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The transformer is a core device of the power system, and it is generally considered that the aging of insulating paper is important to the transformer. The aging process of insulating paper is the degradation process of cellulose. If it can be detected regularly, the aging of oil–paper insulating systems can be monitored conveniently. 5‐hydroxymethylfurfural is an important chemical substance produced by cellulose decomposition. It has broad prospects because of its many advantages. The oil–paper insulation system was thermally aged at 80, 90, 100, and 110 °C to measure the concentration of 5‐hydroxymethylfurfural on insulating paper and in transformer oil. In this paper, the concentration of 5‐hydroxymethylfurfural is detected by high‐performance liquid chromatography. The linear correlation coefficient of this method can reach 0.99, and the minimum detected concentration can be reduced to 10 µg/l. Experiments show that the concentration of 5‐hydroxymethylfurfural increases with the aging time, and when degree of polymerization (DP) decreased, the concentration of 5‐hydroxymethylfurfural increased. The correlation coefficient is greater than 0.92, which shows that there is an experimental relationship between the concentration of 5‐hydroxymethylfurfural and DP. The parameters of regression curves are different at different temperatures, but in actual operation, the temperature is low and remains stable. Therefore, 5‐hydroxymethylfurfural is expected to be a new indicator of the aging degree of oil–paper insulation system. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this letter, a disposable micropower source was developed by integrating a microbial fuel cell (MFC) in filter paper. The paper‐based MFC could harvest electrical energy generated by Escherichia coli during the metabolic process. The air‐dried biofilm anode was activated by water for on‐demand electricity generation. This study aimed to optimize the anodic and cathodic materials for maximization of the MFC performance. The concentration of activated carbon powder in the anode and potassium ferricyanide in the cathode were optimized. The paper‐based MFC with the optimum anode and cathode generated a maximum power density of 8.4 µW/cm2. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The anode electrode plays a vital role in the performance of microbial fuel cells (MFCs) because it has the function of collecting electrons generated by microorganisms living in the anode chamber. In this letter, activated carbon papers fabricated based on ZnCl2‐activated carbon (ZAC) or steam‐activated carbon (SAC) were used as the anodic materials. Escherichia coli was used as an electrogenic bacterium in a two‐chamber MFC. This study compared the performance of ZAC and SAC in the anode. X concentrations (X = 10, 20, and 40 wt%) of ZAC or SAC in the anodes were investigated. The ZAC‐based anode outperformed the SAC‐based anode in terms of MFC‐generated power density. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Adding a Battery Energy Storage System (BESS) in the vicinity of renewable energy sources is a feasible solution to overcome the inherent negative impact caused by their random power fluctuating problems. Power conversion system performs as an interface between the battery packs and grid. The control method of power conversion system is essential to BESS. Finite Control Set Model Predictive Control (FCS‐MPC) is favorable to be chosen as the core control method for grid‐injected current regulation in such a system due to its outstanding benefactions, including fast dynamics, multiobjective optimization and simple implementations. Hence, this paper presents a FCS‐MPC with active damping feature for an Inductor(L) Capacitor(C) Inductor(L) (LCL)‐filter‐based power conversion system first. However, it is also well known that the practical effect of model predictive control significantly relies on the accuracy of mathematical model embedded within the controller. Parametric mismatch of the model tends to generate a prediction error, leading to a deterioration of the power quality of power conversion system or even instability issues furthermore. Therefore, this paper proposes an additional model correction strategy based on a comprehensive on‐line analysis on the difference between predictive and real value of respective voltage or current signals during the ever‐lasting several grid cycles to eliminate the influence of parametric mismatch. Simulation of an LCL‐filter‐based power conversion system is carried out to verify the validity of the theoretical analysis and control method in this paper. Finally, experimental results obtained from a down‐scaled prototype are provided to confirm the feasibility of the overall control strategy. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Data mining extracts useful knowledge from big data. The extracted knowledge in data mining is often represented by association rules, and association rules can be also used for classification. However, when association rules for classification (called class association rules) are extracted, a large number of data with class labels are necessary, which requires a lot of cost of manual annotation. Therefore, this paper proposes a semisupervised learning method for rule extraction, where a small number of labeled data and a large number of unlabeled data are used to efficiently extract class association rules. In detail, this paper proposes two types of classifiers using class association rules: one is a classifier based on semisupervised learning, and the other is that based on both supervised and semisupervised learning. The second method builds several classifiers using supervised learning and semisupervised learning and the classification results of these classifiers are integrated to make the final decision. As an association rule mining method, Genetic Network Programming (GNP), which is one of the graph‐based evolutionary algorithms is used. GNP has shown distinguished classification ability in some applications; therefore, one of the other objectives of this paper is to extend the applicability of GNP to data mining based on semisupervised learning. In the experiments, the classification accuracy is evaluated using some benchmark datasets by comparing with some conventional methods. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper presents a new fault location technique based on the fundamental frequency positive sequence fault components, featuring robustness to the operating state of the prefault system and fault path resistance. Using the fundamental frequency positive sequence fault components, the technique described in this paper does not require the user to know the fault phases and fault type in advance or use a line zero sequence parameter, which is not only difficult to obtain but is also affected by soil resistivity and thus may be variable. In addition, based on the fault components protection principle, the method is inherently unaffected by the operating state of the prefault system. Accurate transmission lines' fault location is important for expediting their repair or reducing outage times, so the proposed technique could improve the quality and security of the electricity supply. This paper describes the characteristics of the proposed technique and assesses its performance by using the PSCAD/EMTDC simulation. