In this paper, the nonconforming infinite edge element method with a reference line is developed for fast magnetic field analysis of infinitely long models such as railway system. The proposed method is effective for reducing calculation burden while retaining computational accuracy even in far region.

In Japan, low thermal insulation performance in existing houses is a considerable issue that may lead to health problems. Therefore, it is necessary to acquire technologies and knowledge regarding thermal insulation renovation. On the other hand, with the spread of photovoltaic panels, urban scale energy management and self-consumption have become important. The purpose of this study is to introduce a net-zero energy house which was designed, built, and analyzed by the team of Waseda University and Shibaura Institute of Technology in the ENEMANE HOUSE 2017 competition. The team proposed a renovation method which insert highly insulated walls into the existing structure, creating not only highly insulated areas but also non-insulated areas called "loggias." By opening and closing the windows of the loggia according to the season, it functions as a passive system and enables residents' behavioural adaptation to the environment. On the other hand, to aim for self-consumption and leveling of reverse power flow, a heat pump water heater and a storage battery were operated according to solar radiation prediction. Actual measurements confirmed the implementation and effect of this operational method. Moreover, the energy consumption was greatly reduced, while thermal comfort was maintained by thermal insulation and efficient equipment introduction. (C) 2019 The Authors. Published by Elsevier B.V.

Recently, the deep learning technology attracts much attention in various industrial fields. In our previous research, we developed an Encoder-Decoder precisely reproducing the optimization process of conventional optimization method, that is, the level-set method which is one of the gradient methods, by means of Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM). The developed method enables us to implement high speed search of solutions, which means the possibility of better and effective optimization starting with various initial shapes. This method can deal with only the initial shape as design parameter for optimization. Thus, it is necessary to re-train the Encoder-Decoder when the design conditions change, e.g., the displacement of permanent magnet. To overcome this drawback, we have developed a novel network structure to incorporate the design conditions into the training data. Finally, to confirm the validity of the proposed method, we evaluate its calculation time and computational accuracy by using a magnetic circuit design model.

In the design optimization of electric machine, we ordinarily derive the objective physical quantities, e.g., the shape of the investigated model as design variables, by using numerical method such as the finite element method with the analysis conditions. In recent years, the representation learning using Deep Learning much attracts attention because it can acquire the features of data as a distributed representation and reproduce corresponding data. In this paper, utilizing machine learning technology, we propose an application of Conditional Variational Auto-Encoder (CVAE) to reproduce the more adequate shape of magnetic materials, i.e., design variables, corresponding to the intended magnetic energy, i.e., objective function values.

The finite element analysis (FEA) of magnetic field generally requires a lot of calculation time. Especially, design optimization methods such as the level-set method with FEA result in large computational effort to find better solution. In this paper, we propose a novel method of precisely and quickly reproducing the conventional optimization steps by means of Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM). The developed method enables us to implement high speed search of solution, which means the possibility of effective optimization with various initial conditions for better solution. Finally, we evaluate calculation time and computational accuracy of the proposed method by using a magnetic circuit design model.

Purpose: The purpose of this paper is to solve efficiently the topology optimization (TO) in time domain problem with magnetic nonlinearity requiring a large-scale finite element mesh. As an actual application model, the proposed method is applied to induction heating apparatus. Design/methodology/approach: To achieve TO with efficient computation time, a multistage topology is proposed. This method can derive the optimum structure by repeatedly reducing the design domain and regenerating the finite element mesh. Findings: It was clarified that the structure derived from proposed method can be similar to the structure derived from the conventional method, and that the computation time can be made more efficient by parameter tuning of the frequency and volume constraint value. In addition, as a time domain induction heating apparatus problem of an actual application model, an optimum topology considering magnetic nonlinearity was derived from the proposed method. Originality/value: Whereas the entire design domain must be filled with small triangles in the conventional TO method, the proposed method requires finer mesh division of only the stepwise-reduced design domain. Therefore, the mesh scale is reduced, and there is a possibility that the computation time for TO can be shortened.

<p>Saving energy in the residential is required under the influence of global warming and electricity shortage caused by natural disaster in Japan. For the purpose of promoting zero energy house, "ENEMANE HOUSE 2017", a competition of Zero-Energy House was held. This paper shows the overview of the building and equipment planning, and also the evaluation of thermal environment and energy in the zero energy house which the consortium of Waseda University and Shibaura Institute of Technology proposed in the competition. This zero energy house demonstrates a method of renovation of housing using low-insulated outer wall of an existing industrialized house. The aim of the facility planning was not only the compatibility of energy-saving and comfort but also the increase in self-consumption of surplus power. </p>

Recently, from the viewpoint of vibration and noise reductions, torque ripple reduction of motor-equipped electrical machines is the need of the hour. The authors have already proposed to improve torque characteristics of a synchronous reluctance motor using the topology optimization method. The evaluated rotor structure succeeded in substantial torque ripple reduction, but the cause for this reduction was unknown. In this paper, we investigate the reason for torque ripple reduction using the improved rotor structure of the motor by a topology optimization method known as R-SLP, by comparing it to the reference model using finite element analysis. A calculation method is proposed to analyze the circumferential magnetic force density of spatial and time harmonic orders using the magnetic density in the air gap. By focusing on the time order at which the torque waveform was evaluated, we estimate which circumferential magnetic force density orders affect torque ripple reduction. Then, we clarify the reason for torque ripple reduction to examine the influence of local shape of rotor structure using 12th time-harmonic magnetic fields. As a result, the modified flux barrier rotor structure is obtained, which further reduces the torque ripple in comparison to the previous structure.

Recently, from the viewpoint of vibration and noise reductions, torque ripple reduction of motor-equipped electrical machines is the need of the hour. The authors have already proposed to improve torque characteristics of a synchronous reluctance motor using the topology optimization method. The evaluated rotor structure succeeded in substantial torque ripple reduction, but the cause for this reduction was unknown. In this paper, we investigate the reason for torque ripple reduction using the improved rotor structure of the motor by a topology optimization method known as R-SLP, by comparing it to the reference model using finite element analysis. A calculation method is proposed to analyze the circumferential magnetic force density of spatial and time harmonic orders using the magnetic density in the air gap. By focusing on the time order at which the torque waveform was evaluated, we estimate which circumferential magnetic force density orders affect torque ripple reduction. Then, we clarify the reason for torque ripple reduction to examine the influence of local shape of rotor structure using 12 th time-harmonic magnetic fields. As a result, the modified flux barrier rotor structure is obtained, which further reduces the torque ripple in comparison to the previous structure.

