IEEJ Transactions on Power and Energy
Online ISSN : 1348-8147
Print ISSN : 0385-4213
ISSN-L : 0385-4213
Volume 140 , Issue 12
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  • Lijun Liu, Kazuaki Sekiya, Masao Ogino, Koki Masui
    2020 Volume 140 Issue 12 Pages 832-841
    Published: December 01, 2020
    Released: December 01, 2020
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    Solving complex symmetric systems efficiently is a significantly important issue in the applications of electromagnetics since the discretization of the numerical model using the finite element method results in complex symmetric systems when computing the electromagnetic field. However, such complex symmetric systems are usually much more difficult to be solved because of the property of non-Hermitian therefore, efficient numerical methods for the solution of complex symmetric systems are demanded. In this study, we proposed an iterative method called COMINRES-QLP which is specially designed for complex symmetric linear systems. Moreover, we proposed a new stopping criterion which could be very useful in practical computations when the condition number of the coefficient matrix is unknown.

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  • Norikazu Kanao, Masaaki Ishimaru
    2020 Volume 140 Issue 12 Pages 842-850
    Published: December 01, 2020
    Released: December 01, 2020
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    Recently, a lot of photovoltaic (PV) generation systems have been penetrated in distribution power systems. It is important for the power system operators to know a total value of PV output and real load of a distribution line in real time. But the real load is unmeasurable while the PV systems are generating. This paper describes an estimation method of PV output and a forecasting method of real load in a distribution line using two types of Kalman filters with power flow data (P, Q) and solar radiation. These methods were examined for accuracy in a real distribution line in Hokuriku Electric Power Company. The root mean square errors (RMSEs) for estimated PV output and 2-hour forecasted real load were about 7% and 10% error rate of total PV capacity through one year, respectively. These results show that these methods would be acceptable for power system operators because this method is simpler than the other methods that have been proposed in the past.

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  • Tetsuya Nakamoto
    2020 Volume 140 Issue 12 Pages 851-857
    Published: December 01, 2020
    Released: December 01, 2020
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    Using the current injection method, how to calculate the transient recovery voltages in three-phase asymmetrical current interruption in analysis has been devised. This calculation is applicable to both effectively earthed neutral system and non-effectively earthed neutral system. Since the transient recovery voltages of three-phase test duty T100a are calculated, the performance of the circuit breaker in three-phase asymmetrical current interruption can be estimated more correctly in synthetic testing.

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  • —Comparison of Simultaneous and Additional Learning—
    Hidenori Sasaki, Yuki Hidaka, Hajime Igarashi
    2020 Volume 140 Issue 12 Pages 858-865
    Published: December 01, 2020
    Released: December 01, 2020
    JOURNALS RESTRICTED ACCESS

    Deep learning is applied to IPM motors with different magnet shapes to realize fast topology optimization. In this method, the cross-sectional image of IPM motors with I-shaped and V-shaped magnets are input to a convolutional neural network to guess their average torque. It is shown that simultaneous learning, in which CNN is trained for both datasets, is superior over the additional learning where CNN is sequentially trained for the two datasets. Moreover, it is shown that the number of required finite element analysis can be reduced to about five percent using the trained CNN in the topology optimization.

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