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In recent years, the power quality problem has become more complicated in power grids because of the extensive usage of power electronics and multisource multitransformation features. The method, based on physical characteristics such as time domain, frequency domain and transform domain, is facing challenges in terms of adaptability, algorithm efficiency and accuracy for the recognition of complex disturbance recognition. The bidirectional long short‐term memory network is an algorithm in deep learning. It is based on data for characterization learning, which can effectively overcome the problem of information loss and generalization ability of physical methods. Moreover, it has the characteristics of memory, which can simultaneously consider historical information and future information and can better learn data features with time series characteristics. Aiming at the transient voltage sag time series data, this paper proposes a recognition method of the voltage sag causes based on the bidirectional long short‐term memory network's extraction eigenvalue, the full‐connection layer's high‐dimensional feature extraction and the Softmax network layer's classification. The experiment uses simulation data and measured data to prove that the model has good recognition ability and good antinoise performance in the recognition of voltage sag causes and can be reliably applied in practical engineering. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Very‐short‐term load forecasting (VSTLF) predicts the load from minutes to 1‐hour timescale. Effective forecasting is important for in‐day scheduling of the power systems. In this paper, a VSTLF method based on empirical mode decomposition and deep neural network is proposed. The extreme point span is used to determine a proper empirical modal number, so as to successfully decompose the load data into different timescales, based on which the deep‐neural‐network‐based forecasting model is established. The accuracy of the proposed method is verified by the testing results in this paper. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper proposes a novel model for the analysis and design of a virtual synchronous generator (VSGs). To enhance the stability in power systems with distributed generators, the concept of VSG has been proposed. The VSG is designed based on the swing equation of a synchronous generator ignoring the dynamics of current flowing through an interconnection reactor. However, responses obtained with actual system are different from those calculated from the model. It implies that the VSG cannot be correctly analyzed and designed by using the conventional model. This paper constructs an accurate VSG model considering the dynamics of current. Moreover, we address the stability analysis of the VSG and reveal a relation between the parameters of VSG controller and the rated power/energy capacity of energy storage systems equipped with the VSG based on the proposed model. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper deals with load extrapolation methods and algorithms for the estimation of the energy efficiency of induction motors, starting from the electrical data generally available after parameter identification. The main aim of this paper is to help the readers move from the theoretical analysis to the experimental verification, which is suitable to be included in its own testing. For this reason, step‐by‐step algorithms are included in this paper. The first part deals with the determination of energy efficiency based on an original load extrapolation. Finally, experimental verification of the high‐power and high‐voltage induction motors is provided. Comparison between the values of the in–out method and load extrapolation method confirms the validity of the proposed algorithms. Compared to the direct in–out method, the error of the load extrapolation proposed in this paper is less than 1%.The load extrapolation method is mainly used for the high‐voltage and high‐power asynchronous motor. The high‐voltage and high‐power motor can be used to drive a low‐power motor to achieve coaxial twin trawling in the absence of a suitable power supply and matched load. The energy efficiency of a high‐power motor under different loads are measured and estimated using a mathematical fitting method. The estimated energy efficiency curves in the whole load range can be used to evaluate the high‐power and high‐voltage induction motor. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper reports an easy‐to‐fabricate micro battery that can be directly printed on a bio‐sensing device such as an immunoreaction‐based disposable complementary metal oxide semiconductor bio‐sensing chip. The printed Mg and AgCl films were used as both cathode and anode materials, while the inspection solution for the bio‐sensing was utilized as an electrolyte, which simplified the structure of the battery. A micro battery fabricated on the printed circuit board, in which each electrode size was 3 × 3 mm2, could generate an open circuit voltage as high as 1.58 V, a maximum power as high as 1.4 mW and a total stored energy as high as 400 mJ. Wireless sensor test platforms self‐powered by the developed on‐chip battery successfully worked in a 0.14 M NaCl solution, and digital data could be successfully transferred using both optical and capacitive coupling methods. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In the frequency domain semi‐airborne electromagnetic detection method, the receiving signal from the coil sensor contains a quantity of noise. In order to improve signal‐to‐noise ratio (SNR), a novel data processing method based on orthogonal phase‐locked amplification is proposed in this paper. By using GPS second‐pulse technology, the proposed method has good real‐time performance and high SNR. The amplitude and phase of the receiving signals can be easily resolved by simple arithmetical operation and stored in real time, which avoids the large error in the short‐term window signal. The proposed method can provide higher resolution in subsurface anomaly and better noise suppression capability. The measured results show that the proposed method amplitude error is less than 3%, and the phase error is less than 0.6° under the condition of double white noise. Noise suppression capability is 10 times of the existing system and resolution is up to 25 times. The smaller anomaly can be reflected more accurately. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper is concerned with a finite‐time nonlinear stochastic optimal control problem with input saturation as a hard constraint on the control input. The stochastic Hamilton‐Jacobi‐Bellman (SHJB) equation associated with this problem is derived, and a concrete solution method is also presented by extending an iteration framework of path integral stochastic optimal control. This is the first result that provides an optimal feedback control rigorously satisfying the saturation constraint as a solution to the SHJB equation. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Recently, multiperson tracking across non‐overlapping camera views is gaining increasing attention in the video surveillance field due to its importance for public security. Most existing methods find a correspondence of person images individually across each pair of adjacent two cameras. However, in such a naive approach, redundant matching where one of the person images is selected for the matching pair for several times, often occurs. It leads to tracking failure. To overcome this problem, in this paper, by considering the matching problem as an instance of the "marriage problem" that is well known in Economics, we propose a simultaneous image matching method for multiple persons based on the stable marriage algorithm. We confirmed that the proposed method outperforms some of the existing state‐of‐the‐art methods on several well‐known public datasets. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