Because of the increasing promotion of renewable energy such as photovoltaic (PV) panels in Japanese houses, the voltage increase and frequency adjustment of a city electrical distribution network sys-tem will be of concern. Therefore, self-consuming surplus electricity and leveling the reverse power flow is important in terms of reducing the smart grid network load and reducing the peak load of the smart grid network. The aim of this study was to acquire knowledge regarding methods of self-consuming surplus power as well as leveling the reverse power flow. An equipment operation method, termed “schedule control,” was proposed that changes the operational time of a heat pump water heater and the charging time of a storage battery according to solar radiation prediction. Because PV power fluctuates depending on weather and time zone, this method helps in self-consuming as much PV power generation as possible. By actual measurement and simulation results, it was confirmed that the schedule control of the heat pump water heater and storage battery was useful in self-consuming surplus power and leveling reverse power flow.

Purpose: Shape optimization using the level-set method is one of the most effective automatic design tools for electromagnetic machines. While level-set method has the advantage of being able to suppress unfeasible shape, it has a weakness of being unable to handle complex topology changes such as perforate at material region. With this method, it is only possible to define simple connected topology, and it is difficult to determine the optimal shape which has holes. Therefore, it is important to efficiently expand the searching area in the optimization process with level-set method. Design/methodology/approach: In this paper, the authors introduce the newly defined hole sensitivity which is based on concept of topological derivatives, and combine it with level-set method to effectively create holes in the search process. Furthermore, they consider a variable bandwidth of gray scale, which indicates the transition width between air and magnetic body and combine it with the hole creation method described above. With these methods, the authors aim to expand the searching area in comparison with the conventional level-set method. Findings: As a result of applying the proposed methods to a magnetic shielding problem, the multi-layered shielding which effectively reduces the magnetic flux in the target area, is successfully produced. Originality/value: The proposed methods enable us to effectively create a hole and to expand the searching area in the topology optimization process unlike in the case of conventional level-set method.

Purpose: The purpose of this paper is the improvement of topology optimization. The scope of the paper is focused on the speedup of optimization. Design/methodology/approach: To achieve the speedup, the method of moving asymptotes (MMA) with constrained condition of level set function is applied instead of solving the Hamilton–Jacobi equation. Findings: The acceleration of convergence of objective function is drastically improved by the implementation of MMA. Originality/value: Normally, the level set method is solved through the Hamilton–Jacobi equation. However, the possibility of introducing mathematical programming is clear by the constrained condition. Furthermore, the proposed method is suitable for efficiently solving the topology optimization problem in the magnetic field system.

The introduction of photovoltaic power systems is being significantly promoted. This paper proposes the implementation of a distributed energy management framework linking demand-side management systems and supply-side management system under the given time-of-use pricing program for efficient utilization of photovoltaic power outputs; each system implements a consistent management flow composed of forecasting, operation planning, and control steps. In our framework, demand-side systems distributed in the electric distribution network manage individual energy consumption to reduce the residential operating cost by utilizing the residential photovoltaic power system and controllable energy appliances so as not to inconvenience residents. On the other hand, the supply-side system utilizes photovoltaic power maximally while maintaining the quality of electric power. The effectiveness of the proposed framework is evaluated on the basis of an actual Japanese distribution network simulation model from both the supply-side and demand-side viewpoints.

Because a synchronous reluctance motor (SynRM) does not require permanent magnets, its industrial applications focus on lowering manufacturing costs. However, the SynRM has disadvantages. It experiences a lower average torque and oscillations derived from torque ripple compared to a permanent magnet-based motor. Therefore, the improvement of torque characteristics is investigated using topology optimization (TO) method which allows a greater variety of rotor structure than the shape optimization technique and does not require the concrete initial structure. Although the level set method is well known among TO methods, the smoothed-heaviside-function-based TO implemented by method of moving asymptotes is more suitable due to the feasibility of implementing the physical structure and the convergence speed. In this paper, the reasonable structure of rotor core in SynRM is investigated using TO method to improve the torque characteristic.

A low-voltage regulator (LVR) is investigated as a countermeasure for voltage violation caused by the integration of photovoltaic (PV) systems in distribution systems. To achieve appropriate voltage control by the LVR, the appropriate control parameters need to be determined. We have proposed schemes to determine the appropriate control parameters using PV forecast profiles. In a previous work, the control parameters were determined on the basis of one-scenario PV forecast, which derives one forecast value in each time step. However, voltage violation could not be avoided by this method in a time step with a large forecast error. In this paper, we propose a method for determining the voltage control parameters of the LVR based on the forecast interval of the PV outputs to quantitatively consider the PV forecast error. The numerical simulation results show that the proposed method can reduce the amount of voltage deviation compared with the conventional method.

We present a novel practical design optimization for the primary core in an induction heating roll, which significantly affects the heating performance. To optimize the 3D eddy current field problem within an acceptable CPU time, we effectively combine 2D magnetostatic optimization and 3D coupled magnetic-thermal FEM. For the 2D optimization, we adopt the level-set method, which has an advantage of being able to derive a feasible shape. However, the disadvantage is that its result occasionally falls into a local optimal solution. To overcome this disadvantage, we propose conducting the initial conceptual design with the linear level-set method before using the nonlinear level-set method to expand the search domain. Furthermore, we incorporate the parallelized move-limit strategy into the level-set method to prevent the configuration from undergoing excess deformation by the operation for the area constraint. Finally, the 2D optimal shape obtained using our new level-set method is converted into a straight line cross-sectional configuration to improve manufacturability, and the final 3D design is created with slits. The final 3D design obtained as a result of the 3D FEM successfully improves both the heating speed and temperature uniformity on the surface of the heating part under the same conditions of input AC current and material volume.

