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Photovoltaics (PV), which is one of variable renewable energies, have been installed largely. In the environment of largely installed PV, the output fluctuates of PV influences on the operation of power gird network adversely. Therefore, PV energy generation forecasting is valid for power grid operation and management and needs the reduction of large forecast error as well as average error. Due to a day‐ahead forecast of the total PV energy generation in the power grid area, we developed the forecasting method by using meteorological forecast data of many points in the target area. In order to forecast the regional PV energy generation, the proposed method uses auto‐encoder and convolutional neural network (CNN) for extracting requirements and valid data, and forecast with neural network (NN) by means of extracted information. In this paper, we improved the forecasting error by using multiple meteorological elements as input data. As a result, we indicated that using both of global horizontal irradiance and low cloud cover is required for the reginal PV energy generation forecasting, and large forecasting error can be reduced by adding either dew point depression, or cumulative precipitation as input data. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

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.

Photovoltaics (PV) output prediction, which is indispensable for power system operation, can affects demand and supply adjustment adversely when large prediction error occurs. Thus, the reduction of large error as well as average error is required in PV power prediction. In 2019, the operation of the Meso‐scale Ensemble Prediction System (MEPS) of numerical weather prediction started from the JapanMeteorological Agency, and the amount of forecasting information would be potentially useful for the improvement of PV power prediction. However, very few studies on inputting multiple meteorological elements of the MEPS have been reported. In this paper, we newly develop the prediction model for an area day‐ahead PV power output composed of Just‐In‐Time Modeling (JIT Modeling) with multiple elements of theMEPS. The developed method achieves precise forecasts with low computational load by both selecting meteorological elements valid for improving prediction accuracy and adequately devising the structure of JIT Modeling. Some numerical examples demonstrating the effectiveness of the developed method are also presented. In particular, the proposed method reduces large error significantly. [ABSTRACT FROM AUTHOR]

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.

In this paper, we propose a novel multi‐objective topology optimization with response surface approximation interpolating various topologies, which is derived by deep learning with training data in the actual design space. The response surface is constructed by means of autoencoder with the training data of geometrically diverse shapes of targeted devices, which can express the interpolations that combine the multiple characteristic structures. The global topology search is performed based on the gradient information of the response surface, by which we can obtain the initial shapes for level set optimization to efficiently obtain easily manufactured and excellent Pareto optimal solutions. The effectiveness of the proposed method is demonstrated by optimizing multi‐flux barriers in a synchronous reluctance motor for the objective functions of average torque and torque ripple. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we describe the applicability of Algebraic Multigrid Method (AMG method) as a fast solution for magnetic field analysis of an electric machine with a laminated core. In an experimental analysis, we have found that there are some cases where the calculation speed can be improved by using the AMG method for a fine mesh that models a laminated iron core exactly. Therefore we investigated the convergence characteristic of the standard Incomplete Cholesky Conjugate Gradient method (standard ICCG method) and the Conjugate Gradient method preconditioned with AMG method (AMGCG method) for the simple and actual analysis models. The numerical results show that the AMGCG method provides fast solutions for laminated mesh models for which the standard ICCG method does not work well in many analysis cases. Index Terms--Algebraic multigrid method, finite element methods, iterative methods, laminated core.

This paper reports a large-scale eddy-current analysis of conductive frame of large-capacity inverter. The eddy-current loss obtained by the electromagnetic field analysis is used as a heat source for the thermal analysis. Then, the suitable configuration of the frame for the suppression of temperature increase is investigated and designed. The hybrid finite-element and boundary-element (FE-BE) method is very suitable for the analysis of a complicated-shaped frame because it does not require mesh division for a free space and can easily treat eddy current. For the reduction of large computational costs, the fast multipole method (FMM) is introduced. Furthermore, in order to improve the convergence characteristic of iterative methods for system matrix, we develop the application of the IDR(s) method to the minor iterative preconditioning technique (MIP) and evaluate the performance. Finally, some numerical results that demonstrate the effectiveness of the developed method are presented. Index Terms--Coupled electromagnetic-thermal analysis, eddy-current, fast multipole method, hybrid finite-element and boundary-element method, IDR(s), large-scale analysis.