As a mathematical model to represent the dynamics of a plant to be controlled, the T‐S fuzzy model is widely used in the control system design. In order to facilitate controller design, it sometimes needs suitable coordinate transformations of the T‐S fuzzy model. Subsequently, some questions arise: (1) can local systems in different fuzzy rules perform different coordinate transformations? if yes, then (2) is the transformed T‐S fuzzy model equivalent to its original one? In answering these questions, this paper at first gives a brief review on the T‐S fuzzy model to catch the real meaning of local systems in the context of the whole system expressed by the T‐S fuzzy model. Then, bearing controller design in mind it discusses the equivalence between pre‐ and transformed systems in various types of T‐S fuzzy models. Finally, in order to share the benefits from the results discussed in this paper, a controller design based on an affine T‐S fuzzy model is provided. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this paper, ablation polymer was studied to improve the thermal interrupting performance of an SF6 gas circuit breaker. One kind of polymer was used as the ablation polymer on the basis of the specific constraint conditions for SF6 gas circuit breakers, such as not including hydrogen, and its ablation characteristics were investigated. Furthermore, the dominant factor of that polymer ablation was discussed by comparing ablated mass characteristics between the ablation polymer and polytetrafluoroethylene, which is widely used as the nozzle material of an SF6 gas circuit breaker. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The modular multilevel AC/AC converter topology in Y configuration, which is called Y‐MMC, suitable for fractional frequency transmission system is proposed in this paper. Y‐MMC can directly connect two three‐phase AC systems of different frequencies and voltage amplitudes with only six equivalent branches, and it has satisfying performance in power quality and characteristics. Y‐MMC enjoys a simple and symmetrical structure with no circulating current problem. The detailed topology and operating principle of Y‐MMC are addressed in this paper. The frequency‐decoupled mathematical model of the Y‐MMC system is deduced. Corresponding control scheme is thoroughly designed, including the inner loop current control, the outer loop control, the individual‐balancing control, and frequency leakage suppression control. The paper also lays emphasis on the optimization of reactive power distribution between the main branches and the assistant branches of Y‐MMC. The validity of the Y‐MMC topology and the effectiveness of the proposed control scheme are verified by the simulation results in MATLAB/Simulink. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The recognition of human motion posture is of great values in the field of sports. In this paper, inertial sensor technology is employed to recognize four postures including dribbling, passing, catching, and shooting in basketball. The data are collected by four nine‐axis inertial sensors worn on the arm. The time domain and frequency domain features are extracted after the process of smoothing and normalizing. Then 30 eigenvectors are obtained by dimensionality reduction of principal component analysis (PCA), and the support vector machine (SVM) method is used for posture recognition. The experimental results show that after PCA dimensionality reduction, the recognition accuracy of the features as the SVM input is significantly high. Compared with the recognition accuracy of back propagation neural network (BPNN) (85.4%), the average recognition accuracy of SVM is 96%, which verifies the reliability of the method proposed in this study. This research proves the effectiveness of sensor technology in basketball posture recognition, which can provide a reliable guidance for basketball training. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

With the development of global renewable energy, DC transmission and DC power distribution technology have been applied on a large scale, and the requirements for DC power quality (PQ) are more stringent. Evaluating DC PQ reasonably and effectively has become a research hotspot at this stage. In this paper, a comprehensive analysis for various indexes of DC PQ is conducted to obtain a unified parameter for describing the characteristics of PQ from an overall perspective. First, weight values of PQ indexes are calculated by combining fuzzy analytic hierarchy process (FAHP) and the improved entropy weight method. FAHP can satisfy the consistency without the consistency test, and the improved entropy weight method is an objective weighting method that can effectively avoid the preference of subjective weighting method. Then, based on a triangular fuzzy function, the membership degree is obtained. Finally, a fuzzy comprehensive evaluation is made. An example analysis is carried out with the data provided by the Gree photovoltaic direct‐driven inverter multi‐variable refrigerant flow system to show the validity of the proposed method for evaluating DC PQ. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In‐wheel motors (IWMs) are one of the most important key technologies to be used by electric vehicles, hybrid electric vehicles, and fuel cell vehicles. To meet the limitations of the space within the wheel rim, unsprung mass, and drive without a multispeed transmission, IWMs need to be designed to simultaneously have high torque per volume and power per mass and wide high‐efficiency operation region. In addition, it is obligatory to meet the requirements of torque output capacity, speed capacity, torque ripple, peak efficiency, power output capacity, etc. In this paper, a direct‐drive surface‐mounted permanent magnet in‐wheel motor (DSPMIWM) is synthetically optimized. Above design demands are accounted for simultaneously by selecting some of them as the design objectives and setting the others as constraints. Firstly, simplified design equations of the DSPMIWM, which can reduce the number of design variables, are established. The size parameters of the DSPMIWM are classified by constants, indirect design parameters, and direct design parameters. The direct design parameters are selected as optimal design variables. Then, a synthetically optimal design of the DSPMIWM is executed by employing the Kriging method combined with the Latin Hypercube sampling and Genetic Algorithm. Compared with an existing mature design, the torque per volume, power per mass, and high‐efficiency operation region of the studied IWM are still improved while all constraints are met. Finally, the effectiveness of the proposed synthetically optimal design procedure is verified by finite element analysis. