Denoising Power Quality Signal Using Savitzky-Golay Based on Virtual Instrument

2013 ◽  
Vol 655-657 ◽  
pp. 974-977
Author(s):  
Han Sheng Yang
Keyword(s):  
Power Quality ◽  
Virtual Instrument ◽  
Classification Rate ◽  
Denoising Method ◽  
Quality Signal ◽  
Power Quality Monitoring ◽  
Power Quality Disturbance ◽  
Detection And Localization ◽  
Transient Power Quality

In power quality monitoring system, there are unavoidably existing various kinds of noises in collected data，the presence of noise may result in increased false classification rate, denoising is an extremely important work for detection and classification of power quality disturbances. In order to improve the denoising result of power quality signal, an denoising method for power quality signal using Savitzky-Golay is proposed. Numerical results show that the proposed method can eliminate the influence of noise components and implement transient power quality disturbance detection and localization, thus providing good foundations for transient power quality disturbance monitoring under noise environment.

Time-Frequency Analysis Method in the Transient Power Quality Disturbance Analysis Application

2014 ◽  
Vol 700 ◽  
pp. 99-102
Author(s):  
Meng Da Li ◽  
Yu Bo Duan ◽  
Yan Wang
Keyword(s):  
Power Quality ◽  
Signal Interference ◽  
Time Frequency ◽  
Quality Signal ◽  
Power Quality Disturbance ◽  
Analysis Application ◽  
Disturbance Analysis ◽  
Realistic Significance ◽  
Transient Power Quality

This paper uses the method of S transformation to test the starting time, the end of the time, frequency and amplitude characteristics of common transient power quality signal disturbance. Through error analysis and simulation show that this method can accurately determine the disturbance occurred time and duration, and the identification and determination of disturbance can be simple and intuitive. It has the practical value and realistic significance to power quality signal interference analysis.

Classification of Power Quality Disturbance Based on Continuous S-Transform-Windowing Technique (CST-WT) and ANOVA as a Feature Selection

2015 ◽  
Vol 785 ◽  
pp. 368-372 ◽  
Author(s):  
Kamarulazhar Daud ◽  
Ahmad Farid Abidin ◽  
Harapajan Singh Nagindar Singh ◽  
Mohd Najib Mohd Hussain
Keyword(s):  
Feature Selection ◽  
Power Quality ◽  
Transient Signal ◽  
New Approach ◽  
Power Quality Monitoring ◽  
S Transform ◽  
Power Quality Disturbance ◽  
Before And After ◽  
Windowing Technique

This paper was conducted in order to identify and classify the different types of Power Quality Disturbances (PQD) based on a new approach the Analysis Of Variance (ANOVA). ANOVA is used as feature selection for the PQD parameters. The datum of PQD from the PSCAD/EMTDC® simulation and Power Quality Monitoring has been validated before feature extraction analysis can be commenced. The obtained datum is then analyzed by using Windowing Technique (WT) based on Continuous S-Transform (CST) to extract the features and its characteristics. Moreover, the study focuses an important issue concerning the identification of PQD selection, detection and classification. The feature and characteristics of three types of signal such as sag, swell, and transient signal are obtained. The outcome of the analysis shows that a new approach framework ANOVA-Based Before and After Neural Network (NN) classification has a slightly increases to 15-25% in term of classification of PQD.

Design of Remote Power Quality Monitoring System Based on LabVIEW

2011 ◽  
Vol 143-144 ◽  
pp. 917-920
Author(s):  
Geng Hui Zhu ◽  
Jiao Xia Wang
Keyword(s):  
Power Quality ◽  
Monitoring System ◽  
Conventional Method ◽  
Virtual Instrument ◽  
Quality Monitoring ◽  
Network Technology ◽  
Power Quality Monitoring ◽  
Software And Hardware ◽  
The Way

