rotor sleeve to reduce the eddy current loss in the rotor and permanent magnets (PMs) caused by higher order harmonics. It has hybrid excitation from both directions to improve the efficiency and terminal voltage. The basic characteristics of DDHEG are analyzed by finite element analysis (FEA) method. The highlights of the proposed DDHEG are illustrated. The simulation results and experimental results reveal that the proposed DDHEG can effectively adjust the terminal voltage at different loads and reduce the harmonics and loss to a satisfied degree. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The successful application of deep learning in bridge damage diagnosis relies on the assumption that the training and test data sets obey the same distribution. However, it is difficult to obtain labeled data of damage status for a bridge in using. Otherwise, it is difficult to apply a model trained with bridge A (source domain) to diagnose bridge B (target domain) because of the distribution discrepancy of data from different working environments or bridges. In response to these problems, motivated by transfer learning, a new bridge damage diagnosis method, namely, the multichannel domain adaptation deep transfer learning based method (MDADTL), is proposed in this paper. First, a CNN based multichannel multi‐scale feature extractor is introduced to extract features. Second, a multichannel domain adaptation module based on maximum mean discrepancy (MMD) is proposed for transfer learning, so that the learned features are domain‐invariant. Through the above process, MDADTL trained with labeled data obtained in the laboratory or the testing bridge is expected to diagnose other bridges with unlabeled data. Experiments prove the effectiveness and advancement of the proposed method. This exploration will promote the practical application of deep learning in bridge damage diagnosis. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper investigates a deep learning‐based wind‐forecasting model to establish an accurate forecasting model which can support the increasing growth of wind power generation. The wind forecasting means wind speed and direction forecasting at the same time. Proposed forecasting model consists of three‐dimensional convolutional neural network and deep convolutional long short‐term memory (3DCNN‐DConvLSTM), and forecasts the wind vector which expressed as time‐sequential images. DConvLSTM model learns spatiotemporal features from time‐series image data that represent a spatial and temporal change of wind speed and direction. The forecasting model combined of 3DCNN and DConvLSTM is effective to decrease training time, and forecasting error in comparison to the DConvLSTM model. Input of the forecasting model is wind speed and direction that is expressed as an image on 2D coordinate and uses the measured data by the Automated Meteorological Data Acquisition System (AMeDAS), Japan. Forecasting accuracy with one‐hour ahead and its usefulness of the proposed forecasting model is evaluated with simulation results for four seasons that is typical of Japan climate, and demonstrated by comparison with fully connected‐LSTM (FC‐LSTM), encoder‐decoder based 3DCNN (ED‐3DCNN), DConvLSTM, and persistent models. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Real estate price prediction takes an important role in the economy that can drive up and down the stock prices and even generate disruptive economic events. Many researchers have tried to understand the pricing mechanism with machine learning techniques such as support vector machine, neural network, random forest, and AdaBoost. The boundary problem, on the other hand, makes the pricing scheme more complicated, and this trend is accelerated especially in the situation of population decline in Japan. In this paper, we discuss how we could approach the boundary problem in real estate prediction. We propose a new comprehensive inference model extending and adapting XGBoost to the domain that has the boundary conditions problem by utilizing the distance between the instances in the domain data set to make the layers of bumpy boundaries smooth for more accurate predictions and robustness against the domain data set. The experiments result showed our proposed method performed well on both hypothetical data sets and actual real estate price data. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

We have developed a 3D lightning mapping system with an array of Discone Antennas working in the medium frequency‐high frequency (MF‐HF) bands. This system is called discone antenna lightning mapping array (DALMA) and has been deployed in Hokuriku area of Japan for the 3D mapping of winter lightning. Radio waves in the MF‐HF bands are rarely used for lightning 3D mapping due to large noises in these frequency bands. However, we have demonstrated in this paper that by using a wideband antenna, 3D mapping in the MF‐HF bands can also produce satisfactory results. We have analyzed two lightning flashes with complicated features observed in the last winter. In the first flash, we have successfully mapped an upward leader triggered by a negative cloud‐to‐ground (CG) lightning from a tall tower. In the second flash, we have successfully mapped a fast downward leader preceding an intense return stroke. Finally, we have also discussed the advantages of DALMA compared with other 3D mapping systems in LF or very high frequency (VHF) bands. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In the design and production of electrical and electronic devices and circuits, it is desirable to have a calculation formula for obtaining exact inductance values, which are generally fundamental for coils. In this paper, a formula that can be applied to the exact calculations of the self‐inductance of arbitrary‐shaped single‐layer coils is presented, and its application to the several types of coils that are technologically valuable is reported. Specifically, the formula employs a new coefficient corresponding to the Nagaoka coefficient and the shape function determined by the coil. Moreover, it realizes a versatile and convenient inductance calculation method. In addition, as the formula is derived via an analytical method, it has the advantage that it can be calculated with a short‐time numerical integration. As examples of the application of the formula, rhombic, race‐track, elliptic, and regular polygonal coils were discussed, and the process and result of deriving the shape function and new coefficient for each coil were presented. Furthermore, regarding the calculation formula for regular polygonal coils, we made a regular pentagonal coil and conducted an experiment, and the validity of the calculation formula was confirmed. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Bioelectric signals such as electromyogram (EMG) and electroencephalogram (EEG) reflect human internal states and intended actions, and have therefore been applied to various types of human–machine interfaces. Such biosignal‐based interfaces are beneficial because they not only allow intuitive control of machines, but can also support persons with disabilities. In this paper, we review the recent studies on human–machine interfaces based on bioelectric signals including EMG and EEG signals. Furthermore, we introduce our recent work on the development of a brain–machine interface for domestic appliance control. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Hybrid excited machine (HEM) is a novel type of machine which has attracted much attention as it is able to adjust the flux linkage flexibly and ensure the wide speed range operation. In this paper, a novel brushless HEM with permanent magnet (PM) located in rotor is further researched. By supplying specific armature currents, the sub‐harmonic component magnetomotive force (MMF) in stator MMF would be generated and utilized to realize the brushless hybrid excited operation. Firstly, the generation principle of the sub‐harmonic component is derived analytically. Secondly, during the brushless hybrid excited operation, the influence of the stator current amplitude ratio m$$ m $$ is quantitatively studied. Thirdly, based on 2D finite element analysis (FEA), the electromagnetic performance of the brushless HEM is analyzed under different operation statuses over a wide speed range. At last, the experiment is performed based on a 6 kW brushless HEM prototype machine, and the correctness of the theoretical analysis and FEA results are validated by the test. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Missing values are ubiquitous in the nonlinear regression research, and may lead to bias and a loss of efficiency. Even in a large dataset, values drop‐out can substantially reduce the available information for analysis. In this paper, we propose an improved hybrid model to solve the nonlinear regression problem under missing data scenarios, consisting of two parts: an overcomplete winner‐take‐all (WTA) autoencoder and a multilayer gated linear network. The WTA autoencoder is trained in an adversarial training process by taking advantage of gradually renewed teacher signals and the discrimination of missing values and observed values, and is designed to play two roles: (1) to impute missing components conditioned on observed samples; (2) to generate gate control sequences. On the other hand, the multilayer gated linear network with the generated gate control sequences implements a powerful piecewise linear regression model, whose parameters are optimized by formulating a support vector regression (SVR) with a deep quasi‐linear kernel. Experimental results based on different real‐world datasets demonstrate the effectiveness of our proposed hybrid model. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, the relationship between additive particle size and properties of AgSnO2 contact materials was studied. La2O3 and Bi2O3 were selected as additives for contact materials. AgSnO2 contact materials were successfully prepared by powder metallurgy, the wettability and electrical contact properties of AgSnO2 contact materials with five particle sizes of additives were investigated. The results show that the wettability and electrical contact properties of the two contact materials are better when the particle size of additives is 500 nm and 1000 nm respectively. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Aiming at the coil offset of magnetic coupling wireless power transmission (WPT) system with the Series–Series (SS) resonance structure, in order to stabilize the transmission efficiency above 80% according to SAE J2954, Control method and variable topology design with the maximum lateral offset of 20 cm are researched on. In this paper, the mutual inductance theory is adopted to establish an equivalent circuit model of the system. The expressions of the transmission characteristics with coil offset are derived and the influence of coil offset on transmission characteristics is analyzed. According to the difference offsets, a bilateral control method with phase‐shift control on primary side and double closed‐loop control on secondary side for small offset (0, 10 cm) for constant voltage output at 200 V is adopted. In addition, a double‐sided LCC topology structure is developed for larger offset (10, 20 cm) with the maximum efficiency transmission method by parameter configuration. The simulation platform and the experiment platform are developed and the output characteristic experiments with different loads and different coupling coefficients under different offsets are finished to verify the results and provide a reference for the anti‐offset research of the system. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