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The demand for highly efficient motors has risen because of the increase in the number of hybrid electrical vehicles and electrical vehicles. Eddy current loss in the motors, which is generated by leakage of magnetic flux interlinked with the winding, is one factor that leads to the decrease in efficiency. Therefore, in this paper, by attaching magnetic composite materials to the winding of the interior permanent magnet (IPM) motor, we attempted to reduce the eddy current loss due to the leakage of magnetic flux of the rotor while maintaining the torque. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this paper, a novel economic analysis for multiterminal voltage‐source converter high‐voltage direct current (MTDC) systems with wind farms is developed. Both the reinforcement and operation methods of an MTDC system are determined hierarchically in the proposed approach. Based on these methods, not only wind power transmission but also the MTDC system is capable of contributing to the power transmission among alternating current (AC) grids in cases of low wind power production cases. As a consequence, the economic benefits produced by the MTDC system can be increased. This paper also focuses on the sensitivity analysis of small‐signal stability constraints on the developed approach. It is demonstrated that the system for wind power transmission without any MTDC systems is exposed to instability, which is solved by the proposed method. On top of that, the small‐signal stability improvement effect of the MTDC system is analyzed from the economic viewpoint. Under strict small‐signal stability constraints, the economic benefits obtained by the MTDC system increase. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In order to improve the economic benefit of household photovoltaic (PV) system users under time‐of‐use (TOU) price and enhance their ability to cut peaks and fill valleys for main grid, an optimization method based on dynamic tie‐line transmission power is proposed in this paper, which can be applied to different weather conditions. First, an optimization scheduling model of economic benefit for a grid‐connected PV system is put forward, with the final revenue of user as the objective function. Under the TOU price policy, this model fully considers economic factors such as energy income, energy cost, government subsidy, system maintenance cost, etc. Moreover, the dynamic tie‐line transmission power is taken as the optimization variable, and the improved chaotic simulated annealing particle swarm optimization algorithm is used to solve the optimization problem. Finally, a typical household grid‐connected PV system is taken as study case, and convincing results are obtained to verify the proposed model and optimal strategy. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper proposes a novel integrated solution for real‐time power quality (PQ) disturbance analysis. Traditionally, the recognitions are based on the feature extraction and are implemented offline or on the advanced reduced instruction set computer machine/digital signal processor platforms. In this paper, the optimized deep belief network (DBN) analyzes the PQ signals by learning knowledge from raw data of signals directly, which maximizes the features of original signals, and runs on an embedded parallel computing platform (EPCP). In simulation studies, eight types of common PQ disturbances are divided into 17 classes of data frame models according to the PQ disturbances that may occur during a fixed period of time. These samples of data frame models are utilized to train and optimize the DBNs on a central server. Compared with the existing classifiers, the simulation results demonstrate that the proposed approach has higher accuracy and stronger robustness. Then, the optimized DBN is sent to EPCP, and the previous DBN model is updated. The EPCPs are used to recognize the signals of PQ disturbances from a real time digital system (RTDS). The proposed integrated solution has excellent performance regarding accuracy but is time consuming. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

As more and more renewable generation resources are integrated into the smart grid, they are likely to cause supply–demand imbalance such as overgeneration due to their uncertain and variable nature, resulting in poor power quality and unreliable power delivery. To balance overgeneration, this paper presents a collaborative control strategy of thermostatically controlled appliances in the timescale of minutes. The proposed strategy includes four parts: state awareness, real‐time analysis, scientific decision‐making, and precise execution. A responsive task‐type model is designed to identify the executable task type of an appliance in the state awareness part. A multiobjective 0–1 programming method is used to solve the optimal control combination in the scientific decision‐making part. And a thermostat set‐point control rule is used to generate the control signals of appliances in the precise execution part. In order to illustrate the advantage of the proposed strategy, four case studies are designed, and the advantage of the strategy is validated by the simulation results of the case studies. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency and quality of a permanent magnet synchronous generator (PMSG) for vehicles, the parametric model and finite‐element model of the generator are established. The influence of seven structure parameters on three performance parameters is obtained by simulation analysis, and the sensitivity values of the parameters are given. According to the simulation results, it can be seen that the structure design parameters have higher degrees of freedom, and the relationship among parameters is complex. Using three multidimensional functions as test functions, the precision of the fitting method proposed in this paper is compared with that of the traditional methods. The test results show that, compared with the other methods, maximum projection (MaxPro) sampling and the Kriging method can select as fewer samples as possible while guaranteeing the higher fitting precision. Then, the Kriging surrogate model, which reflects the nonlinear relationship between the structure and performance parameters, is established, and the prediction precision of the model is verified. Based on the surrogate model, the performance of the generator with three performance parameters as optimized objects is optimized by use of elitist nondominated sorting genetic algorithm (NSGA‐II), and a Pareto optimal solution set of the objective function is obtained. Three of the optimal solutions are selected for finite‐element verification. The results show that the Kriging surrogate model can provide better global and local prediction between input and output variables. It is further proved that the samples obtained by MaxPro sampling can fully reflect the characteristics of the design space. The optimized objects can be weighed according to the optimal decision based on the results of multiobjective optimization through the Kriging surrogate model. The effectiveness of the optimization method is verified. It is of great engineering significance to improve the performance of generators, and the optimal model obtained by this method has an important reference value for prototype trial production. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