Photovoltaic(PV) power generation systems have gained much attention against a background of energy and environmental problems. However, the output of PV system depends on climate conditions. Therefore, a mass introduction of PV results in the power quality deterioration in the distribution system. To overcome the difficulty, it is effective to introduce Low Voltage Regulator(LVR) to the distribution system. However, the application of LVR brings a new problem, i.e., a control delay for activating the tap after detecting the fluctuation. With this background, to provide more useful predictive information in advance, this paper deals with a novel prediction interval estimation method of 10 second PV fluctuation with two-dimensional kernel density estimation. We also carry out the prediction by using several different methods for comparison, e.g., the conventional method with one-dimensional kernel density estimation and the application of various smoothing methods to this conventional method. Finally, some numerical results, which demonstrate the effectiveness of the proposed method on the basis of several indexes, are also presented.

In a distribution line, power system control and power equipment investment are planned based on a measured power system current. However, recently the mass introduction of photovoltaic (PV) make it difficult for us to precisely measure the demand curve that is a current consumed by electrical equipment because the reversal power flow from PV systems is superposed. Therefore, the prediction of demand curves of distribution line is indispensable for power system management. In addition, it is also necessary to estimate the reliability of the predicted values as well as predicted current itself. In this paper, we propose the estimation method of the prediction interval that is the index of reliability based on the past demand curve database. The feature of the proposed method based on Just-In-Time (JIT) modeling make it possible for us to accurately estimate the prediction interval by the normalized database of demand curve. In this paper, some numerical examples are presented, which demonstrate the effectiveness of the proposed method. (C) 2017 Wiley Periodicals, Inc.

It is very important to design electrical machineries with high efficiency from the point of view of saving energy. Therefore, topology optimization (TO) is occasionally used as a design method for improving the performance of electrical machinery under the reasonable constraints. Because TO can achieve a design with much higher degree of freedom in terms of structure, there is a possibility for deriving the novel structure which would be quite different from the conventional structure. In this paper, topology optimization using sequential linear programming using move limit based on adaptive relaxation is applied to two models. The magnetic shielding, in which there are many local minima, is firstly employed as firstly benchmarking for the performance evaluation among several mathematical programming methods. Secondly, induction heating model is defined in 2-D axisymmetric field. In this model, the magnetic energy stored in the magnetic body is maximized under the constraint on the volume of magnetic body. Furthermore, the influence of the location of the design domain on the solutions is investigated.

Topology optimization is one of the mathematical methods for finding the optimal structure of electrical machinery. Because topology optimization can make a design with much higher degree of freedom in terms of structure than other optimization methods, there is a possibility for achieving a completely new shape that is not limited to the conventional model. The optimized structure is strongly dependent on the characteristic function which is an explicit function with respect to the design variable. To identify the practical topology in which the gray scale elements do not exist as much as possible, Heaviside function is suitable to suppress the generation of gray scale. In this paper, Heaviside function is applied to the IH equipment problem, and both influences of the difference between single and multiple design domain and the difference of the constraint value of the magnetic body volume on optimal solution are particularly investigated.

Topology optimization (TO) has advantages over shape optimization; for example, the design space is wider and the degrees of the shape freedom is larger. The convergence characteristic in the conventional level set (LS) method is slow because of the limitation of the time step size that is used for solving the simplified Hamilton-Jacobi equation, which is normally defined as the width of one finite element in the design domain. To overcome this difficulty, convergence acceleration using the method of moving asymptotes is investigated. The performance of the proposed method is compared with the conventional LS method for a 3-D TO problem regarding the magnetic shielding and an interior permanent magnet motor in a 3-D nonlinear magnetostatic field.

This paper proposes a voltage control method during service restoration in the distribution networks with photovoltaic (PV) generator systems. In the current distribution automation system (DAS) process in Japan, voltage dips and surges occur during service restoration because PVs are disconnected simultaneously after a fault and subsequently reconnected after service restoration. However, in the current DAS, voltage regulators such as an on-load tap changer (OLTC) and step voltage regulators (SVRs) are not controlled during service restoration. The proposed DAS estimates the voltage in a distribution network during service restoration, and it controls the tap position of OLTC and/or SVRs according to the predicted voltage. The numerical simulation results using a real-world distribution system model on a real map and PV output profiles derived by actual square kilometer solar radiation data will be shown. Those results indicate that the proposed DAS prevents voltage deviation that occurs as long as the current DAS is used. The results also show high spatial resolution PV output data are needed to prevent voltage deviation absolutely. (C) 2016 American Society of Civil Engineers.

Topology optimization (TO) is an attractive design tools for electrical machinery. In particular, the level-set-based TO has been investigated enthusiastically. In this paper, a level-set-based topology optimization method supported by the method of moving asymptotes is proposed to realize fast convergence. The performance of the proposed method is verified in comparison with the conventional level-set-based method, which is composed of both gradient-based-correction and regularization.

It is difficult to analyze magnetostatic field problems with multiply connected domains by the direct boundary element method (BEM). On the other hand, there are two methods which can solve magnetostatic field problems with multiply connected domains in double layer charge (DLC) formulation. One uses imaginary loop current to calculate exciting scalar potentials and the other uses the direct BEM to calculate exciting scalar potentials. Thus, in this study, we expand the application scope of the above methods to the direct BEM. The direct BEM is widely used with other analysis methods such as the finite element method (FEM). In that respect, it is also effective to be able to analyze magnetostatic field problems with multiply connected domains by the direct BEM. In addition, results comparing the two methods to analyze multiply connected problems in both the DLC formulation and the direct BEM have not been reported. Therefore, we compare those and systematically clarify their characteristics by calculating a toroidal core model.

It is difficult to analyze magnetostatic field problems with multiply connected domains by the direct boundary element method (BEM). On the other hand, there are two methods which can solve magnetostatic field problems with multiply connected domains in double layer charge (DLC) formulation. One uses imaginary loop current to calculate exciting scalar potentials and the other uses the direct BEM to calculate exciting scalar potentials. Thus, in this study, we expand the application scope of the above methods to the direct BEM. The direct BEM is widely used with other analysis methods such as the finite element method (FEM). In that respect, it is also effective to be able to analyze magnetostatic field problems with multiply connected domains by the direct BEM. In addition, results comparing the two methods to analyze multiply connected problems in both the DLC formulation and the direct BEM have not been reported. Therefore, we compare those and systematically clarify their characteristics by calculating a toroidal core model.