This paper investigates a starting procedure of rotational sensorless permanent magnet synchronous motor (PMSM) in the rotating condition, which is suitable for some applications with higher maximum rotor frequency and longer current sampling time. Instantaneous estimation of initial rotor position and frequency, right after gates start, is essential for restarting the operation of inverters. Existing estimation methods are not available for the aforementioned applications because of their higher maximum rotor frequency and longer current sampling time. To cope with this problem, we propose a novel initial rotor frequency estimation method. The proposed estimation method is verified by experiments using a 2-kW interior PMSM and a numerical simulation. Index Terms--Permanent magnet synchronous motors (PMSMs), rotational sensorless control, starting procedure at rotating condition.

This paper proposes a novel robust optimization approach by combination of sensitivity analysis and sigma level estimation in multi-objective problems. In order to obtain robust Pareto-optima within acceptable computational costs, we actively reuse the already calculated data for the sensitivity analysis in multipoint search algorithm. The sigma level estimation is also utilized to select the significant solutions from a large number of Pareto-optima based on both the robustness and the performance. Some numerical results that verify the effectiveness of the proposed methods are presented. Index Terms--Genetic algorithm (GA), multi-objective optimization, particle swarm optimization (PSO), robust optimization, sensitivity analysis, sigma level.

This paper proposes the variables screening technique based on the stepwise multiple regression in multiobjective design optimization. This approach enables us to efficiently select the design variables that have a sufficient effect on machine performance. Some numerical results that demonstrate the validity of the proposed method are also presented. Index Terms--Multiobjective design, optimization methods, stepwise multiple regression.

This paper describes large-scale and fast nonlinear magnetostatic field analyses by the magnetic moment method (MMM) with the adaptive cross approximation. In order to stabilize the convergence characteristic of the Newton-Raphson method, we apply a line search technique to the MMM. Some numerical results that demonstrate the validity of the developed method are also presented. Index Terms--Adaptive cross approximation, line search, magnetic moment method (MMM), nonlinear magnetostatic field analysis.

This paper shows large-scale eddy-current analysis by a hybrid finite-element and boundary-element (FE-BE) method. We introduce the fast multipole method (FMM) into the two kinds of hybrid FE-BE formulations developed by ourselves. To achieve more reduction of CPU time, we propose a novel preconditioning technique suitable for the hybrid FE-BE methods with the FMM. Furthermore, we improve the FMM calculation process in the hybrid method using magnetic field intensity. Some numerical results that demonstrate the effectiveness of these approaches are also presented. Index Terms--Eddy-current, fast muitipole method, hybrid finite-element and boundary-element method, large-scale analysis.

This paper shows a large-scale analysis of surface charge in eddy-current problems, which is useful for designing an electric machine. We introduce the fast multipole method with the pseudoparticle method into the large-scale surface charge analysis and further propose an approach to dealing with the symmetry and periodicity of the analysis model by the concept of the method of images. Some numerical results, which will show the validity of the proposed method that calculation time is reduced while maintaining high precision, are presented. Index Terms--Eddy current, fast multipole method (FMM), method of images, pseudoparticle method, surface charge.

A computational approach to the design of an interior permanent magnet synchronous motor to clarify its optimal design applied for traction systems of the next generation commuter train is developed. The finite element method, the multiobjective optimization technique and the response surface methodology are introduced.

This paper shows a large-scale and highly accurate nonlinear magnetostatic field analysis of laminated iron core by using the hybrid finite element and boundary element (FE-BE) method. The hybrid FE-BE method is fairly effective to directly deal with the microstructure because no mesh division is required for the free space. In order to obtain the drastic reduction of the computational costs and stabilize the convergence characteristic of the Newton-Raphson method, the fast multipole method and the line search are introduced. Some numerical results that verify the effectiveness of the developed method are also presented. Index Terms--Fast multipole method, hybrid finite element and boundary element (FE-BE) method, laminated iron core, line search.