Detection and Classification of Complex Power Quality Disturbances Using Hilbert Transform and Rule Based Decision Tree

Saini, Rahul; Mahela, Om Prakash; Sharma, Deepak

doi:10.1109/poweri.2018.8704427

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…This technique is efficient for identifying various single and multiple PQ disturbances under noisy conditions. In [10], the authors designed a method for detecting and classifying MPQ disturbances by the application of HT and RBDT. The voltage signal with MPQ disturbance is processed using the HT and absolute values of output are computed, which is assigned the name H-index.…”

Section: Related Research Workmentioning

confidence: 99%

Identification and Classification of Multiple Power Quality Disturbances Using a Parallel Algorithm and Decision Rules

Swarnkar¹,

Mahela²,

Khan³

et al. 2022

Energy Engineering

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A multiple power quality (MPQ) disturbance has two or more power quality (PQ) disturbances superimposed on a voltage signal. A compact and robust technique is required to identify and classify the MPQ disturbances. This manuscript investigated a hybrid algorithm which is designed using parallel processing of voltage with multiple power quality (MPQ) disturbance using stockwell transform (ST) and hilbert transform (HT). This will reduce the computational time to identify the MPQ disturbances, which makes the algorithm fast. A MPQ identification index (IPI) is computed using statistical features extracted from the voltage signal using the ST and HT. IPI has different patterns for various types of MPQ disturbances which effectively identify the MPQ disturbances. A MPQ time location index (IPL) is computed using the features extracted from the voltage signal using ST and HT. IPL effectively identifies the initiation and end of PQ disturbances and thereby locates the MPQ events with respect to time. Classification of MPQ disturbances is performed using decision rules in both the noise-free and noisy environments with a 20 dB noise to signal ratio (SNR). The performance of the proposed hybrid algorithm using ST and HT with rule-based decision tree (RBDT) is better compared to the ST and RBDT techniques in terms of accuracy of classification of MPQ disturbances. MATLAB software is used to perform the study.

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Section: Related Research Workmentioning

confidence: 99%

Identification and Classification of Multiple Power Quality Disturbances Using a Parallel Algorithm and Decision Rules

Swarnkar¹,

Mahela²,

Khan³

et al. 2022

Energy Engineering

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show abstract

“…The rapid development of the country and the rapidly improving lifestyle of the people, and the increasing development and use of modern electrical equipment also contribute to the problems related to power quality [1]. Power quality (PQ) disturbance is a phenomenon in power line consisting of voltage sag, swell, harmonics, momentary interruption, flicker, notch, spike, and oscillatory transient [2]- [4]. Among the sources of the occurrence of disturbances are energization of heavy loads, starting of heavy loads such as industrial motor, lightning strikes, use of nonlinear load, and power system faults [5].…”

Section: Introductionmentioning

confidence: 99%

Border Distortion Minimization for Multiple PQ Disturbances - Stockwell Transformation Modification

Marzuki,

Bin-Abidin,

Bin-Jusoh

et al. 2023

IJCDS

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Signal processing is a method used in electrical engineering to analyse and modify signals hence improving the quality. In power quality classification, signal processing is employed as an alternative for better detection of disturbances. This is done with the application of some extraction features to amplify the differences of each disturbance. However, due to border distortion effect, signal processing results usually encounter problem. Border distortion is the aberration in results due to tempering, appearing at the starting and the ending of the waveform when signals are processed and modified using signal processing techniques. This leads to misclassification of PQ disturbances, causing problems in determining the correct mitigation technique to be taken to reduce power quality disturbances. In this paper, minimization of border distortion of features extraction resulting from Stockwell transform will be discussed via the implementation of Hanning Taper and polynomial fitting. The discussion involves the three types of multiple power quality disturbances which are voltage sag with harmonics, voltage sag with transient, and harmonics with transient. The modification technique in Stockwell transform will be analysed to prove the accuracy and the consistency in features extraction. In this study, the border distortion effect was successfully reduced by an average of 88.704%.

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Hybrid signal processing technique to design smart meter for detection of voltage amplitude disturbances

Singh,

Sharma,

Mahela

2022

Active Electrical Distribution Network

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Detection and Classification of Complex Power Quality Disturbances Using Hilbert Transform and Rule Based Decision Tree

Cited by 10 publications

References 7 publications

Identification and Classification of Multiple Power Quality Disturbances Using a Parallel Algorithm and Decision Rules

Identification and Classification of Multiple Power Quality Disturbances Using a Parallel Algorithm and Decision Rules

Border Distortion Minimization for Multiple PQ Disturbances - Stockwell Transformation Modification

Hybrid signal processing technique to design smart meter for detection of voltage amplitude disturbances

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