• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.53-58
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• 2021

Nuclear power plant's safety against seismic events is evaluated as risk values by probabilistic seismic safety assessment. The risk values vary by the seismic failure correlation between the structures, systems, and components (SSCs). However, most probabilistic seismic safety assessments idealized the seismic failure correlation between the SSCs as entirely dependent or independent. Such a consideration results in an inaccurate assessment result not reflecting real physical phenomenon. A nuclear power plant's seismic risk should be calculated with the appropriate seismic failure correlation coefficient between the SSCs for a reasonable outcome. An accident scenario that has an enormous impact on a nuclear power plant's seismic risk was selected. Moreover, the probabilistic seismic response analyses of a nuclear power plant were performed to derive appropriate seismic failure correlations between SSCs. Based on the analysis results, the seismic failure correlation coefficient between SSCs was derived, and the seismic fragility curve and core damage frequency of the loss of essential power event were calculated. Results were compared with the seismic fragility and core damage frequency of assuming the seismic failure correlations between SSCs were independent and entirely dependent.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2510-2518
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• 2022

The main purpose of collecting and analyzing operating experience events is to look for insights to improve safety. The underlying assumption is the correlation and causality between events with different safety significances. The analysis of this assumption could be valuable to optimize operating experience feedback programs and to enhance safety. This paper analyses the correlation between events with different safety significances. Groups of events from six nuclear energy related databases are considered. The findings are that a correlation exists but with various levels and not as large or consistent as might be expected across different databases. These results might be the basis for further work to analysis causality, to find out how a similarity in causes influences the correlation, and finally to improve the operating experience program.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.12
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• pp.1625-1634
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• 2000

Verification of measurements is required for precise evaluation of turbine cycle performance in nuclear power plant. We assumed that initial acceptance data and design data of the plant could provide correlation information between performance data. The data can be used as sample sets for the correct estimation model of measurement value. The modeling was done practically by using regression model based on plant design data, plant acceptance data and verified plant performance data of domestic nuclear power plant. We can construct more robust performance analysis system for an operation nuclear power plant with this validation scheme.

• ETRI Journal
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• v.36 no.1
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• pp.99-105
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• 2014

This paper presents a new locomotion mode recognition method based on a transformed correlation feature analysis using an electromyography (EMG) pattern. Each movement is recognized using six weighted subcorrelation filters, which are applied to the correlation feature analysis through the use of six time-domain features. The proposed method has a high recognition rate because it reflects the importance of the different features according to the movements and thereby enables one to recognize real-time EMG patterns, owing to the rapid execution of the correlation feature analysis. The experiment results show that the discriminating power of the proposed method is 85.89% (${\pm}2.5$) when walking on a level surface, 96.47% (${\pm}0.9$) when going up stairs, and 96.37% (${\pm}1.3$) when going down stairs for given normal movement data. This makes its accuracy and stability better than that found for the principal component analysis and linear discriminant analysis methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1127-1136
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• 2021

In the field of power analysis attacks, electrical noise and misalignment of the power consumption trace are the major factors that determine the success of the attack. Therefore, several studies have been conducted to overcome this problem, and one of them is a signal processing method based on wavelet transform. Up to now, discrete wavelet transform, which can compress the trace, has been mostly used for power side-channel power analysis because continuous wavelet transform techniques increase data size and analysis time, and there is no efficient scale selection method. In this paper, we propose an efficient scale selection method optimized for power analysis attacks. Furthermore, we show that the analysis performance can be greatly improved when using the proposed method. As a result of the CPA(Correlation Power Analysis) and DDLA(Differential Deep Learning Analysis) experiments, which are non-profiling attacks, we confirmed that the proposed method is effective for noise reduction and trace alignment.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.296-297
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• 2006

In order to support wind power development, the wind resource database of Jejudo has been established by meteo-statistical analysis on meteorological-mast measurements of KIER. Analysis processes contain correlation of monthly wind speed and power-law exponent among neighboring sites, Measure-Correlated-Predict for long-term correlation, classification of exposure category using satellite image and so forth. It is found that the monthly variations of wind speed and power-law exponent depend on seasonal winds and characterize wind system of Jejudo.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.3
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• pp.246-255
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• 2023

Due to lack of hydrogen charging stations and hydrogen supply compared to the supply of hydrogen vehicles, social phenomena such as 2-hour queues and restrictions on charging capacity are occurring, which negatively affects the spread of hydrogen vehicles. In order to resolve these problems, it is essential to have a strategic operation of the hydrogen charging stations. To establish operational strategies, it is necessary to derive customer demand patterns and characteristics through the analysis of sales data. This study derived the demand patterns and characteristics of customers visiting hydrogen charging stations through data analysis from various perspectives, such as charging volume, charging speed, number of visits, and correlation with external factors, based on the hydrogen sales data of off-site hydrogen charging stations located in domestic residential areas.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.35-45
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• 2011

The Salsa20/12 stream cipher selected for the final eSTREAM portfolio has a better performance than software implementation of AES using an 8-bit microprocessor with restricted memory space, In the theoretical approach, the evaluation of exploitable timing vulnerability was 'none' and the complexity of side-channel analysis was 'low', but there is no literature of the practical result of power analysis attack. Thus we propose the correlation power analysis attack method and prove the feasibility of our proposed method by practical experiments, We used an 8-bit RISC AVR microprocessor (ATmegal128L chip) to implement Salsa20/12 stream cipher without any countermeasures, and performed the experiments of power analysis based on Hamming weight model.

• ETRI Journal
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• v.32 no.1
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• pp.102-111
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• 2010

Recently power attacks on RSA cryptosystems have been widely investigated, and various countermeasures have been proposed. One of the most efficient and secure countermeasures is the message blinding method, which includes the RSA derivative of the binary-with-random-initial-point algorithm on elliptical curve cryptosystems. It is known to be secure against first-order differential power analysis (DPA); however, it is susceptible to second-order DPA. Although second-order DPA gives some solutions for defeating message blinding methods, this kind of attack still has the practical difficulty of how to find the points of interest, that is, the exact moments when intermediate values are being manipulated. In this paper, we propose a practical second-order correlation power analysis (SOCPA). Our attack can easily find points of interest in a power trace and find the private key with a small number of power traces. We also propose an efficient countermeasure which is secure against the proposed SOCPA as well as existing power attacks.