As an effective countermeasure against lightning faults on transmission lines, transmission line arresters (TLAs) have been installed. However, they have been damaged by lightning strokes with large electric charges, particularly in winter. Through the investigation of damaged TLAs, we found that some of the internal zinc oxide elements had been damaged despite the undamaged appearance of the arresters. Therefore, it is necessary to detect TLAs with damaged zinc oxide elements as soon as possible to prevent lightning faults with arrester failures. As reported in this paper, we have improved the previous method of detecting TLAs with damaged zinc oxide elements using the frequency characteristics of equivalent series resistance and evaluated the accuracy of the improved method. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Aiming at the problem of limited fault data and data expiration of distribution transformers, a transfer learning fault diagnosis model of the distribution transformer considering multi‐factor situation evolution is proposed in this paper. First, the state quantities that influence the distribution transformer operation are constructed, and fuzzy binary quantification is used for the state quantities. The association between the state quantities and the fault is explored by the fuzzy Apriori algorithm, and the key state variables that induce the transformer fault are extracted. The Tanimoto coefficient is introduced for the limited fault data of distribution transformers, and the effective auxiliary fault data is transferred to the target distribution transformer. On this basis, the fault diagnosis model based on information transfer is proposed. A health index is introduced to describe the distribution health levels, and the auxiliary fault data in different health levels is transferred because data has expired. On this basis, the fault diagnosis model for data expiration is proposed. The weights of the target and auxiliary fault data in the above model are iteratively solved by using the TrAdaBoost algorithm. Finally, an example analysis is carried on the basis of distribution transformer fault data, and the simulation results show that the fault diagnosis accuracy of the model is high and that it has stronger generalization ability than traditional diagnosis models. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Discharge voltage prediction of engineering gap configurations is a great challenge for external insulation design in high‐voltage engineering. This paper presents an air gap discharge voltage prediction model based on the support vector regression (SVR). A series of features are defined on the shortest interelectrode path of an air gap, and they are extracted from the electric field calculation results using the finite element method. These electric field features are considered as the input parameters of the SVR‐based model, and the output is the air gap discharge voltage. The genetic algorithm is used for parameter optimization of the SVR model. Trained by a few experimental data of the Institute of Electrical and Electronics Engineers standard rod–rod gaps, this model is applied to predict the standard lightning impulse flashover voltages of parallel gaps for insulator strings under different gap configurations. The prediction results coincide well with the experimental data collected from previous publications. The mean absolute percentage error of the eight test samples is within 4.07%, which is acceptable for engineering applications. The SVR‐based model may be helpful to guide the structure design and insulation coordination of parallel gaps and insulator strings, thus reducing the required full‐scale tests. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The characteristic impedance value of the overhead line is different from that of the underground cable. Existing traveling wave‐based fault location methods for mixed power transmission systems have setbacks including location error caused by wave velocity and difficulty in detecting wave arrival time. In order to solve these problems, the increase of available information from different locations by installing wire‐based sensors along the power line is a feasible solution. In this paper, a traveling wave‐based fault location system, which is based on the current data measured at the midpoint of the overhead line and the joint point, is introduced. The data at these two locations are measured by the wire‐based current sensor we designed. The whole transmission line system is divided by these two sensors into three segments. The first step of this proposed method is to record the postfault current data at the two measuring devices. Second, by comparing the amplitudes and polarities of the current at these two measurement points, the faulty segment can be identified. Finally, postfault wave propagation paths are ascertained; the accurate velocity values of the waves in the overhead line and underground cable are obtained; and then, the fault point is located without the need of time synchronization. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Misalignment is a problem faced when electric vehicles work under the dynamic wireless charging mode using segmented transmitting coils. One kind of coil misalignment is coil lateral offset. In order to improve lateral offset tolerance, transfer efficiency and output power need to be stabilized. In this paper, first, the circuit model of a wireless power transfer (WPT) system is analyzed, from which mutual inductance is the major factor of the transfer efficiency decline caused by coils' lateral offset. The mutual inductance of two parallel square coils with lateral offset is analyzed. With the length and width of the transmitting coil being optimally designed according to the mutual inductance analysis, the mutual inductance of coils with lateral offset is optimized, and thus, transfer efficiency can be stabilized, and the system lateral offset tolerance is preliminarily improved. Moreover, in order to further enhance the lateral offset tolerance, the secondary‐only resonant series–series (S–S) topology is adopted to stabilize the system output power. Finally, the optimal design with stabilized transfer efficiency is verified by the finite element simulation and the experiment with coils being scaled down. Due to the limitation of experimental conditions, the stability of output power is verified by simulation. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Fault protection is a major issue in the development of multiterminal high‐voltage direct current (HVDC) system based on voltage‐source converter. Owing to the rapid increase in fault current under DC faults, protection requires a fast fault detection method to isolate the fault current. However, the selectivity and reliability of the fast protection scheme should be primarily guaranteed. Therefore, a new protection strategy based on modulus maximum under wavelet transform is proposed in this paper. Fault detection and discrimination are achieved using single‐end signals of fault current. The external and internal faults can be discriminated via local information. The reliability and robustness of the proposed scheme against potential factors are verified. Numerous simulation cases are performed in PSCAD/EMTDC under different fault scenarios, and signal data are analyzed in MATLAB to demonstrate the effectiveness of the proposed fault protection scheme. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

