• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.432-434
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• 1994

This paper describes a phase-shifter which can flexibly adjust the active and reactive power flow through an ac transmission line. The phase-shifter has two voltage-source converters sharing an energy storage capacitor. The magnitude of the injected voltage is controlled by the converter I connected in parallel with the sending terminal, while that of phase angle by the converter II in series with the line through the coupling transformer. In order to analyze the whole system operation, an equivalent circuit model was developed and verified by a computer simulation with EMTP code.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.1
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• pp.11-21
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• 2020

This study aims to develop and advance the evaluation technology for assessing PHWR safety. For this purpose, the complete loss of AC power or station blackout (SBO) was selected as a target accident scenario and the analysis model to evaluate the plant responses was envisioned into the MARS-KS input model. The model includes the main features of the primary heat transport system with a simplified model for the horizontal fuel channels, the secondary heat transport system including the shell side of steam generators, feedwater and main steam line, and moderator system. A steady state condition was achieved successfully by running the present model to check out the stable convergence of the key parameters. Subsequently, through the SBO transient analyses two cases with and without the coolant leakage via the PHTS pumps were simulated and the behaviors of the major parameters were compared. The sensitivity analysis on the amount of the coolant leakage by varying its flow area was also performed to investigate the effect on the system responses. It is expected that the results of the present study will contribute to upgrading the evaluation technology of the detailed thermal hydraulic analysis on the SBO transient of the operating PHWRs.

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.81-86
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• 2012

The objective of the present study is to investigate the effects of various turbulence models on the aerodynamic noise of an air-conditioner (AC) indoor unit. The results from URANS (unsteady Reynolds-averaged Navier-Stokes) simulations with the standard k-$\varepsilon$, k-$\omega$ shear stress transport (SST) and Spalart-Allmaras (S-A) turbulence models were analyzed and compared with the noise data from the experiments. The frequency spectra of the far-field acoustic pressure were computed using the Farrasat equation derived from the Ffowcs Williams-Hawkings (FW-H) equation based on the acoustic analogy model. Two fixed fan casings and the rotating cross-flow fan were used as the source surfaces of the dipole noise in the Farrasat equation. The result with the standard k-$\epsilon$ model showed a much better agreement with the experimental data compared to the k-w SST and S-A models. The differences in the pressure spectra from the different turbulence models were discussed based on the instantaneous vorticity fields. It was found that the over-estimated power spectra with the k-w SST and S-A models are related to the emphasized small-scale vortices produced with these models.