Photovoltaic (PV) systems have recently attracted considerable attention in the context of environmental problems, antinuclear power movements, and energy problems. Therefore, the large-scale introduction of PV systems is expected in the near future. But the connection of many PV systems to the power system leads to problems. For example, the system voltage often drifts from the norm when reverse power flows increase. Accordingly, optimal system operation is required in order to make maximum use of solar energy to the maximum by installing energy buffers such as storage batteries. In particular, in forecast information, knowledge of the reliability as well as the predicted solar irradiance is essential for effective operation. In this paper, we propose a way of estimating the prediction interval of solar irradiance as an index of reliability by using just-in-time modeling. We consider the accuracy of the prediction interval under many conditions and derive a high-precision estimation method. In addition, we also discuss about the future subjects of study. (C) 2016 Wiley Periodicals, Inc. Published online in Wiley Online Library (wileyonlinelibrary.com).

This paper proposes a novel accuracy improvement technique for the double-layer charge (DLC) formulation in shielding problems. Although the DLC formulation has advantages over the direct methods from the viewpoint of computational cost, the calculation accuracy can be worse because of cancellation errors. In order to improve the accuracy, we apply a new technique based on the difference field concept. Numerical results, which verify the effectiveness of the proposed method, are presented.

Topology optimization (TO) is an effective method for producing practical design of electrical machines. TO is conventionally implemented based on the material density; however, this approach can yield a large number of grayscale areas and unfeasible shapes. On the other hand, when the level-set function is applied to the TO of the magnetic field problem, the potential for obtaining a feasible solution improves. This paper implemented a TO method that uses the regularized level-set function to solve the 3-D nonlinear magnetic field problem. Furthermore, a spatial symmetry condition (SSC), which can introduce the mirror and periodic symmetry of the level-set function from the viewpoint of the electromagnetism, is proposed. To achieve symmetry in the electromagnetic field distribution, the validity of the SSC is investigated and confirmed in a 3-D magnetic shielding problem.

In the case of a mass introduction of PV the instability of PV system output leads to a deterioration of power quality in the distribution system. In this research, we focus on the storage battery operation to achieve a balance between power supply and demand, and perform multi-objective optimization. Specifically, we determine the optimal relationship between the storage battery's charging and discharging rates and the required time resolution for ideal optimization results.

The Output of photovoltaic (PV) systems depends on weather conditions. Therefore if there is a large introduction of PV systems, the power quality in the distribution system will be affected. One effective solution for this problem is to predict PV output. Although the need for prediction information for short period fluctuation is increasing, it is difficult to directly predict a steep fluctuation on the second time scale. For the prediction information of PV output, we propose the estimation of the prediction interval of the fluctuation widths on a 10 second scale. In this paper, we carry out the prediction by using the conventional method, with one-dimensional kernel density estimation, and the proposed method, with two-dimensional kernel density estimation. Then, we discuss the effectiveness of the proposed method based on several numerical indexes.

© 2016 University of Ljubljana. The degree of operational freedom of home appliances is increasing with introducing controllable demand-side appliances by using Home Energy Management System with some communication standard. This situation increases the demands on methodology achieving customer utility maximization, which is able to plan operational strategies of a variety of appliances under various exogenous variables such as energy demand, outlet temperature, and power output of Photovoltaic power generator. Energy demand and photovoltaic output have some uncertainty or variation in the parameter. The objective of this study is to analyze a solution behavior of an operational planning problem adapting Mixed Integer Second-Order Cone Programming extended from traditional Mixed Integer Linear Programming model. The objective function of the mathematical optimization involves mean and its variance by extracting naturally Markowitz model. Above proposed model is intended to sophisticate robust operational planning method, and is also evaluated on the EMS simulation platform that we are developing. As a result, it is found that involving variance to objective function affects to computational time meaning computational load rather than robustness of planned schedule. Additionally, using several scenario results in more robust schedule than using plausible one scenario.

This paper deals with the multi-objective design optimization of the primary core in induction heating roll in consideration of heating performance, cost, and manufacturability. We effectively carry out the shape optimization of the core by combining the 2D level-set method with the 3D finite element method for the coupled nonlinear magnetic-thermal analysis.

The axle counter which detects the position of the train is important railway signal device. This paper deals with a multi-objective optimization of the axle counter by 3D magnetic field analysis. In the optimization, we newly propose the introduction of the conductor plate and carry out its design optimization. It is revealed that the shape optimization of conductor plate enables us to well improve the detection performance of the axle counter from the multi-objective point of view.

In this paper, we propose a novel analysis method with local expantion edge elements, in which the interpolation of the potential in the radial direction is defined besed on the idea of the local expansion. It enables us to accurately analyze the physical quantity in the targeted finite region as more smoothed values.

In a distribution line, power system control and power equipment investment are planned based on a measured power system current. However, recently the mass introduction of PV make it difficult for us to precisely measure the demand curve that is a current consumed by electrical equipment because the reversal power flow from PV systems is superposed. Therefore, the prediction of demand curves of distribution line is indispensable for power system management. Additionally, it is also necessary to estimate the reliability of the predicted values as well as predicted current itself. In this paper, we propose the estimation method of the prediction interval that is the index of reliability based on the past demand curve database. The feature of the proposed method based on Just-In-Time (JIT) modeling make it possible for us to accurately estimate the prediction interval by the normalized database of demand curve. In this paper, some numerical examples are presented, which demonstrate the effectiveness of the proposed method.

The Output of photovoltaic (PV) systems depends on weather conditions. Therefore if there is a large introduction of PV systems, the power quality in the distribution system will be affected. One effective solution for this problem is to predict PV output. Although the need for prediction information for short period fluctuation is increasing, it is difficult to directly predict a steep fluctuation on the second time scale. For the prediction information of PV output, we propose the estimation of the prediction interval of the fluctuation widths on a 10 second scale. In this paper, we carry out the prediction by using the conventional method, with one-dimensional kernel density estimation, and the proposed method, with two-dimensional kernel density estimation. Then, we discuss the effectiveness of the proposed method based on several numerical indexes.

In the case of a mass introduction of PV the instability of PV system output leads to a deterioration of power quality in the distribution system. In this research, we focus on the storage battery operation to achieve a balance between power supply and demand, and perform multi-objective optimization. Specifically, we determine the optimal relationship between the storage battery's charging and discharging rates and the required time resolution for ideal optimization results.