When a transformer is being energized, a large magnetic inrush current flows depending upon the closing phase angle of the circuit breaker and the residual magnetic flux in the iron core. One of the suppressing methods of the magnetic inrush current is to control the closing phase angle of the circuit breaker. Controlled switching has been used for no‐load transformer energization until now. However, the transformer may be switched under an on‐load state. In this case, a large magnetic inrush current will flow. To suppress the inrush current by using controlled switching, the information of the residual magnetic flux in the iron core is needed. The residual magnetic flux for no‐load transformers has been investigated. However, the residual magnetic flux for on‐load transformers was not investigated. In this paper, the residual magnetic flux for an on‐load transformer was investigated by experiments and calculations. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Gene ontology annotation is known to be a very complicated multilabel classification task, and the hierarchical multilabel classification (HMC) approaches with local classifiers have been shown to be effective for the task. In a traditional HMC method, a set of hierarchically organized simple local classifiers are usually used, each of which for one hierarchical level separately. In this paper, we propose a novel hierarchical multilabel classifier implementing the whole set of hierarchically organized local classifiers in one deep convolution neural network (CNN) model with multiple heads and multiple ends (MHME). The proposed MHME CNN model consists of three parts: the body part of a deep CNN model shared by different local classifiers for feature extraction and feature mapping; the multiend part of a set of autoencoders performing feature fusion transforming the input vectors of different local classifiers to feature vectors with the same length so as to share the feature mapping part; and the multihead part of a set of linear multilabel classifiers. Furthermore, a sophisticated recursive algorithm is designed to train the MHME CNN model to realize the functions of a set of hierarchically organized local classifiers. In this way, by sharing a deep CNN with multiple local classifiers, we are able to construct more powerful local classifiers for each level with limited training samples, and to achieve better classification performance. Experiment results on various benchmark datasets show that the proposed deep CNN‐based model has better performance than the state‐of‐the‐art traditional models. Moreover, it gives rather good performance even under a transfer learning. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The present paper describes the design and evaluation results of a sensor for measuring body pressure and sweat volume using conductive fibers. Pressure ulcers that develop from staying in the same posture for a long time are a serious problem in nursing care. The main causes of pressure ulcers are blockage of capillaries due to body pressure and skin structure degeneration due to sweat. To quantify the causes of pressure ulcers, Mengeng Liu et al. have developed a sensitive (14.4 kPa−1) pressure sensor using conductive fibers with excellent cleaning and flexibility. However, a conductive fiber sensor that focuses on both body pressure and sweating has not yet been established. Therefore, in the present research, we made a sensor that can measure body pressure and sweat volume with only fibers and evaluated the performance of the proposed method. The fabricated sensor is a parallel plate capacitive sensor made of two conductive fibers that sandwich an insulating cloth. When body pressure is applied, the distance between two parallel conductive fibers increases, and when sweat is applied, the dielectric constant of the fabric changes, increasing the capacitance of the sensor. Capacitance change can be evaluated by peak holding the output of the AC bridge circuit. Through an evaluation experiment using a vise and a constant temperature and constant‐humidity chamber, the fabricated sensor was confirmed to be able to measure a pressure change of 10 mmHg and a humidity change of 10%. This sensor, which can evaluate pressure and humidity (amount of adhering water) at the same time and at low cost, contributes to reducing the burden of nursing care. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Semisupervised classification aims to construct a classifier by making use of both labeled data and unlabeled data. This paper proposes a semisupervised classifier based on a piecewise linear regression model implemented by using a gated linear network. The semisupervised classifier is constructed in two steps. In the first step, instead of estimating the break points of a piecewise linear model directly, a label‐guided autoencoder‐based semisupervised gating mechanism is designed to generate binary gate control signals to realize the partitioning. In the second step, the piecewise linear model is first transformed into linear regression form, and the linear parameters are then optimized globally by a Laplacian regularized least squares (LapRLS) algorithm using a kernel function comprising the gate control signals obtained in the first step. Moreover, the composed kernel function is used as a better similarity function for the graph construction. As a result, we capture data manifold from both labeled and unlabeled data, and the data manifold is ingeniously incorporated into both the kernel and the graph Laplacian in LapRLS. Numerical experiments on various real‐world datasets exhibit the effectiveness of the proposed method. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this paper, we propose a semicentralized voltage control method utilizing past voltage measurements obtained with sensors in a distribution network (DN) to improve the voltage control performance of a single‐step voltage regulator (SVR). In this method, the SVR basically performs autonomous voltage control referring to the control parameter, the reference voltage, but the parameter is updated with a specific interval via communication. To determine a time series of the reference voltage using the past voltage measurements, the simple averaging method and the probabilistic weighting method are considered. The effect of these methods on the voltage control performance is evaluated with a power flow simulation using a realistic 6.6 kV DN model with photovoltaic systems. The results show that the proposed semicentralized SVR control with these advanced parameter‐updating methods dramatically mitigate voltage violation compared to the conventional SVR operation in which the constant reference voltage is used for 1 year. