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The penetration rate of renewable energy source generation in power systems continues to increase in recent years. However, due to the intermittent nature of renewable energy source (RES) generation, more frequency regulation resources with faster response time and larger capacities are required in the system in order to maintain the system frequency stability. Electric vehicles (EVs) can provide frequency regulation capacities to the system with their batteries when idle, but first they need to be aggregated to enter the ancillary service market for frequency regulation. In this paper, a model predictive control scheme is proposed for the EV aggregators. With the proposed control scheme, an EV aggregator can receive more payment through participation in system frequency regulation while not violating the EV users’ convenience. A prediction method based on a seasonal-autoregressive-integral-moving-average (SARIMA) model on the regulation capacity price is also implemented to further boost the EV aggregator’s payment. Simulation based on actual frequency regulation market price is conducted to examine the performance of the proposed control scheme. Compared with the simple prediction method on the regulation capacity price used in the existing literature, the proposed MPC scheme with SARIMA prediction increases the payments from the ancillary service market by 4.3% for the EV aggregator.

In this talk, chalcogenides and their applications to advanced high-performance devices such as nonvolatile memories and artificial synapses, which will play a great role in future IoT era, will be discussed from reliability, storage density, power consumption, and so on. To improve reliability, doping N or O into conventional chalcogenides with a fast operation speed was investigated with the aim of reducing the volume change upon crystallization. For ultrahigh-storage density, the multilevel storage was investigated using GeSbTe chalcogenide devices. More than 20 resistance levels with good stability were demonstrated, which resulted mainly from the gradual enlargement of crystalline region between electrodes by Joule heating. For ultralow power consumption, the phase-change device incorporated with nanostructures and a high-resistivity chalcogenide layer was systematically investigated and its heating efficiency was proved to be much higher than that of the conventional device. Finally, the chalcogenides and their applications to artificial synapses will be specially discussed.

The spatial transfer function (STF) is important for many acoustic technologies. However, it is not easy to measure STFs at multiple points. We propose a method of estimating the sound field using a small number of microphones to make it easier to measure STFs. By using equivalent sources, STFs are modeled to extrapolate the sound field including primary reflections. We investigated the effect of the arrangement of the microphone array configuration and the robustness to noise for the proposed method. It was found by simulation that the proposed method provided better estimation accuracy, especially extrapolation, than linear interpolation.

Many methods of interpolation for the spatial impulse response have been proposed to improve the measurement efficiency. In this paper, we propose a method of extrapolating the room transfer functions including higher-order reflections using a small number of microphones. The direct sound and reflected sounds are represented by the sparse equivalent source method and the image source method. Experiments using a finite-difference time-domain (FDTD) simulation show that the proposed method has smaller errors than linear interpolation at low frequencies.

This paper proposes a parallel resonant power oscillator that has the load-independent characteristic. The proposed oscillator is the first parallel-resonant power oscillator for high frequency operations. In addition, it achieves the constant output voltage and the soft switching against the load variations without any control. The feedback network for generating a driving signal does not have a resonant structure and its function is not affected by the self-oscillation frequency. Therefore, the proposed oscillator also has a self-tuning function for the resonant-filter component tolerances. Because of the above characteristics, the proposed oscillator is expected to be used in many applications such as a transmitter of the wireless power transfer systems.

The introduction of a large amount of renewable energy to the power system is causing system frequency stability issues due to the randomness of its generation. Electric vehicles (EVs) are regarded as one of the most prospective solutions for system frequency regulation. EVs, when aggregated, can join the ancillary market for frequency regulation as the demand-side response. However, the communication delay of the control signal could degrade the performance of EVs and reduce the payback. This paper proposed a novel control method to compensate for the delay of frequency control signals for EVs in a power system which applies Flat Frequency Control (FFC). The implementation cost of the proposed method is small, and the competitiveness of EVs in the frequency regulation market could be boosted with the proposed method.

In the past few years, Japanese government has decided to implement the Electricity Market Reform in Japan. According to that reform, legal unbundling will take place from 2020. Before that year, some utilities have a responsibility to keep the quality of electricity high. However, after unbundling, Transmission System Operator should ensure the ability of control by itself. Thus, we need to design the ancillary service market to ensure the quality of electricity. In this study, this new ancillary service market in Japan is proposed. In addition to that, through some case studies, the economic feasibility of the battery system is analyzed with an economic index called Net Present Value (NPV). The market optimization results show that the price of electricity procurement and that of ancillary service market behave conversely in the daytime. In one case with nuclear power plants regulated, NPV gets worse by 34 % because the price of regulation gets lower. For my future work, more detail analysis will be needed to estimate the economic feasibility more accurately.