This paper proposes a new pulse width modulation (PWM) carrier distribution technique for reducing motor electromagnetic noise. The proposed method uses only two carrier frequencies and controls PWM harmonics by the transferring probability of the two carrier frequencies. The proposed method is verified by experiments using 0.8 kW PMSM.

In this paper, a magnetic-polarity detection method for a permanent-magnet reluctance motor (PRM) is presented. The inductance characteristics of a PRM are different from those of common interior permanent-magnet synchronous motors and are verified by an electromagnetic field analysis. Moreover, a novel magnetic-pole detection method is proposed using the inductance characteristics of a PRM. The proposed method is verified by experiments using a 90-kW PMSM.

Electromagnetic phenomena intrinsically spread over an infinite region. Thus, efficient handling of open boundaries is one of the main issues in electromagnetic field computations. This paper deals with the orthogonalized infinite edge element method that efficiently performs precise analysis of the infinite region. In this method, several parameters are used to achieve high accuracy. As one of the parameters, we focus on the reference point and investigate the effect of its position setting on accuracy. We also evaluate the accuracy of the calculated magnetic field in the far region. By applying boundary element method as postprocessing, it is found that high computational accuracy in the region can be effectively achieved.

The infinite edge element method (IEEM) has been proposed as an effective method for efficiently handling open boundary region, i.e., the air region. In this paper, we present a newly defined infinite element radiated from a reference plane (RPL), and propose the combination method using various infinite element configurations, such as radiated configurations from a reference point, a reference line, and an RPL. By using the proposed hybrid method, we can drastically decrease the number of ill-shaped infinite elements and improve the computational accuracy and convergence characteristics in comparison with the conventional IEEM, especially in the case of flattened analysis models.

The axle counter as a train detector is one of the important railway signaling devices for accurate and safe train control systems. This paper deals with a design optimization of the axle counter by large-scale magnetic field computations. To efficiently reduce the computational burden in the optimization, we accurately estimate the signaling level by applying infinite edge elements to an extensive air domain, which results in a practical design approach within an acceptable CPU-time.

PV system recently attracts much attention on the back of environmental problems, antinuclear power movements and energy problems. Therefore, a large scale introduction of PV system is expected in the near future. On the other hand, a lot of PV systems connected to the power system bring on some problems. For example, a system voltage often drifts from the norm when the reverse power flow increase. Accordingly, it is necessary to perform an optimal system operation in order to utilize a solar energy to the maximum by installing energy buffers, e.g. storage batteries. Especially, the forecast information i.e., the reliability as well as predicted solar irradiance is essential for the effective operation. In this paper, we propose a way to estimate the prediction interval of the solar irradiance as an index of reliability by using Just-In-Time Modeling (JIT Modeling). We consider the accuracy of the prediction interval under many conditions and derive the high-precision estimation method. In addition, we also talk about the future outlook of this study.

The nonlinear magnetic properties of an iron core should be considered when topology optimization (TO) is applied to a realistic problem. However, a scheme for introduction of the magnetic nonlinearity to material-density-based TO has not been rigorously established. In this paper, TO by using material density with magnetic nonlinearity is proposed. The numerical instability of the sequential linear programming method is a well-known topic. The stabilized sequential linear programming method, which realizes the stabilized convergence characteristics of an objective function, is proposed and investigated in the 3-D design problem of a magnetic circuit.

In the past, we have proposed battery operations in a photovoltaic (PV) system using PV output and load power forecasts. In the proposed method, we utilized multiobjective optimization for a residential area model that includes a large number of PV systems with storage batteries. To practically demonstrate that the proposed operation effectively improves economic and environmental efficiency, it is indispensable to evaluate the effects of forecast error on the operation design of a PV system with storage battery. In this paper, we propose a method for evaluating the robustness of battery operation taking account of the statistical characteristics of forecast errors. Some numerical examples, which show the validity of the proposed method, are also presented.

Residential houses are in the process of introducing power generators such as photovoltaic (PV) power generators and fuel cell cogeneration systems. Under current laws in Japan, surplus electricity from a residential PV system can be sold by feeding it back into the electrical grid. However, when a lot of neighboring power generators make and feed back electricity at the same time, there is an issue of an upper voltage violation of the provisions of the laws and regulations relating to the Electricity Business Act in the distribution system of the electrical grid. The issue has been solved by stopping power generators when they reach an upper voltage limit, 107V. Another solution is to acknowledge demand response signal from electrical grid operator to store electricity in residential batteries using Home Energy Management System (HEMS). The research question is that how to collaborate HEMS and Grid Energy Management System (GEMS). This paper developed an evaluation framework for the cooperative behavior between HEMS and GEMS. Using this evaluation framework, this paper demonstrated the optimal operational strategy of HEMS including PV in the case that HEMS is informed voltage profile from GEMS, and also assessed amount of PV suppression quantitatively in residential sector in practical aspect.

Demand-side electricity saving is an important factor in the reduction of the installed capacity of power-supply facilities. In order to save electricity automatically while maintaining comfort levels, home energy management systems (HEMS) have attracted attention. These systems can control residential energy equipment cooperatively to reduce electricity consumption while considering benefits to consumers. Although many researchers have evaluated HEMS, no one has conducted a study which considers the control of various types of residential energy equipment in real time along with the uncertainties of energy demands. This paper proposes a single HEMS method which connects prediction, operational planning and control steps and enables the evaluation of operational planning methods of HEMS connected with many kinds of residential energy equipment currently in use in Japan while considering the uncertainties. The purpose of this study is to evaluate the economic potential of residential energy systems based on the proposed method with the uncertainties of energy demands and photovoltaic (PV) output under time-of-use prices. The results allowed us to establish a framework to quantitatively evaluate the operational planning methods of HEMS with the uncertainties of energy demands and PV output. In addition, the usability of the proposed method was confirmed by comparing the operational costs to those of a reference method.