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Nonlinear dynamic behaviors such as the bifurcation and chaos of DC‐DC converters with switching constant power load are studied in this paper. Based on the consideration of constant power load switching, a discrete iterative mapping model of the system including the switching process is established, and its Lyapunov exponent spectrum algorithm is derived. The main procedure of the algorithm is as follows: Firstly, the system is divided into six smooth segments, and the zero‐time discontinuous mapping of the load and mode switching is introduced. Secondly, the local mapping of each smooth segment and the zero‐time discontinuous mapping of the switching phase are used to construct the composite Poincaré mapping of the system by the chain rule, and then the discrete iterative mapping model of the system is established. Finally, the Lyapunov exponent spectrum algorithm of the system is derived based on the model to determine the type of nonlinear dynamic behavior of the system. This algorithm overcomes the problems of the existing methods, which lead to inaccurate results due to the neglect of the switching process, and achieves the purpose of accurately describing the dynamic characteristics of power electronic circuits. The simulation and experimental results have verified the validity of the proposed model and algorithm. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This paper reviews various sensor technologies with application in automobiles and robots. Several automotive sensors have been developed using the micro‐electromechanical systems (MEMS) technology. The technologies related to combustion pressure sensors, yaw rate sensors, acceleration sensors, and optical scanners are described here. The combustion pressure sensors are used for engine control, while the yaw rate sensors of quartz and silicon crystals and the acceleration sensors are applied for vehicle motion control. Optical scanners are developed for autonomous driving. Several automotive sensors have been significantly reduced in size and cost, and their performance has been improved dramatically by MEMS technology. The inertial force‐sensing system with yaw rate and acceleration sensors enabled the assistant and partner robots to stand on two legs, walk, or invert and move on two wheels. Because the robots are required to have a variety of sensors, a nerve‐net sensing system was developed. This sensing system has three layers: the host, relay, and sensor nodes. The sensor node is a special large‐scale integration called a 'nerve‐net chip.' A triaxial force tactile sensor integrated with the nerve‐net chip was developed as a 2.8‐mm square surface‐mountable chip. A force and thermal tactile sensor was also developed, which detected heat flows and discriminated the materials of contacted objects. The heat flow sensor was thinned with thin‐film technology. The sensor technologies will be used for eco cars and autonomous vehicles. Next‐generation robots are also supported by several automotive sensor technologies. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In our previous study, we presented a method of estimating the color of amber using the red, green, and blue (RGB) color space and the hue, saturation, and value (HSV) color space. In particular, the method estimates the color of amber on a target image consisting of four colors (yellow, brown, black, and amber with an outer cover [AOC]). However, because of the existence of amber with a partially exposed outer cover (APEOC), the estimated accuracy of AOCs was 57.1%. In addition, the size of the amber used in the study was approximately 1–2 cm, considering improvements in versatility. It is also necessary to estimate the color of amber with a size of approximately 3–5 mm, which is even smaller. However, because the color of brown amber is similar to yellow amber, the estimation accuracy of amber having a size of less than 1 cm, using conventional methods, was 62.1%. Therefore, in this paper, we propose a method that switches the estimation method in terms of color features and amber of sizes ranging between 1 and 2 cm and those of 1 cm or less. Based on the experimental results of the proposed method, estimation accuracies of 94.1% for 185 ambers with a size of 1–2 cm and 96.0% for 125 ambers with a less than 1 cm were achieved. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Manually monitoring the safety of personnel working on high‐voltage lines is difficult and unreliable. To overcome this problem, this paper proposes an online high‐voltage live safety monitoring and early warning system based on spatial cross‐border prevention. To develop the proposed system, following analysis of high‐voltage typical live working modes and the minimum approach distance, we divide the safe operation space and use a time‐of‐flight (TOF) depth camera to measure the live working distance in real time. This enables us realize safety early warning by detecting the boundary crossing and intrusion of the safe operation space. Subsequently, we analyze the ambient light and noise that affect the imaging quality of the TOF camera, evaluate the confidence of the depth image pixels, and apply a purpose‐designed adaptive filter guided by a confidence map to repair the depth images. The results of field experiments conducted verify that the proposed system accurate and reliable of this system through field experiments. Compared with manual observations, the system can significantly improve the effectiveness of real‐time live working safety monitoring, and can effectively prevent the occurrence of live working personal injury accidents. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

With the increased number of installations of distributed photovoltaic (PV) systems within electricity distribution systems, power flow analysis is required to handle multiple PV systems. At present, PV systems are equipped with a local control function (LCF). The conventional algorithm is then applied for power flow analysis with the LCF of each PV system, where the power output of LCF of each PV system is calculated and used in the power flow calculation. The conventional algorithm is terminated when the voltage at each iteration of the power flow algorithm is converged. However, the conventional algorithm inevitably requires a lengthy calculation. This paper proposes a power flow algorithm that applies the Newton–Raphson technique to handle multiple PV systems with an LCF for a faster calculation. The LCF is approximated to have a continuous characteristic. The developed power flow algorithm can be used for a three‐phase unbalanced distribution system and its effectiveness was demonstrated in a modified 19‐node distribution system. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Certain applications of power electronics for railway vehicle traction systems and fixed installations are reviewed and future possibilities considering technical and social trends around railway industry are mentioned in this paper. First of all, some particularities of railway load and traction power supply system are summarized as problems to be solved by power electronics technologies. Such technologies for fixed installations and vehicle traction systems are presented and future possibilities for higher performance, minimization, and improved resilience of railway system are pointed out. