Detection of power quality disturbances using discrete wavelet transform

Dekhandji, Fatma Zohra

doi:10.1109/icee-b.2017.8192080

Cited by 30 publications

(10 citation statements)

References 9 publications

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“…In other words, high-scale signal analysis is not necessary because it gives poor temporal positioning. Suppose we have a special type of mother wavelet with L filter coefficient, h(n) and g(n), which form a family of wavelet functions ϕ(t) and scale functions ψ(t), respectively [13].…”

Section: Wavelet Transform As a Detection And Location Toolmentioning

confidence: 99%

Detecting and Locating Power Quality Issues by Implementing Wavelet Transform

Asadi¹,

Harikandeh²,

Hamzenia³

2021

IJSEA

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Lack of power quality imposes many costs on large and small consumers every year. Therefore, considering the importance of power quality in today's industries, this article examines the issue of detection and location of various power quality issues. DWT discrete wavelet transform is investigated in this paper. The signals under the perturbations are written to the field and the start and end times of the perturbation are obtained and compared with the real time, and the accuracy of the measurements is confirmed by repetitions.

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Section: Wavelet Transform As a Detection And Location Toolmentioning

confidence: 99%

Detecting and Locating Power Quality Issues by Implementing Wavelet Transform

Asadi¹,

Harikandeh²,

Hamzenia³

2021

IJSEA

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“…In the papers presented in [42,[53][54][55][56][57][58][59][60][61], their main theme coincides and is to classify the faults that can be obtained from the analysis of the voltage wave through WT. Broadly speaking, it can be highlighted that they obtain the range of frequency, amplitude, time of action, waveform, etc.…”

Section: Power Qualitymentioning

confidence: 99%

Wavelet Transform Analysis to Applications in Electric Power Systems

Oliveira¹,

Reversat²,

Reynoso³

2019

Wavelet Transform and Complexity

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The wavelet transform has received great importance in the last years on the power system analysis because the multi-resolution analysis presents proprieties good for the transient signal analysis. This chapter presents a review on main application of wavelet transform in electric power systems. The study areas have been classified as power system protection, power quality disturbances, power system transient, partial discharge, load forecasting, faults detection, and power system measurement. The areas in which more works have been developed are the power quality and protections field, where both cover 51% of the articles analyzed.

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“…where X 1 is the RMS value fundamental frequency component and X i is the RMS value of other harmonics components present in the signal %Error = Actual − EWT/DWT Actual × 100 (10) Since the minimum frequency present in voltage is 550 Hz in most of the loading condition; therefore, an analysis of RMS values obtained by EWT, DWT & WPT is shown in Table 5. For the ease of comparison the magnitude less than threshold value of 3% is considered.…”

Section: Analysis Of Pq Indices At Different Loading Conditionsmentioning

confidence: 99%

“…Similarly for phase currents, the percentage error in RMS value is calculated for EWT, DWT & WPT using (9) and (10) which is shown in Tables 6 and 7.…”

Section: Current Rmsmentioning

confidence: 99%

“…In paper [8], the analysis of distorted current signal has been presented with the help of WT and artificial intelligence. Detection and categorisation of PQ disturbances have been done with the help of discrete WT (DWT) and wavelet networks [9,10]. In [11], authors have reviewed the application of WT for detection and analysis of PQ Disturbances.…”

Section: Introductionmentioning

confidence: 99%

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