Voltage notch detection and localization in power quality signals in phase space

Kolenc, Marko; Plesnik, Emil; Tasič, J.F.; Zajc, Matej

doi:10.1109/eurocon.2013.6625213

Cited by 2 publications

(5 citation statements)

References 16 publications

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“…The third category according to the type of PQD is associated with voltage notches. These studies mainly deal with the detection of notches in voltage signals [189,190,194,205,206,209]. The characterization of voltage notches is also performed in some cases.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Therefore, a set of thresholds are generally used when dealing with the detection and classification of multiple PQDs. Moreover, segmentation is less [136,139,142,143,145,153,159,160,164,170,182] 20 [191,194,196,197,203,204,206 [188,192,198,199,201,208 [187,190,195,200,206,209] [189,191,193,200,201,205,207,211] Page 12 of 37 frequently used for specific disturbances, as can be seen in the literature for voltage sags and notches in Table 7.…”

Section: Segmentationmentioning

confidence: 99%

“…For voltage sags, techniques used for detection include adaptive notch filter [136], KF [138,156,161], integrator model [155], harmonic footprint [160], ICA [162], and Goertzel algorithm [166]. When the interest of the study is the characterization of voltage notches, detection has been conducted using the Teager energy operator and threshold algorithm [201], and the Euclidean norm [206,209].…”

Section: Detectionmentioning

confidence: 99%

“…The product of the notch depth times the width of the notch [12] It allows quantifying the severity of notches [190,191,194,201,209,210] 3 Number of notches per cycle Occurrences of notch switching disturbances in one cycle It allows quantifying the aggregate severity of notches and identifying the producing converter [37,87,187,190,193,195,200,201,[203][204][205][206][207]209] Page 29 of 37…”

Section: Areamentioning

confidence: 99%

See 3 more Smart Citations

A systematic review of real-time detection and classification of power quality disturbances

Navarro

Agudelo-Martínez²,

Trujillo

et al. 2023

Prot Control Mod Power Syst

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This paper offers a systematic literature review of real-time detection and classification of Power Quality Disturbances (PQDs). A particular focus is given to voltage sags and notches, as voltage sags cause huge economic losses while research on voltage notches is still very incipient. A systematic method based on scientometrics, text similarity and the analytic hierarchy process is proposed to structure the review and select the most relevant literature. A bibliometric analysis is then performed on the bibliographic data of the literature to identify relevant statistics such as the evolution of publications over time, top publishing countries, and the distribution by relevant topics. A set of articles is subsequently selected to be critically analyzed. The critical review is structured in steps for real-time detection and classification of PQDs, namely, input data preparation, preprocessing, transformation, feature extraction, feature selection, detection, classification, and characterization. Aspects associated with the type of disturbance(s) addressed in the literature are also explored throughout the review, including the perspectives of those studies aimed at multiple PQDs, or specifically focused on voltage sags or voltage notches. The real-time performance of the reviewed tools is also examined. Finally, unsolved issues are discussed, and prospects are highlighted.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Segmentationmentioning

confidence: 99%

Section: Detectionmentioning

confidence: 99%

Section: Areamentioning

confidence: 99%

See 2 more Smart Citations

A systematic review of real-time detection and classification of power quality disturbances

Navarro

Agudelo-Martínez²,

Trujillo

et al. 2023

Prot Control Mod Power Syst

View full text Add to dashboard Cite

show abstract

“…Frequency and time-frequency domain methods are based on data transformation, such as Fourier transform, or wavelet transform [10]. Another frequently used transform-based method is space projection, such as phase space reconstruction [11]. Once the time series is transformed into a feature-based representation, a classification stage is performed.…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Voltage Notches using Support Vector Machine

Qi¹,

Zyabkina²,

Martinez³

et al. 2021

REPQJ

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This paper presents a comprehensive framework for voltage notch analysis and an automatic method for notch detection using a nonlinear support vector machine (SVM) classifier. A comprehensive simulation of the notch disturbance has been conducted to generate a diverse database. Based on domain knowledge and properties of power quality disturbances (PQDs), a set of characteristic features is extracted. After feature extraction, a set of most descriptive features has been selected with decision tree (DT) algorithm, and a nonlinear SVM classifier has been trained. Finally, the detection efficiency of the trained model is presented and discussed.

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Voltage notch detection and localization in power quality signals in phase space

Cited by 2 publications

References 16 publications

A systematic review of real-time detection and classification of power quality disturbances

A systematic review of real-time detection and classification of power quality disturbances

Automatic Detection of Voltage Notches using Support Vector Machine

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