About three million people die from sudden cardiac arrest (SCA) or infarction each year. It is the biggest killer on the planet and it can happen to anyone, anywhere, and anytime. Early and effective diagnosis from ECG signals can help save a large part of these SCAs. Premature ventricular contraction (PVC) detection and classification was performed with different methods. A new method of automatic classification of PVC based on a three‐bit linear interpolation error signal (LIES) is proposed in this paper. We start by a QRS detection, a nonlinear transformation and then a sliding window. This method was tested on normal and abnormal beats obtained from MIT‐BIH and AHA databases. The proposed algorithm with a sensitivity 94.8% and a specificity was 98.6%. is accurate. This algorithm is also automatic, robust, and fast. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Dissolved gas analysis in oil is an effective method for early fault diagnosis of transformers. Predicting the concentration of future characteristic gases in the transformer can assist operation and maintenance personnel in judging the operation trend of the transformer and ensure stable operation. In order to improve the prediction accuracy of dissolved gas in transformer oil based on a small number of samples, this paper proposes a VMD‐SMA‐LSSVM combined prediction model by using variational modal decomposition and least square support vector machine optimized by slime mold algorithm. First, use variational modal decomposition to decompose the gas signal. For each subsequence, a combined algorithm based on slime mold optimization and least square support vector machine is used to predict separately. Then the prediction results of each sub‐sequence are superimposed and reconstructed to obtain the final prediction value. The research results show that the prediction results obtained based on this method have better prediction effects than other models of machine learning models, other decomposition methods and optimization methods. The proposed method has good fitting characteristics when predicting seven characteristic gases, which verifies the effectiveness. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Electric vehicles (EV) are the future of mobility solutions. The EV's are driven by an electric motor with the help of a power electronic interface. The power electronic interface needs to be designed in an efficient way both in mechanical and electrical aspects. This paper proposes the concept of design, simulation and analysis of a 10 kW Multi‐Device Interleaved DC‐DC Boost Converter (MDIBC) to drive a 4 kW Induction Motor. The output DC voltage is to be maintained at a constant 400 V irrespective of the input variations. MDIBC consists of semi‐controlled switches topology excited by Phase Shifted PWM technique to reduce the ripple current in interleaving inductors. The dual loop control of the MDIBC is implemented using both PI and ANN controllers. The MATLAB/Simulink environment is used to simulate and analyze the design and control implementations. The results obtained through the implementation of ANN control proves that the control of MDIBC is simpler and is superior when compared to PI control. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Because of the crosstalk of neutral line signals in adjacent distribution transformers, the phase attribution relationship between users and transformer is not clear, which brings difficulties to the collection of users' electricity consumption information, file management, and power systems business development. Accordingly, this paper proposes a phase identification method for distribution network users based on dynamic phasor measurement, which can effectively identify all phase meter devices under the same station area. Firstly, considering that the signal on the power line contains complex frequency components and interference, the time‐varying phasor is approximated by the Taylor series. Secondly, by combining the discrete Fourier transform results of two adjacent data windows and calling the offline calculation matrix, accurate phasor measurements can be obtained. Phase shift processing is to obtain the phase angle of the bus line on the low‐voltage side of the transformer and the user at the same reporting time. In addition, the phase angle distortion caused by the impedance of the transmission line under different currents is also considered, so we make phase angle compensation to decrease the influence of the impedance of the line on the voltage phase angle. Simulation results and field experiments show that the proposed method can achieve a recognition success rate of 100% under frequency deviation conditions. Under the dynamic modulation and harmonic interference conditions, the recognition success rate could achieve 94.83% and 96.55%, respectively, it is much higher than that of the voltage correlation analysis method. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents a low‐power self‐contained overvoltage detector. Compared with conventional detectors that consist of stacked Zener diodes, the proposed structure can trim the threshold with binary codes to accommodate system‐level changes. The proposed structure enables trimming by adding a decoder, a biasing circuit, and switches in parallel with Zener diodes. The newly configured structure forms a standalone detector that can operate independently and be powered from the supply under detection with negligible current addition. The proposed structure is applicable to any high‐voltage process that contains N‐type isolation layer and needs no high‐voltage device. The proposed circuit with three bits adjustment circuit was fabricated in a 0.18 μm Bipolar‐CMOS‐DMOS (BCD) process, the overvoltage threshold can be adjusted from 8 to 38 V with post trim variation of ±2.5 V. The measured quiescent current was around 0 μA at 10 V and 28 μA at 38 V, which was comparable to the current consumption in a conventional structure with 38 V overvoltage threshold. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In Japan, the Goal of Carbon Neutral in 2050 was declared by Prime Minister in October, 2020. In order to achieve the goal, the Japanese government positioned Renewable Energy Source (RES) such as PV and wind power as 'main power supply resource' and is expanding its introduction by taking various types of countermeasures to solve the problems induced by massive integration of the RES into the grid. In recent years, the power system was damaged many times by a lot of natural disaster such as strong earthquakes, typhoons and heavy rains. The situation of the Japanese power system is drastically changing due to low demand growth, massive introduction of the RES as well as evolution of the power system reform that is introduction of power markets such as energy spot market, capacity market and balancing market. In this paper, our activities toward deregulated, smart and resilient power systems are presented. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper deals with a design of a nonlinear filter using a pseudo‐formal linearization method based on Chebyshev expansion with constant filter gains. The given nonlinear dynamic and measurement equations are piecewisely linearized by a formal linearization method using Chebyshev expansion, therefore the steady‐state Kalman filter can be applied for each linearized system. Then the resulting filters are smoothly united into a single nonlinear filter by an automatic choosing function. We demonstrate the proposed method in nonlinear systems to verify the effectiveness. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

High dynamic and low output distortion are the key requirements of power converters in high‐precision motion control. The soft‐switching auxiliary resonant snubber inverter (ARSI) has the advantage of low dead‐time effect is very suitable to be used in high‐precision applications. However, the auxiliary switches in ARSI suffer from over‐voltage problem due to the resonance between the junction capacitors of auxiliary switches and resonant inductor. Besides, all switches of natural zero‐voltage switching ('NZVS+NZVS' mode) under the light load condition brings about voltage error. Thus, the clamped auxiliary resonant snubber converter (CARSC) is proposed in this paper. Extra diodes are added, which can not only reduce the voltage stress of auxiliary switches but also save the freewheeling energy for the next commutation to improve the efficiency. Moreover, all switches of auxiliary zero‐voltage switching ('AZVS+AZVS' mode) is proposed to reduce the voltage error of 'NZVS+NZVS'. The experimental results demonstrate that the over‐voltage problem is addressed and the loss of the proposed CARSC is reduced. Besides, the high‐precision performance of CARSC is verified. The lowest THD of the output current is 0.015%. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In recent years, the sub‐/super‐synchronous oscillation (SSO) caused by grid integration of direct‐drive permanent magnet synchronous generators (D‐PMSG) has attracted wide attention. However, most of the existing stability analysis methods are either complex or cannot quantitatively analyze the influence of parameter changes on system stability. To address the problems, this paper proposes a novel stability analysis method for SSO in the D‐PMSG integrated power system based on closed‐loop transfer function poles. Firstly, the impedance modeling method was introduced to analyze the stability of the D‐PMSG power system. Then, a stability criterion was proposed based on the poles of the closed‐loop function. The proposed criterion is simple and has a clear physical background. The real part of the poles represents the damping while the imaginary part of the pole reflects the oscillation frequency. Finally, simulation results verify the accuracy and effectiveness of the proposed method. Moreover, its application in influence factors for quantitative analysis was also validated. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents a method to synthesize the multiple‐pattern frequency‐invariant conformal arrays for the first time. In this method, the extended generalized matrix pencil method is applied to obtain the optimized linear arrays. Then with the help of the quasi‐conformal transformation optics, the conformal arrays are designed by employing the inhomogeneous metamaterials. A set of numerical simulations on Taylor pattern, pencil‐beam pattern and flat‐beam pattern is shown to demonstrate the results. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In traditional power systems, the positive sequence fault component (PSFC) based criteria is often used to identify the fault directions. If the PSFC impedance angle of the inverter‐interfaced distributed generator (IIDG) is between 0 and 90°, the traditional PSFC‐based criteria will remain applicable in active distribution networks (ADNs). However, due to the diversity of the IIDG fault control mode and the uncertainty of the positive sequence voltage variation caused by faults, the PSFC impedance angle of IIDG is difficult to determine. To solve this problem, this paper proposes a two‐stage fault control scheme for IIDG. At different stages, IIDGs select different power references to meet different requirements. In the first stage, the PSFC impedance angle of IIDG is fixed to a given value, thereby maintaining the applicability of the PSFC‐based criteria in ADN. The detailed power reference calculation method of IIDG is given for this stage. In the second stage, IIDGs can select different fault control modes to support the fault voltage flexibly. By using the proposed two‐stage IIDG fault control scheme, the protection devices can accurately identify the fault direction in ADNs, which is verified by the MATLAB simulation results. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

According to the air‐gap flux density (AGFD) and the thickness of the permanent magnet (PM) in the direction of magnetization, this paper proposes a modified analytical model for the sine pole‐shaping surface‐mounted permanent magnet motor (SPMM) under parallel magnetization. The construction of the model also involves the Carter coefficient formula, the principle of magnetic‐circuit equivalence, and the distributed magnetic‐circuit method, which are used to deal with such influential factors as stator slotting, interpolar magnetic leakage, edge effect, and magnetic‐circuit saturation. Then, a finite‐element model is established to verify the analytical model through simulation. The results show that the fundamental amplitude of AGFD of the modified sine pole‐shaping motor is respectively 6.4 and 0.15% higher than that of the simplified sine pole‐shaping motor and the eccentric pole‐shaping motor, and that the total harmonic distortion of AGFD the former is respectively 67.2 and 11.1% lower than that of the latter, thereby causing an increase in average torque of the sine pole‐shaping motor and a decrease in its radial electromagnetic harmonics and torque ripple. Experiments show that both the modified analytical and finite‐element model are accurate. And, the proposed analytical model which does not need ergodic scanning as the eccentric pole‐shaping method can further optimize the electromagnetic performance of the motor. It can not only improve the motor design but also provide reference for the optimal design of high‐quality PM motors. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

As a typical cyber physical system (CPS), a smart grid should facilitate more robust integration and interoperability of information models and subsystems so that the performance of the physical system can be optimized. However, the intrinsic complexity and heterogeneity of CPS are two of the biggest obstacles to interoperation and interconnection among various information models and subsystems. In order to address the dilemma, this paper proposed a systematic, data‐centric system design approach comprehensively including data‐oriented system architecture, data resources abstraction and data‐driven mechanisms. To be specific, the autonomous decentralized system (ADS) theory is introduced to establish the data‐centric system architecture. A MQTT/MQTT‐SN‐based communication protocol, which supports not only IP‐based devices but also non‐IP devices, is proposed to meet the requirement of publish–subscribe mechanism of the ADS‐based system architecture. A data‐centric meta‐interface is proposed to formalize the data resources abstraction. A Lebesgue sampling‐based data exchange mechanism, which is proven tractable but effective, is proposed to realize the data‐driven mechanism. As user energy management system (UEMS) is an integral part of smart grid, a realistic UEMS for heating project is considered a typical case to study the performance of the proposed data‐centric system. This paper is one of the first few papers that systematically propose a systematic data‐centric system design approach for a smart grid, which is supported by aspects of system architecture, communication protocol and data exchange mechanism. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The design of external insulation for transmission lines is usually based on real‐type experiments. With the increasing voltage level of the transmission lines, in order to better design the experiments and reduce the experiment workload in the future, this paper studies the switching impulse discharge characteristics of air gaps of an ultrahigh‐voltage (UHV) transmission line. A long air gap switching impulse breakdown voltage prediction method based on the leader discharge mechanism is proposed in this paper, and a continuous leader inception model is fitted for the air gaps in UHV transmission lines by calculating the factor R of the conductor–plane gaps. The method and the model can effectively predict the air gap breakdown voltage of transmission lines. The influence of tower width and conductor structure on air gap breakdown characteristics of UHV transmission lines is studied by the method and the model proposed this paper. The results show that, as the width of the tower increases, the breakdown voltage decreases, and as the gap length increases, the influence of the tower width on the breakdown voltage decreases. The conductor structure has no obvious influence on the discharge characteristics of transmission line air gaps. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Multiple‐Input‐Multiple‐Output (MIMO) systems are widely used to enhance the system capacity in wireless communications systems. The complexity and the cost for implementing the multiple radio frequency‐chain (RF‐chain) increases proportional to the number of signal streams. Therefore, so‐called load modulating single‐RF MIMO system is one promising technology in the practical aspects. Load modulating single‐RF MIMO can utilize two‐port network for controlling the load and the desired signal can be generate by loading proper set of impedance. In this paper, the optimization method for choosing the two‐port network impedance solution that is robust to the impedance noise is proposed and the simulations are conducted to verify the robustness. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

There are various structures in the underground space, and the structures are managed as 3D data in underground geospatial information map system (UGIMS). However, there is a problem that takes a long time to load the data into a mobile app from UGIMS because the data are very large. In order to reduce the loading time of 3D data, the number of data vertices should be reduced within a range that can keep the shape of 3D object in a mobile app. In this paper, we try to reduce the number of vertices using a 3D Mesh Simplification method to reduce the loading time of data in a mobile app. The proposed method applies simplification by extracting refined vertex feature information using a deep learning encoder‐decoder based model and performing vertex clustering by grouping similar vertices together with the feature information using K‐means clustering. We were able to reduce the number of vertices by 30% compared with the previous data. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Induction machine monitoring becomes a substantial industrial need due to their constraints such as mechanical and electrical defects. Thus, many fault diagnosis tools have been employed to figure out these drawbacks. The motor current signature analysis is very developed in fault processing of induction machine fault diagnosis. In this paper, our proposed technique combines the motor current analysis and the artificial intelligence (AI) for induction motors faults recognition. Particularly, we introduce the statistical neural networks as an efficient classifier among AI techniques which provides the operating modes identification. In this context, the radial basis function neural networks and the probabilistic neural network are studied in this paper for detecting faults based on motor current analysis. In selection features, we applied the principal component analysis to transform the original database into novel uncorrelated features space. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The prognosis of time‐to‐failure for a battery can avoid the failure caused by battery performance loss. In this paper, a novel and effective algorithm is proposed to predict the remaining useful life of lithium‐ion batteries. The extended Kalman particle filter is used to improve particle degradation problem existing in standard particle filter algorithm. In order to fit battery capacity degradation, a transformed model is proposed based on double exponential empirical degradation model. It can reduce the number of parameters and the training difficulty of parameters; it also matches the form of state transfer equation. In order to improve prediction accuracy, the auto regression model is introduced to correct observation values produced by observation equation. Experimental results show that the proposed algorithm can effectively improve the accuracy of prediction compared with other algorithms. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Accurate and reliable fault location technology is essential to the stable operation of the modular multilevel converter‐high voltage direct current (MMC‐HVDC) system. Aiming at the difficulty of locating high‐resistance ground faults on MMC‐HVDC transmission lines, this paper proposes a method for fault location of transmission lines based on wavelet transform and deep belief network (DBN). First, the wavelet transform is used to decompose the original single pole ground fault voltage waveform, and then the high‐frequency and low‐frequency components obtained are used as training samples to train different DBN models, the final fault location results are obtained by superimposing the outputs of each model at last. The ±250 kV double‐ended MMC‐HVDC system model is established by using PSCAD/EMTDC, which can simulate the faults of different positions and different transition resistances. In order to verify the fault location performance of the proposed method, it is compared with two machine learning fault location methods. The results show that this method can accurately and reliably locate the single pole‐to‐ground fault of the transmission line with transition resistance of up to 10 000 Ω at low sampling frequency of 20 kHz. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In recent years, with the large‐scale access of distributed generation (DG), the line voltage of the distribution network will be offset, which will adversely affect users. This paper aims at the voltage adjustment of the distribution network. Firstly, the reactive power control methods of distributed static synchronous compensator (DSTATCOM) and electric spring (ES) are studied separately, and then a layered cooperative control strategy based on them is proposed, which combines centralized compensation and distributed compensation to stabilize the entire line voltage. The upper layer aims at optimizing the comprehensive factors including voltage offset, user comfort and cost, and applies the dynamic adaptive particle swarm optimization (DAPSO) algorithm to study the optimal scheme of voltage adjustment. The lower layer designs the control loops of the compensation devices in response to the reactive power instruction. Finally, simulation results show that the voltage of the distribution network is effectively controlled. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In recent years, human collaborative robots (HCRs) that work in the same space have attracted attention. HCRs with safety measures using a contact detection function are commercially sold. However, most safety measures for end effectors on HCRs are insufficient. In this paper, we propose a general‐purpose safety light curtain using Time of Flight (ToF) sensors for safety measure of an end effector on HCRs. The prototype safety light curtain consists of 24 pieces of ToF sensors. ToF sensors are set on a 24 polygonal base plate, and the angle is 45° to the end effector. The safety light curtain mounted on the top of the end effector can detect objects around the end effector without contact. Thus, the end effector on HCRs can avoid an unexpected collision using this safety light curtain. The light curtain will be used for various kinds of end effectors and works. Therefore, the safety of HCRs can be improved. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In both the research and engineering fields, missing data is a serious problem that cannot be overlooked. Therefore, available datasets with missing data are a challenge to be modeled by conventional global prediction models. In this paper, we propose a hybrid model consisting of an autoencoder and a gated linear network for solving the regression problem under missing value scenario. A sophisticated modeling and identifying algorithm is developed. First, an extended affinity propagation (AP) clustering algorithm is applied to obtain a self‐organized competitive net dividing the datasets into several clusters. Second, a multiple imputation tool with top p% winner‐take‐all denoising autoencoders (DAE) is introduced to realize better predictions of missing values, in which rough estimates of missing values by using the mean imputation and similarity method within the clusters are used as teacher signals of DAE. Finally, a gated linear network is designed to construct a piecewise linear regression model with interpolations in the exact same way as a support vector regression with a quasilinear kernel composed using the cluster information obtained in the AP clustering step. Based on the experiments of five datasets, our proposed method demonstrates its effectiveness and robustness compared with other traditional kernels and state‐of‐the‐art methods, even on datasets with a large percentage of missing values. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The perturbation and observation method (P&O method) is commonly used for maximum power point tracking in wind energy conversion systems. However, the selection of a suitable step size for this method is the key challenge when employing this technique. To address this, the paper presents a new method, called the FLC‐P&O method, in which a combination of fuzzy logic control (FLC) and the conventional P&O method is used. Both simulation and experimental results are presented in order to demonstrate the performance of the proposed MPPT method. Experimental testing is performed on both a laboratory wind simulator and a practical wind turbine. The results confirm that the FLC‐P&O method can provide better maximum power point tracking performance compared to the conventional P&O method. Moreover, the implementation and testing of the proposed technique on a practical wind turbine can extract more energy compared to conventional P&O. All findings are verified experimentally. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The quality of training sample is an important factor for wind speed prediction using data‐driven approaches, such as deep learning. This paper proposes a novel local predictor based on dynamic time wrapper (DTW) as training sample adaptation for wind speed prediction. After analyzing the similarity of wind speed time series using dynamic time wrapper, a local predictor is applied to improve the quality of training sample. An evaluation index is firstly proposed for estimating the quality of selected training sample. To verify the effectiveness of the proposed method, a random forest model with local predictor based on dynamic time warping (RF‐DTWLP) is applied to predict the wind speed. The simulation results demonstrate the prediction of wind speed by local predictor based on DTW has higher prediction accuracy. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]