• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1376-1385
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• 2017

This paper proposes a method for estimating the expected frequency of voltage swells caused by asymmetrical faults in a power system. Although voltage swell is less common than voltage sag, repeated swells can have severe destructive impact on sensitive equipment. It is essential to understand system performance related to voltage swells for finding optimal countermeasures. An expected swell frequency at a sensitive load terminal can be estimated based on the concept of an area of vulnerability (AOV) and long-term system fault data. This paper describes an effective method for calculating an AOV to voltage swells. Interval estimation for an expected swell frequency is also presented for effective understanding of system performance. The proposed method provides long-term performance evaluation of the frequency and degree of voltage swell occurrences.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.260-265
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• 1995

Based on a thermohydraulic estimation of the level swell and shrinkage of the nuclear steam generators, a fuzzy logic controller is designed and tested to handle the problem of controlling the level swell and its restoration. The estimation is used to form an artificial system which is nearly the opposite of the level swell and shrinkage and a PD type controller is designed to control this system. This controller is added to a PI type ordinary fuzzy logic controller to form the proposed controller which is tested through various experiments on a scaled-down steam generator. It is found to perform efficiently so that the divergence of the level to a low limit can be avoided.

• Journal of the Korean Society for Railway
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• v.16 no.4
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• pp.272-277
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• 2013

Power quality is a term that is now extensively used in power systems applications, and in this context the voltage, current, and phase angle are discussed widely. In particular, different algorithms that are capable of detecting the voltage sag and swell information in a real time environment have been proposed and developed. Voltage sag and swell play an important role in determining the stability, quality, and operation of a power system. This paper presents ANFIS (Adaptive Network based Fuzzy Inference System) models with different membership functions to build the voltage shape with the knowledge of known system parameters, and detect voltage sag and swell accurately. The performance of each method has been compared with each other/other methods to determine the effectiveness of the different models, and the results are presented.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.217-223
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• 2016

Outcome misclassification is widespread in classification problems, but methods to account for it are rarely used. In this paper, the problem of inference with misclassified multinomial logit data with a large number of multinomial parameters is addressed. We have had a significant swell of interest in the development of novel methods to infer misclassified data. One simulation study is shown regarding how seriously misclassification issue occurs if the number of categories increase. Then, using the group lasso regression, we will show how the best model should be fitted for that kind of multinomial regression problems comprehensively.

• Journal of IKEEE
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• v.25 no.4
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• pp.710-715
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• 2021

Power line signal can show disturbances due to various causes. Typical anomalies are temporary sag/swell of the amplitude, flat topped signal, and harmonic distortions. The disturbances need to be detected and treated properly for the quality of the power signal. In this study, the power disturbances are detected using the inflection points (IP). The inflection points are defined as points where local maxima/minima or the slope changes occur. The power line signal has a fixed IP pattern since it is basically sinusoidal, and it may have additional inflection points if there is any disturbance. The disturbance is detected by comparing the IP patterns between the normal signal and distorted signal. In addition, by defining a cost function, the time instant where the disturbance happens can be decided. The computer simulation shows that the proposed method is useful for the detection of various disturbances. The simple sag or swell signal only shows the amplitude changes at the detected inflection points. However, the flat top signal and harmonically distorted signal produce additional inflection points and large values in the cost function. These results can be exploited for the further processing of disturbance classification.

• Journal of Ship and Ocean Technology
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• v.10 no.4
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• pp.34-48
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• 2006

The visual observation of wave condition depends on the observer's skill and experience. Also, the environmental conditions such as light and cloud heavily influence the visual measurement. In the speed test of sea trial, the wave measurement should be objective and accurate. In this paper, the problems of visual measurement and their effects on speed test are described. To overcome those problems, we developed the wave measurement system using commercial marine X-band radar, WaveFinder. The system installed at inland base was calibrated by waverider buoy and then the system's operability was defined. Onboard tests had also been performed three times for formal wave measurement to correct the ship speed. The results illustrated very good agreement with visual observation by experts. It can be concluded that the system would be useful to measure wave and swell information for the sea trial, irrespective of day and night.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.74-80
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• 2001

Because of ocean waves, swell, steering corrections, etc, the hydrophones of a towed array will not live along a straight line. However the degradation of bearing estimation performance occurs when beamforming is carried out on the hydrophone outputs of an acoustic towed array which is not straight. So it is required to estimate the shape of the array for the improved beamformer output. In this paper, an iterative array shape estimation technique is presented, which is based on the use of the least squares polynomial fitting to the data from heading sensors. The estimation error and the influence of deformations on the performance of the conventional beamformer output are investigated. Finally, the suggested method is applied to the real system in order to investigate the applicability.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.286-287
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• 2011

Kalman filter(KF) algorithm is a very useful application being used in many engineering fields. Through the KF, the next time step's estimation can be almost simultaneously calculated by the recursive least square optimization method with the present measurement data. It provides us with the superior detection performance of power quality events. This paper deals with the concrete programming example of KF to detect various kinds of PQ disturbances, such as voltage sag, swell, harmonics, voltage fluctuation and Frequency variation.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.445-451
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• 2007

Voltage quality problems such as voltage sag, swell, flicker, undervoltage, and overvoltage have been of great concern for both utilities and customers over the last decade. In this paper, a new approach based on the $H_{\infty}$ algorithm to monitor voltage disturbances is presented. The key idea of this approach is to estimate the amplitude of the fundamental component of distorted and noisy voltage waveform instantaneously, and then the information can be extracted from the estimated envelope to identify and classify different voltage related power quality problems. The $H_{\infty}$ algorithm is characterized by a fast tracking, unlike that of existing techniques. The $H_{\infty}$ algorithm outperforms the Kalman Filter (KF) by its fast convergence and robust tracking performance against non-Gaussian noise. The paper investigates the effects of various types of noise on the performance of the $H_{\infty}$ algorithm. Digital simulation results confirm the validity and accuracy of the proposed method. The proposed $H_{\infty}$ algorithm is examined by tracking the flicker produced by a resistance welder simulated in the PSCAD/EMTDC package.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.42-46
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• 2012

With the development of industry, more large-scale non-linear loads are added to existing power systems and they cause the serious power quality (PQ) problems to the nearby sensitive installations more and more. To protect the important loads and mitigate the impact of PQ disturbances on them, various compensating devices are installed. One of the most important control skills used in the compensating equipment at the load side is how fast they can recognize or detect the discontinuous abnormal PQ events from the normal voltage signal. This paper deals with two estimation methods for the fast detection and tracking of general PQ disturbances: Teager Energy Operator (TEO), which is a non-linear operator and used for a short time energy calculation, and Kalman Filter (KF), which is one of the most universally used estimation techniques. And it is also shown how to apply the TEO and the KF to detect the PQ disturbances such as voltage sag, swell, interruption, harmonics and voltage fluctuation.