Residential houses are in the process of introducing power generators such as photovoltaic (PV) power generators and fuel cell cogeneration systems. Under current laws in Japan, surplus electricity from a residential PV system can be sold by feeding it back into the electrical grid. However, when a lot of neighboring power generators make and feed back electricity at the same time, there is an issue of an upper voltage violation of the provisions of the laws and regulations relating to the Electricity Business Act in the distribution system of the electrical grid. The issue has been solved by stopping power generators when they reach an upper voltage limit, 107V. Another solution is to acknowledge demand response signal from electrical grid operator to store electricity in residential batteries using Home Energy Management System (HEMS). The research question is that how to collaborate HEMS and Grid Energy Management System (GEMS). This paper developed an evaluation framework for the cooperative behavior between HEMS and GEMS. Using this evaluation framework, this paper demonstrated the optimal operational strategy of HEMS including PV in the case that HEMS is informed voltage profile from GEMS, and also assessed amount of PV suppression quantitatively in residential sector in practical aspect.

This paper studies a magnetic polarity detection method for permanent magnet reluctance motor (PRM). Inductance characteristic of PRM is different from that of common interior permanent magnet synchronous motor. The inductance characteristic of PRM is verified by electromagnetic field analysis. Moreover, this paper proposes novel magnetic polarity detection method using the inductance characteristic of PRM. The proposed method is verified by experiments using a 90-kW PRM.

Recently, for the purpose of utilizing renewable energy in a community, interactive electricity power networks, such as smart grid, have received much attention. In those electricity power networks, the technologies for maintain the balance of electricity demand and supply in a limited area become more important. Installing photovoltaic system can be effective for supplying electricity in a limited area at the peak load time, but PV output depends on weather conditions. Thus we propose to combine PV power generation with demand response program. We simulate interchange PV power with demand response program in a residential community. Some numerical results, which demonstrate the validity of the proposed method, will be presented.

Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.

This paper presents a distribution automation system (DAS) for service restoration in the distribution network with photovoltaic (PV) generator systems, which are disconnected simultaneously after a fault and subsequently reconnected after service restoration. Because the reverse power flow of PVs affects voltage in the distribution system, voltage dips and surges occur during the service restoration. However, current DAS do not control voltage regulators such as an on-load tap changer (OLTC) and step voltage regulators (SVRs) during the service restoration. The proposed DAS estimates the voltage in a distribution network considering the simultaneous disconnection of PVs by performing power flow calculations, and it controls the tap position of OLTC and/or SVRs according to the predicted voltage deviation. The voltage after the disconnection of PVs is calculated by estimating the PV output utilizing square kilometer solar radiation data calculated using satellite image data in real time.

When using the indirect method in magnetostatic analysis, the magnetic material is represented by the double-layer charge on the material surface. The double-layer charge offers an integral form of scalar potential to give a boundary integral equation (BIE). A unified integral form of excitation potential has been derived, resulting in a BIE capable of solving generic problems. When we apply the standard BIE to analyze magnetic shields by thin shells with high permeability, we usually cannot get accurate results in the shielded space. To accurately solve shielding problems using rough meshes, in this paper we propose a new modeling approach by using a concept of the boundary element method.

This paper derives an effective shape of the flux barrier in an interior permanent magnet (IPM) motor. IPM motors generally have many design parameters such as the current phase angle, shape of the rotor and stator's iron core, and shape and position of the magnet. The flux barrier plays an important role in controlling torque characteristics. We apply topology optimization (TO) to the rotor core using a multistep genetic algorithm to determine an effective flux barrier. Furthermore, we extend the TO to combinatorial optimization for considering its effect on the current phase angle. Thus, a reasonable flux barrier with an optimal phase angle is determined.

Topology optimization (TO) makes it possible to obtain new structures for electrical machines. The sensitivity-based method, which can cope with some constraint conditions, is suitable for large-scale three-dimensional TO. However, if the material density is defined by unknown variables in TO, elements with intermediate density (grayscale) occasionally appear. The grayscale cannot clearly show the material allocation within its finite element. Thus, we propose a sigmoid-based filtering function to suppress the generation of grayscale. Moreover, because the constraint condition can be simply taken into consideration, sequential linear programming is occasionally utilized as a topology optimizer. However, the convergence characteristics frequently oscillate and are strongly dependent on the move limit that controls the maximum intensity of the correction vector. To overcome this numerical difficulty, we propose an identification technique for the determination of a quasi-optimal move limit (QOML). This paper demonstrates the performance of both the mathematical function filtering grayscale and QOML.

This paper deals with a large-scale eddy-current analysis of the constructions in railway system from the view point of electromagnetic noise assessment. To reduce computational costs with the calculation accuracy kept, we develop some numerical methods and demonstrate their effectiveness using a practical large-scale model.

This study derives a high performance flux barrier for an interior permanent magnet (IPM) motor using binary-based topology optimization (TO). TO has a higher degree of optimization than size or shape optimization. An IPM motor has many design parameters including the current phase angle, core shape of rotor and stator, and magnet position and shape. The flux barrier in an IPM motor plays a particularly important role, influencing several characteristics. We apply TO, using a multistep genetic algorithm, to the rotor core in order to determine a flux barrier with the highest torque performance.

Purpose - The purpose of this paper is to improve the multistep algorithm using evolutionary algorithm (EA) for the topology optimization of magnetostatic shielding, and the paper reveals the effectiveness of methodology by comparison with conventional optimization method. Furthermore, the design target is to obtain the novel shape of magnetostatic shielding.
Design/methodology/approach - The EAs based on random search allow engineers to define general-purpose objects with various constraint conditions; however, many iterations are required in the FEA for the evaluation of the objective function, and it is difficult to realize a practical solution without island and void distribution. Then, the authors proposed the multistep algorithm with design space restriction, and improved the multistep algorithm in order to get better solution than the previous one.
Findings - The variant model of optimized topology derived from improved multistep algorithm is defined to clarify the effectiveness of the optimized topology. The upper curvature of the inner shielding contributed to the reduction of magnetic flux density in the target domain.
Research limitations/implications - Because the converged topology has many pixel element unevenness, the special smoother to remove the unevenness will play an important role for the realization of practical magnetostatic shielding.
Practical implications - The optimized topology will give us useful detailed structure of magnetostatic shielding.
Originality/value - First, while the conventional algorithm could not find the reasonable shape, the improved multistep optimization can capture the reasonable shape. Second, An additional search is attached to the multistep optimization procedure. It is shown that the performance of improved multistep algorithm is better than that of conventional algorithm.