The monitoring of power quality is the foundation and prerequisite of its improvement. There are a lot of disadvantages in the conventional method of power quality monitoring, the adoption of the virtual instrument and network technology can overcome these disadvantages very well. Remote power quality monitoring system based on LabVIEW was put forward, as well as the way of the combination of software and hardware and the realization procedure is illustrated in detail in this paper. Then the merits of this way are mentioned, and the additional functions that can be further developed. This paper provides a more convenient way for the realization of remote power quality monitoring

A Fuzzy–Expert System For Classification Of Short Duration Voltage Disturbances

2012 ◽  
Author(s):  
Ghafour Amouzad Mahdiraji ◽  
Azah Mohamed
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Short Duration ◽  
Automated Detection ◽  
Voltage Sag ◽  
Fuzzy Expert System ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Fast Fourier Transform Analysis

Satu aspek penting dalam penilaian kualiti kuasa adalah pengesanan dan pengkelasan gangguan kualiti kuasa secara automatik yang memerlukan penggunaan teknik kepintaran buatan. Kertas kerja ini membentangkan penggunaan sistem pakar-kabur untuk pengkelasan gangguan voltan jangka masa pendek yang termasuk lendut voltan, ampul dan sampukan. Untuk memperolehi sifat unik bagi gangguan voltan, analisis jelmaan Fourier pantas dan teknik purataan punca min kuasa dua digunakan untuk menentukan parameter gangguan seperti tempoh masa, magnitud voltan pmk maksimum dan minimum. Berasaskan pada parameter ini, sebuah sistem pakar–kabur telah dibangunkan dengan mengset aturan kabur yang menimbangkan lima masukan dan tiga keluaran. Sistem ini direka bentuk untuk mengesan dan mengkelaskan tiga jenis gangguan voltan tempoh masa pendek dengan menentukan sama ada gangguan adalah gangguan ketika, gangguan seketika dan bukan gangguan lendut, ampul dan sampukan. Untuk mengesahkan kejituan sistem yang dicadangkan, ia telah diuji dengan gangguan voltan yang diperolehi dari pengawasan. Keputusan ujian menunjukkan bahawa sistem pakar–kabur yang dibangunkan telah memberikan kadar pengkelasan yang betul sebanyak 98.4 %. Kata kunci: Kualiti kuasa, sistem pakar–kabur, lendut, ampul dan sampukan One of the important aspects in power quality assessment is automated detection and classification of power quality disturbances which requires the use of artificial intelligent techniques. This paper presents the application of fuzzy–expert system for classification of short duration voltage disturbances which include voltage sag, swell and interruption. To obtain unique features of the voltage disturbances, fast Fourier transform analysis and root mean square averaging technique are utilized so as to determine the disturbance parameters such as duration, maximum and minimum rms voltage magnitudes. Based on these parameters, a fuzzy-expert system has been developed to set the fuzzy rules incorporating five inputs and three outputs. The system is designed for detecting and classifying the three types of short duration voltage disturbances, so as to determine whether the disturbance is instantaneous, momentary and non sag, swell and interruption. To verify the accuracy of the proposed system, it has been tested with recorded voltage disturbances obtained from monitoring. Tests results showed that the developed fuzzy–expert system gives a correct classification rate of 98.4 %. Key words: Power quality, fuzzy–expert system, sag, swell and interruption.

Study on Transient Power Quality Disturbance and Detection Method

2012 ◽  
Vol 203 ◽  
pp. 313-316
Author(s):  
Bo Yong Lu
Keyword(s):  
Power Quality ◽  
Detection Method ◽  
Electrical Energy ◽  
Control Methods ◽  
Testing Methods ◽  
Power Sector ◽  
Power Quality Disturbance ◽  
Scientific Testing ◽  
Transient Power Quality

Nowadays, in electrical energy, transient power quality disturbance issue is one of the “stubborn problems” that plagued the power sector and users. This paper focuses on analyzing the causes and effects of transient power quality disturbance, sequentially finds out scientific testing methods and sums up its control methods.

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