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In recent years, a rapid spread of residential photovoltaic power systems (PVs) causes voltage imbalance in distribution systems. For this reason, it has become difficult to control voltage in distribution systems to within the allowable range. Therefore, the authors have proposed a system for suppressing the voltage unbalance using single‐phase static capacitors (SCs). The purpose of the system (SC system) is to suppress voltage imbalance by controlling single‐phase SCs in each phase, and its effect has been confirmed by the previous authors' study. On the other hand, as a result of analyzing the voltage measured on some distribution lines, the authors found that it is not necessary to control single‐phase SCs in each phase because the voltage imbalance hardly changes throughout a day. In this paper, an alternative method for suppressing the voltage imbalance by constantly installing single‐phase SCs on distribution lines is proposed in order to realize at a lower cost than the previous SC system. In addition, the authors verify the effect of the method on the actual distribution lines. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In our previous study, we carried out confidence interval estimation of next‐day photovoltaic (PV) output with just‐in‐time modeling hour by hour. When the target reliability is high in particular, the width of the confidence interval becomes large certainly. Therefore, in this paper, based on behavior of the measured PV output in the morning of the targeted day, we predict of PV output transition in the estimated confidence interval in the afternoon. The proposed method, which is consistently based on black box modeling, enables us to easily and effectively narrow the confidence interval width, i.e., sharpness, of PV output. Some numerical examples, which demonstrate the effectiveness of the proposed method, are also reported. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In recent years, hard disk drives (HDDs) have been primarily used in data servers. At the data servers, the head positioning accuracy of control systems is influenced by various external vibrations. The deterioration of the positioning accuracy causes degradation of the digital data transfer rate in the data server. To compensate for the external vibrations in the head positioning systems of HDDs, in this research, the authors developed an adaptive feedforward control (AFC) with a gain learning function. The proposed AFC can update the characteristics of the control system to compensate for the external vibrations in real‐time. This paper reports on the results of experiments in which the proposed AFC is employed to compensate for the speaker‐induced vibration due to buzzing of the data server, implemented to act as notification for any issues occurring in the system. It was noted that the proposed AFC can compensate for the vibrations caused by the buzzing. Moreover, the control parameters updated in real‐time can be used to sense the occurrence of buzzing in the system. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

A magnetically driven arc does not advance smoothly between parallel electrodes with edges. The anode spot stagnates on the anode surface when the arc column and cathode spot move forward. According to experimental results, when the arc column moves closer to the anode surface, or a high‐temperature gas comes into contact with the anode, a new anode spot appears and electrical breakdown occurs. Meanwhile, the original anode spot disappears. It is well known as the re‐strike phenomenon. Also, it can be observed using a bandpass filter (520 nm) that a large amount of Cu vapor is generated whenever a new anode spot appears. Because the Cu vapor considerably increases the arc's radiative emission and has a dissimilar effect on the gas's electrical conductivity at different concentrations, a three‐dimensional electromagnetic thermal fluid simulation program that considers the metal vapor from the electrodes is proposed in this paper. Based on the experimental figures, it is able to simulate the re‐strike process by controlling the electrical conductivity of the control volume at the anode surface. In addition, the physical properties of the arc plasma, the original anode spot area, and the re‐strike point area are analyzed, in order to elucidate the occurrence conditions of the re‐strike phenomenon. The results show that the arc form is affected by the electrode jets, which leads to an increase in the electric field density between the re‐strike point and the arc column, thereby causing the re‐strike phenomenon to occur. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Since it can be difficult to directly estimate the temperature of permanent magnets (PM) in high‐density permanent magnet motor rotors, this paper proposes a method based on lumped parameter thermal networks (LPTN) for online estimation of PM temperature. Firstly, a parameter model is established that contains a four‐node thermal network model and a loss model. For the online estimation, an extended Kalman filter algorithm with fading factor is used to dynamically update the thermal network parameter model in order to estimate the PM temperature. The simulation and experimental results show that the parameter model can quickly converge to a value that is close to the true value. Therefore, this online estimation method for PM temperature can accurately monitor the PM temperature online without increasing the required motor hardware; thus not affecting the motor operation. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Controller performance assessment (CPA) is capable to evaluate the controller performance and has been widely used in industrial processes. In the existing research studies, CPA usually assumes that the feedback signals are the actual process outputs without considering the measurement noise. Minimum variance (MV)‐based CPA is the most common method for controller performance evaluation. In this paper, the effect of measurement noise is considered in the feedback signals of the MV‐based CPA. The dynamic data reconciliation (DDR) is incorporated in the MV‐based CPA (DDR‐MV‐CPA) to decrease the effect of measurement noise on CPA. The effectiveness of the proposed DDR‐MV‐CPA method is demonstrated via theoretical derivation, simulations, and experimental comparisons. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

To achieve current balance between parallel‐connected insulated gate bipolar transistors (IGBTs) of a DC microgrid hybrid circuit breaker (DC MHCB), it is a simple and effective method to add impedance in parallel‐connected IGBTs, but this will also affect the vacuum arc commutation of the DC MHCB. The focus of this paper is the effects of adding impedance on vacuum arc commutation characteristics. By constructing a simplified model of vacuum arc commutation in the case of adding impedance, the effect of adding impedance on vacuum arc commutation is theoretically derived. The test circuit of vacuum arc commutation is established, and the effect of adding impedance on vacuum arc commutation in the presence or absence of the externally applied transverse magnetic field (TMF) is investigated using the electrical measure. The theoretical formula and related formulas of the effect of adding impedance on the duration of vacuum arc commutation are obtained. A method combining adding impedance and an externally applied TMF is proposed. The constraint formula for adding impedance during vacuum arc commutation is obtained. The main factors that limit the value of adding impedance are obtained. Research on the effect of adding impedance on vacuum arc commutation characteristics can provide theoretical guidance for the application of the method of adding impedance in a DC MHCB. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]