The topology optimizations which optimize a material arrangement on an element, without extracting feature quantity, are attractive methods, because we can obtain a free idea of the initial design of magnetic devices. However, in actual design processes, all of the required features of the products cannot be included objective functions, such as ease of manufacture or influence of rise in heat. Moreover, the multiple-purpose optimizations concerning many kinds of physical phenomena have difficulty with calculation time. Thus, it is necessary to estimate whether the obtained optimal solution under the limited condition is applicable to an actual designing of magnetic devices. This paper introduces two-step topology optimization method using the constraints on the similarity of the topology, which provides us various topologies including suboptimal solutions. By using the proposed method, we can determine some actual applicable solutions out of obtained solutions. The proposed method was verified by applying it to the C-core problem and the magnetic shield problem, which demonstrated the effectiveness of the proposed method.

Against a background of environmental problems and energy issues, it is expected that PV systems will be introduced rapidly and connected with power grids on a large scale in the future. For this reason, concerns about how PV power generation will affect supply and demand adjustment in electric power in the future arise, and the technique of correctly grasping PV power generation becomes increasingly important. PV power generation depends on solar irradiance, module temperature, and solar spectral irradiance. Solar spectral irradiance is the distribution of the light intensity for every wavelength. As the spectral sensitivity of solar cells depends on the kind of solar cell, it becomes important for an exact grasp of PV power generation. But the preparation of solar spectral irradiance data is not easy because observational instruments for solar spectral irradiance are expensive. Against this background, in this paper, we propose a new method based on statistical pattern recognition for estimating the spectrum center, which is a representative index of solar spectral irradiance. Some numerical examples obtained by the proposed method are also presented. (c) 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 184(1): 1018, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22393

The electromagnetic phenomena intrinsically spread over the infinite space. Thus, the efficient handling of the open boundary is one of the main issues in the electromagnetic field computation. This paper proposes the infinite edge element method (IEEM) with the boundary surface integration to accurately obtain the magnetic field, i.e., the derivatives of vector potentials, in the far-field region.

PV power output mainly depends on solar irradiance, which is affected by various meteorological factors. Thus, it is required to predict solar irradiance in the future for the efficient operation of PV systems. In this paper we develop a novel approach for solar irradiance forecasting, in which we combine the black-box model (JIT modeling) with the physical model (GPV data). We investigate the predictive accuracy of solar irradiance over a wide controlled area of each electric power company by utilizing measured data from 44 observation points throughout Japan provided by JMA and 64 points around Kanto provided by NEDO. Finally, we propose an applied forecasting method of solar irradiance to deal with difficulties in compiling databases. We also consider the influence of different GPV default times on solar irradiance prediction. (C) 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 182(4): 19-28, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22338

Analysis and modeling of electric energy demand is indispensable for power planning, operation, facility investment, and urban planning. Because of recent development of renewable energy generation systems oriented for households, there is also a great demand for analysing the electricity usage and optimizing the way to install electricity generation systems for each household. In this study, employing statistical techniques, a method to model daily consumption patterns in households and a method to extract a small number of their typical patterns are presented. The electricity consumption patterns in a household is modeled by a mixture of Gaussian distributions. Then, using the symmetrized generalized Kullback-Leibler divergence as a distance measure of the distributions, typical patterns of the consumption are extracted by means of hierarchical clustering. The statistical modeling of daily consumption patterns allows us to capture essential similarities of the patterns. By experiments using a large-scale dataset including about 500 houses' consumption records in a suburban area in Japan, it is shown that the proposed method is able to extract typical consumption patterns. © 2010-2012 IEEE.

The electromagnetic phenomena intrinsically spread over the infinite region. Thus, the efficient handling of open boundary is one of the main issues in the electromagnetic field computations. This paper deals with the orthogonalized infinite edge element method which efficiently performs precise analysis of the infinite region. In this method, there are several parameters to achieve its high accuracy. As one of the parameters, we focus on the reference point and investigate the effect of its position setting on the accuracy. Furthermore, we also evaluate the accuracy of the calculated magnetic field at distance region. By applying boundary element method (BEM) as post-processing, it is found that the high computational accuracy in the region can be effectively achieved. © 2013 The Institute of Electrical Engineers of Japan.

Topology optimization using the binary information of magnetic material is one of the most attractive simulations for the conceptual design of electrical machines. Heuristic algorithms based on random search allow engineers to define general-purpose objects with various constraint conditions. However, it is difficult for topology optimization to realize a practical solution without island and void distribution. In this paper, we propose a hybrid evolutionary algorithm that is composed of a genetic algorithm (GA) and extended compact GA (ECGA). We verify the effectiveness of the proposed algorithm on the binary topology optimization problem for the design of magnetostatic shielding. © 1965-2012 IEEE.

This paper investigates the effectiveness of the time domain parallelization in magnetic field analyses of practical electric machines. We propose an efficient procedure to parallelize transient as well as steady-state analyses by generalizing the formulation of the parallel time-periodic finite element method. The proposed method is called the time domain parallel finite element method (TDPFEM) because it can be applied to both transient and steady-state analyses. Additionally, we derive a special condition of the slip to reduce computational costs for steady-state analyses of induction motors by using a half-cycle polyphase time-periodic condition. © 1965-2012 IEEE.

Since the line loop current is equivalent to the double layer charge, it gives an integral form of scalar potential. The segmental loop current on the interface between magnetic materials produces a potential gap, which works to give a boundary integral equation (BIE). By virtue of another potential gap due to a fictitious circulating current along the contour of cut-surface in the material, the excitation potential becomes single valued and the BIE becomes applicable to generic problems without any restriction. Regarding the nonlinear magnetic material as composed of segmental materials with different values of permeability, we get the same BIE for the nonlinear analysis as for the linear analysis. In order to check the adequacy and effectiveness of the nonlinear BIE, we solve a typical magnetostatic problem and compare the computed results with those by the conventional magnetic moment method. © 1965-2012 IEEE.

In the past, we have proposed some battery operations in a photovoltaic (PV) system using the PV output and load power forecasts. In the proposed method, we utilized multi-objective optimization for a residential area model that includes a large number of PV systems with storage batteries. To practically demonstrate that the proposed operation effectively improves the economic and environmental efficiencies, it is indispensable to evaluate the forecast error effects on operation design of PV system with storage battery. In this paper, we propose a method for evaluating the robustness of battery operation taking account of the statistical characteristics of forecast errors. Some numerical examples, which show the validity of the proposed method, are also presented. © 2013 The Institute of Electrical Engineers of Japan.