This paper presents a thermal network model in a steady state condition for thermal management of future smart glasses. It is accomplished by disassembling the state wearing smart glasses into some parts, creating the equivalent thermal resistance circuit for each part, approximating heat generating components such as ICs to simple physical structures, setting power consumption to the heat sources, and providing heat transfer coefficients of natural convection in air. The average temperature difference between the thermal network model and a commercial thermal solver is 0.9°C when the maximum temperature is 62°C. Moreover, the thermal analysis results using the model reveal some important points for thermal design of smart glasses.

Automatic judgment of open/closed eye states from the awake background electroencephalogram (EEG) recording has been always in a high demand for neurological signal analysis and plays an important role for posterior dominant rhythm (PDR) analysis. PDR appears predominantly in occipital lobes and contains significant information for interpreting fundamental brain dysfunctions. The aim of this research is to develop a system that can properly differentiate between open and closed eye states, so that some specific segments can be chosen for PDR analysis that appears just after eye open/close. In this proposed method, a computer assisted automatic system for eye-opening/closing detection from awake background EEG has been developed. EEG data that was visually inspected by a qualified electroencephalographer (EEGer) was taken into account for separating open and closed eye states by creating parameters for each states. Later using those parameters and conditions, new equations were developed and implemented for accurate detection of open/closed eye. Based on the automatic detection result, some specific segments that appears just after eye open/close will be selected for PDR analysis. Organization, frequency, amplitude and their asymmetry these characteristics will be taken into account for PDR analysis.

This paper presents thermal countermeasure methods for glass wearable devices by effectively using the structural features of the devices. We show the effectiveness of the main measures, i.e., the use of Al for frame material, a wider rim, and placements on both sides to divide the device. We also show the effects of other measures, e.g., the use of a side heatsink and front center placement of the device. Experimental results demonstrate that the main measures can reduce the temperature rise that glass wearable devices generally produce by 28%.

Wearable devices are evolving at a rapid pace. Many researchers are studying wireless power transfer technologies. Functions beyond current smartphone capabilities must be realized in wearable devices that are smaller than smartphones. Heat due to power consumption causes both circuit malfunctions and low-temperature burns to users. In this paper, we propose thermal management methods for future wrist wearable devices with higher performance. The methods include the reconstruction of a 3D IC, the heatspreader within a device, and the built-in heatspreader and surface fin heatsink of a belt. Our experiments with a FEM-based 3D thermal solver demonstrate that the new proposed methods can achieve 44.9% reduction in the gradient coefficients of °C /W.

In designing an induction heating system, the load part with magnetic field has been considered by converted to the L-R series equivalent circuit or the model with transformer. These circuit models don't correspond to the physical phenomenon of the load part, and the design guidelines of the system have not been established yet. Although there are methods of repeating electromagnetic field simulation to each application and obtaining a converged solution by trial and error, it takes lots of time and is inefficient. This paper proposes an equivalent circuit corresponding to the magnetic flux of IH load part, in order to clarify it. Moreover, a coupled analysis of electric circuit and IH load is carried out. This enables more detailed analysis of an IH load, and it was derived that high power utilization rate is realized in the parallel resonance mode by the simulation and the experiment.

This paper shows the application of a genetic algorithm (GA) for component selection to improve the accuracy of a kNN (k-Nearest Neighbor) method when using it for breast cancer prognosis. Our GA uses the best chromosome (member) in a generation to produce new ones. The probabilities of crossover and mutation have not fixed values, instead they depend on the evaluation of the chromosomes involved in the generation of new ones. The GA determines the best components that must be used in prognosis by the kNN method. This method for the UCI breast cancer data usually gives a 76% average accuracy, but we have found a combination of only sixteen components that rises the average accuracy of kNN to 79%.

We present a modeling approach to the economic assessment of flexible resources in the power generation mix, taking the renewable-forecasting error distribution into account. The model can analyze explicitly the production cost impact of renewable-power forecasting accuracy. A supposed power system with large-scale renewable integration in Japan in 2030 is taken as an example. The results show that the greater the forecasting error, the more that flexible resources such gas-fired power generation and energy storage systems are needed in the daily power-generation mix and the less that base power generation units are utilized. This has an impact on the yearly power generation cost as well. The unit power generation cost, in which only fossil-fuel-fired and nuclear-powered generation units are included, increases by 16–53% compared to that of a particular accurate forecast, depending on the degree of renewable forecasting error.

