Sang-Wook Sohn

Algorithm for screening PMU data for power system events

Wide Area Monitoring Systems (WAMS) are a Smart Grid technology which can enhance real-time situational awareness for power sytem operators. WAMS are created from a network of synchronized measurement devices taking voltage and current measurements from the power system. This network is also known as a synchrophasor network. A synchrophasor network was created at the University of Texas at Austin to obtain real power system measurements for power system analysis. The network is continuously operating and recording voltage phasor data (voltage magnitude, angle, and frequency) at a rate of 30 data points per second. Because of the high volume of PMU data generated it is difficult to detect and analyze power system events of interest. To help power system operators more easily monitor the power system and easily detect events in PMU data, two different types of methods were created to automatically screen the data for events. The first method screens a small window of PMU voltage data and detects events based on a variety of techniques. The second method is an off-line method that detects events based on the magnitude of low frequency oscillations in PMU voltage data.

Seismic Noise Reduction Using Micro-Site Array Stacking

Abstract - This paper presents a new approach to improve the signal to noise ratio (SNR) for local seismic disaster preventing system in densely populated area. The seismic data measured in the local site includes various sensing noises (offset or measurement noise) and man-made/natural noises (road and rail traffic noise, rotating or hammering machinery noise, human activity noise such as walking and running, wind/atmospheric pressure-generated noise, etc.). These additive noises are different in time and frequency characters. The proposed method uses 3-stages processing to reduce these different additive noises. In the first stage, misalignment offset noise are diminished by time average processing, and then the second and third stages, coherent/incoherent noises such as man-made/natural noises are suppressed by array stacking. In addition, we derived the theoretical equation of the SNR gain improved by the proposed method. To evaluate the performance of the proposed method, computer simulations were performed with real seismic data and test equipment generated data as the input.Key Words : Earthquake event, Seismic noise, Signal to noise ratio, Array processing, Stacking†Corresponding Author : Dept. of Electronic Engineering, Dong-Eui University, KoreaE-mail : hchoi@deu.ac.kr* HVDC CP Accepted : December 20, 2013

A singular point detection and localization of power quality disturbance using filter bank and the residuals of adaptive filter

It is very important to detect power quality disturbances effectively in power quality monitoring. In industrial and commercial power systems, voltage sags, voltage swells, transients, and interruptions are main disturbances which affect sensitive equipments. This paper presents a signal processing technique which combines filter bank system and adaptive filter for power quality disturbances detection and localization. In this method, the filter bank system which has binary tree structure is designed for decomposing input power signal to subband signal components. In each subband, adaptive filters are operated as predictor, and the residual values of each adaptive predictor are used to detect power quality disturbances. The usefulness of the proposed method is demonstrated by synthesized signals harmonically.

Validation of distribution level measurements for power system monitoring and low frequency oscillation analysis

The University of Texas at Austin introduced the Independent Synchrophasor Network in order to monitor events and analyze low frequency oscillations from the electric power grid through PMU measurements taken at customer level voltage (120 V). The purpose of this paper is to present validation of the quality of these distribution level measurements for power system monitoring and analysis. Three different steps are used in the validation process. In the first step, the distribution voltage phase angle measurements are plotted with and compared to the state estimated transmission level voltage phase angle. The second step is the comparison of distribution level PMU measurements to transmission level PMU measurements during a power system transient response. The frequency, voltage magnitude, and voltage phase angle are analyzed during a unit trip event. In the final step, the modal frequency and damping estimates are used to illustrate the accuracy of distribution measurements as representative of the power systems ambient response. Because of the location of the PMUs within the network, it will also be possible to measure the effects of wind power on the rest of the grid.

Subband IPNLMS Adaptive Filter for Sparse Impulse Response Systems

In adaptive filtering, the sparseness of impulse response and input signal characteristics are very important factors of it`s performance. This paper presents a subband improved proportionate normalized least square (SIPNLMS) algorithm which combines IPNLMS for impulse response sparseness and subband filtering for prewhitening the input signal. As drawing and combining the advantage of conventional approaches, the proposed algorithm, for impulse responses exhibiting high sparseness, achieve improved convergence speed and tracking ability. Simulation results, using colored signal(AR(4)) and speech input signals, show improved performance compared to fullband structure of existing methods.

Subband Affine Projection Algorithm Using Variable Step Size

In applications with highly correlated inputs or long length of filter, adaptive filters suffer from slow convergence and large steady-state error. Affine projection algorithms based on the subband structure and step size controlling are good solutions for these problems. In this paper, we propose a new subband affine projection algorithm with variable step size. Experimental results on highly correlated inputs produce faster convergence, lower misadjustment error, and smaller complexity than conventional methods based on the fullband structure

Filter bank based technique for flicker signals detection and estimation of power signals

Voltage fluctuations are one of the power quality problems, which cause light flickers. Generally, voltage fluctuations are described as an amplitude modulation (AM). To determine the flicker severity, the flickermeter concept was developed in an IEC 61000-4-15 standard. Flickermeter of IEC 61000-4-15 as an international standard for flicker measurement recommends square demodulation method to detect flicker signals. This paper suggests a new effective method using filter bank to detect and estimate flicker signals, which is effective in comparison with square demodulation method. For the accurate detection of flicker signals, the filter bank is designed with a full consideration of the spectrum characteristics of AM signals. The frequency and magnitude of the detected signals by the filter bank are estimated using recursive method. Computer simulations were performed on synthesized signals to prove validity of the proposed method.

Subband Adaptive Algorithm for Convex Combination of LMS based Transversal Filters

Convex combination of two adaptive filters is an efficient method to improve adaptive filter performances. In this paper, a subband convex combination method of two adaptive filters for fast convergence rate in the transient state and low steady state error is presented. The cost function of mixing parameter for a subband convex combination is defined, and from this, the coefficient update equation is derived. Steady state analysis is used to prove the stability of the subband convex combination. Some simulation examples in system identification scenario show the validity of the subband convex combination schemes.

Singular point detection of time-varying power events using filter banks and adaptive filters

The detection of disturbances in power signals is important to prevent damage to electrical machines. The disturbance waveforms contain singular points where events have occurred. This paper presents a method to detect singular points in a power quality disturbance waveform using filter banks and adaptive filters. The proposed method decomposes the input disturbance signal using a filter bank system of non-tree structure. The non-tree filter bank is designed to separate high frequencies to reduce spectral leakage. An adaptive filter is then used to predict the decomposed signal. The error signal from the adaptive filter becomes the residual signal. The energy of the error signal is used to detect singular points.

Subband adaptive convex combination of two NLMS based filters for sparse impulse response systems

It is well known, combination scheme is suitable for improving the performance of adaptive algorithms. In this paper, we propose a subband combination scheme for sparse impulse response systems. The combination is carried out in subband domain. In this convex combination, SIPNLMS and SNLMS are derived for fast convergence and small steady state error respectively. And mixing parameters are described by minimum mean square error and stochastic gradient algorithm. In adaptive system identification scenario, the advantages of this proposed method are illustrated.