In this study, we examine the relationship between harmonic voltage injection, acoustic noise, and position estimation performance in a PMSM when a position-sensorless control method involving harmonic voltage injection is used at low speeds. Further, we propose a novel control method for voltage injection; this method can be used to reduce acoustic noise in the motor. The proposed control method is verified by performing numerical simulations and carrying out experiments using a four-pole, 2-kW, 2100-rpm IPMSM (interior permanent-magnet synchronous motor). (c) 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 179(3): 4956, 2012; Published online in Wiley Online Library (). DOI 10.1002/eej.21246

This paper investigates the effectiveness of various methods to accelerate the convergence to a steady state in time-periodic electromagnetic field problems. We first introduce the time-periodic explicit error correction (TP-EEC) method taking account of both the dc and linearly-varying error components and propose the harmonics TP-EEC method which enables us to achieve the increase in error correction frequency. Then, we discuss the convergence property of the TP-EEC methods based on the error analysis. The advantages and disadvantages of the TP-EEC method and the time differential correction (TDC) method are investigated from the viewpoints of computational costs and application scope.

Adopting the integral representation of scalar potential due to double layer charge, we derive a boundary integral equation with one unknown to solve magnetostatic problems. The double layer charge produces a potential gap at the air-material boundary without disturbing the continuity of normal magnetic flux density and the potential gap makes the tangential component of magnetic field continuous; accordingly, the boundary conditions are fully fulfilled even with one unknown. The boundary integral equation is capable of solving the double layer charge at edges and corners. Once the double layer charge is solved, it gives directly the magnetic flux density by Biot-Savart law. In this paper, we investigate how to evaluate the magnetic flux density at the vertex.

The scalar potential formulation by the boundary integral equation approach is attractive for numerical analysis but has fatal drawbacks due to a multi-valued function in current excitation. We derive an all-purpose boundary integral equation with double layer charges as the state variable and apply it to nonlinear magnetostatic problems by regarding the nonlinear magnetization as fictitious volume charges. We investigate two approaches how to treat the fictitious charges. In discretization by the constant volume element, a surface loop current is introduced for the volume charge. By the linear volume element, the fictitious charges are evaluated on the condition that the divergence of the magnetic flux density is zero. We give a comparative study of these two approaches.

This paper investigates the parallelization of the time-periodic finite-element method in nonlinear magnetic field analyses of rotating machines. The developed method, which can obtain the steady state solutions directly, provides large granularity even in the small-scale problems compared with the ordinary parallel FEM based on the domain decomposition approach. Furthermore, we apply the parallel TPFEM to analyses of induction motors which have different time periodicities in stator and rotor regions due to the slip. Numerical results verify the effectiveness of the developed method.

This paper proposes an orthogonalization of the Hilbert matrix in element matrices of the infinite edge elements. The validity of the infinite edge element is demonstrated in previous researches, but the Hilbert matrix results in extremely slow convergence in the ICCG method, especially when using higher order expansions. The proposed orthogonalization technique improves the convergence drastically and it makes the infinite elements practical in the electromagnetic FEM analysis of the open boundary problems in quasi-static magnetic fields.

With a background of environmental problems and energy issues, it is expected that PV systems will be introduced rapidly and connected with power grids on a large scale in the future. For this reason, the concern to which PV power generation will affect supply and demand adjustment in electric power in the future arises and the technique of correctly grasping the PV power generation becomes increasingly important. The PV power generation depends on solar irradiance, temperature of a module and solar spectral irradiance. Solar spectral irradiance is distribution of the strength of the light for every wavelength. As the spectrum sensitivity of solar cell depends on kind of solar cell, it becomes important for exact grasp of PV power generation. Especially the preparation of solar spectral irradiance is, however, not easy because the observational instrument of solar spectral irradiance is expensive. With this background, in this paper, we propose a new method based on statistical pattern recognition for estimating the spectrum center which is representative index of solar spectral irradiance. Some numerical examples obtained by the proposed method are also presented. © 2012 The Institute of Electrical Engineers of Japan.

The volume integral equation approach replaces magnetic materials with the magnetization in magnetostatic analysis. The concept of magnetic shell relates the magnetization with loop currents. The loop current is equivalent to the magnetic double layer, which gives an integral form of the scalar potential. The nonlinear magnetic field is formulated by regarding the nonlinear magnetization as volume magnetic charges. This paper presents how to utilize the volume charge to solve nonlinear problems. In the case of constant volume element we replace the volume charges with the surface loop currents to derive the nonlinear boundary integral equations having the line and surface loop currents as unknowns. The boundary integral equation is solved iteratively while improving alternately the loop and surface currents.

Electricity consumption in households varies dependent on a lot of possible reasons such as lifestyle, family configuration, and weather. It is of great importance to optimize the electricity generation system to install for each household. In our previous work, we proposed a clustering approach for extracting a small number of basic electricity consumption patterns in a household. In this study, we apply the method to a larger dataset with many households. In the previous work, we determined the number of basic patterns in a heuristic manner. In this work, we use gap statistics to automatically determine an appropriate number of basic patterns, and we obtained a reasonable result on a large-scale data.

This paper develops a parallel fast multipole method specialized for uniform brick elements to achieve large-scale micromagnetic simulations of a practical perpendicular recording head within acceptable computation time. In highly parallel computation, it is indispensable to equally distribute the computing load among processes so as to obtain the good parallel speedup. The load balancing technique which can be regarded as the domain decomposition method based on octree structure in the fast multipole method is discussed. The scalability of the parallel fast multipole accelerated micromagnetic simulation is investigated with 100 or more MPI processes.

In this paper, we describe a study of mesh deformation methods for magnetic field analysis. We propose an efficient method that is a combination of two conventional mesh deformation methods. We numerically estimate the basic performance of the proposed method and conventional methods using three-dimensional mesh models for magnetic field analysis. We highlight the advantages of the proposed method with respect to its robustness and computational cost. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons,

This paper proposes a novel effective method for open boundary problems by using the finite-element method (FEM) with a new formulation of the infinite edge element. We developed the formulation of the infinite element by adopting the characteristi