Due to large-scale renewable energy installation, frequency regulation is becoming more important and more difficult in power system. Battery energy storage system (BESS) is the one solution to this problem. It is assumed that effectiveness of installing BESS into power systems depends on its generation mix and control systems of frequency regulation. However, the optimal size of BESS has been discussed without consideration of supply-demand control in the power system, especially under the largescale renewable energy installation. If variable generations, such as photovoltaic power (PV) generation and wind turbine (WT) generation are largely integrated into the grid, load frequency control (LFC) is required to compensate not only short-term fluctuation but long-term fluctuation which is conventionally dealt with by economic dispatching control (EDC) because of the uncertainty of the uncertainty of the PV and WT output. Therefore, the way of LFC and EDC should be revised under such circumstances, and then, the value of BESS should be analyzed in consideration of this change of control system. First of all, the new coordination method of EDC and LFC is proposed to deal with the large-scale installation of PV and WT generation. Next, the effectiveness of the proposed method in terms of frequency regulation is verified by numerical simulation. Moreover, the optimal size of BESS is analyzed based on the proposed EDC and LFC systems. Numerical simulation shows the effectiveness of the proposed EDC and LFC system and the cost benefits of the use of BESS for LFC.

The total number of students, who graduate from all the colleges of National Institute of Technology (NIT) Japan, is over 10,000 every year. The college graduates are highly evaluated from the industrial world for over 50 years. In order for the students to acquire high skills, the curriculum in NIT should be combined lectures with experiments and/or practical trainings. However the skills of experiments and practical trainings are implicit know-how up to now. Therefore, we make the skills be explicit knowledge for improvement of skills. In this paper, we propose a method to visualize the skills, and we introduce an approach to decide the level of achievement of experiments and practical training skills. This approach is almost based on original lab manuals, but in order to evaluate of ICT and Software skills, we attempt to use "i Competency Dictionary". In order to propose our methods, we checked and evaluated over 300 lab manuals. The experimental skill-sheets and the evaluation-sheets that are the vital part of our methods, have been developed using the learning items, which derived from those manuals in manually. It is possible to visualize each student's skills by defining evaluation standard with the sheets. The evaluation standard is one of the tools to guide students to their final target effectively and clearly. Using our methods, the level of achievement and the motivation of students' skills will be improved drastically in the experimental subjects and practical trainings.

In the next-generation grid, distributed energy management system will play a significant role, cooperating with the whole power infrastructure. The residential sector has the potential for making full use of the advantages of new equipment of power generation and storage. We inspected empirical data from houses which have both fuel cells and photovoltaics in Japan and based on this built simulation model of residential energy system. Under an assumed environment after deregulation of electric power, we verified the effect of interchanging electricity on CO 2 mitigation in the model. In addition, this paper proposes introducing home batteries, which are expected to be useful for peak shift and during a power failure. We analyzed how residential appliances worked from the perspective of self-interested customers in our model by using the mixed integer programming.

This paper presents a comparison study of various motors for application to an electric vehicle (EV) and the potentiality of a ferrite magnet motor as a candidate for rare-earth-less motor for an EV. The rotor shape of the proposed ferrite magnet motor is based on a spoke-type shape. Further, we developed two types of prototypes: one has a large magnetic torque equivalent to a conventional rare-earth permanent magnet motor for an equal volume, and another has a wide variable-speed range suitable for an EV.

Recently, stepping motors have been widely used in the field of industrial manufacturing for high-speed position control over minute distances. Furthermore, fast and precise position control at finer angles is strongly required. However, a few problems hinder the satisfaction of these requirements when using a stepping motor. For example, the motor becomes expensive and its size increases, and the number of poles increases structurally. To overcome these problems, a surface permanent magnet synchronous motor (SPMSM) is commonly employed for high-speed position control. In this paper, a rapid current profile is designed by using a new current profiling method based on the angular impulse of acceleration and deceleration, and the SPMSM is operated by proposed current profile. In the experimental results, it is confirmed that faster and more precise and stable position control is achieved by the proposed method.

In this study we examine 12 geographically distributed wind farms in Tohoku area in east Japan to improve our understanding of variable wind output in the point of output fluctuation. Wind power outputs are converted to frequency domain using FFT (Fast Fourier Transform). In frequency domain, we use Power Spectrum Analysis (PSA) to estimate correlation characteristics between wind farms in different frequency domains. Furthermore, we evaluate the degree of smoothing effect of solar power over a certain region and compare with wind power analysis to understand the difference between these two major forces of nature. Our examination of data shows clearly that the smoothing effect of distributed wind farms can contribute largely to its output fluctuation. We also discuss the expected impacts on power system stability, in the event of high level wind power penetration.

A polarization coded holographic memory is demonstrated. Writing and reading characteristics are examined through numerical calculations and experiments. The polarization state of the readout signal is influenced by the ratio of intensity and polarization gratings.