Performance Evaluation of Real Power Quality Disturbances Analysis Using S-Transform

Abstract

Power quality is main issue because of the impact to electricity suppliers, equipments, manufacturers and user.To solve the power quality problem, an analysis of power quality disturbances is required to identify and rectify any failures on power system. Most of researchers apply fourier transform in power quality analysis, however the ability of fourier transform is limited to spectral information extraction that can be applied on stationary disturbances. Thus, time-frequency analysis is introduced for analyzing the power quality distubances because of the limitation of fourier transform. This paper presents the analysis of real power quality disturbances using S-transform. This time-frequency distribution (TFD) is presented to analyze power quality disturbances in time-frequency representation (TFR). From the TFR, parameters of the disturbances such as instantaneous of root mean square (RMS), fundamental RMS, total harmonic distortion (THD), total nonharmonic distortion (TnHD) and total waveform distortion (TWD) of the disturbances are estimated. The experimental of three phase voltage inverter and starting motor are conducted in laboratory to record the real power quality disturbances. The disturbances are recorded via data logger system which is mplemented using LabVIEW while the analysis is done using Matlab in offline condition. The results show that S-transform gives good performance in identifying, detecting and analyzing the real power quality disturbances, effectively.

An Accurate Classification Method of Harmonic Signals in Power Distribution System by Utilising S-Transform

“…Since in this research, all previous information that's been obtained from power quality signals gave good information, this classifier is suitable to be used for signal characterization. The utilization of rule-based classifier agreeing below requirements [12]: > and < (12) >= and < (13) In the meantime, a flow chart of the rule-based classifier for signal classification clearly shown in Figure 4. and are set according to results of numerous investigation of these signals.…”

“…In this stage, the expert knowledge is used to define the rule by disaggregating the disturbance [12]. The rule-based classifier of the proposed method is verified and according to the IEE Std 519:2014 and clearly show in Figure 4.…”

An Improved of Multiple Harmonic Sources Identification in Distribution System with Inverter Loads by Using Spectrogram

“…Thus, it is a crucial request to reduce or eliminate the harmonic pollution and the detection of harmonic sources is the first step towards enhancing the power quality of the system [4]- [5]. Meanwhile, in power distribution system, multiple harmonic sources can be found at utility side which known as upstream and downstream when harmonic sources located at customer side with a respect to a measurement point of point of common coupling (PCC) [6]- [8].…”

“…This paper proposes a high accuracy, fast estimation and costs efficient of a new multiple harmonic sources identification method with single-point measurement [8] at the PCC utilizing TFD which is spectrogram. The spectrogram is an appropriate technique that represents a signal in time and frequency representation and known as time-frequency representation (TFR) [8]-[15]- [17].…”

“…The spectrogram is an appropriate technique that represents a signal in time and frequency representation and known as time-frequency representation (TFR) [8]-[15]- [17]. From these the signals, spectral information can be monitored with changes of time.…”