• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.905-912
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• 2013

Power system fault analysis is commonly based on well-known symmetrical component method, which describes power system elements by positive, negative and zero sequence impedance. In case of balanced fault, such as three phase short circuit, transmission line can be represented by positive sequence impedance only. The majority of fault in transmission lines, however, is unbalanced fault, such as line-to-ground faults, so that both positive and zero sequence impedance is required for fault analysis. When unbalanced fault occurs, zero sequence current flows through earth and skywires in overhead transmission systems and through cable sheaths and earth in cable transmission systems. Since zero sequence current distribution between cable sheath and earth is dependent on both sheath bondings and grounding configurations, care must be taken to calculate zero sequence impedance of underground cable transmission lines. In this paper, conventional and EMTP-based sequence impedance calculation methods were described and applied to 345kV cable transmission systems (4 circuit, OF 2000mm2). Calculation results showed that detailed circuit analysis is desirable to avoid possible errors of sequence impedance calculation resulted from various configuration of cable sheath bonding and grounding in underground cable transmission systems.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.3
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• pp.281-301
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• 2024

The power cable tunnels which are part of the underground transmission line project, are constructed using the shield TBM method. The disc cutter among the shield TBM components plays an important role in breaking rock mass. Efficient tunnel construction is possible only when appropriate replacement occurs as the wear limit is reached or damage such as uneven wear occurs. A study was conducted to determine the wear conditions of disc cutter using a deep learning algorithm based on real-time measurement data of wear and rotation speed. Based on the results of full-scaled tunnelling tests, it was confirmed that measurement data was obtained differently depending on the wear conditions of disc cutter. Using real-time measurement data, an algorithm was developed to determine disc cutter wear characteristics based on a convolutional neural network model. Distributional patterns of data can be learned through CNN filters, and the performance of the model that can classify uniform wear and uneven wear through these pattern features.