Wavelet-transform-based algorithm for harmonic analysis of power system waveforms

Pham, Van‐Long; Wong, Kit Po

doi:10.1049/ip-gtd:19990316

Cited by 154 publications

(51 citation statements)

References 9 publications

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“…Approximate coefficients will have maximum magnitude as it contains fundamental component in A6. As a general rule, wavelets with large numbers of coefficients present lower spectral leakage than wavelets with small numbers of coefficients, and are better suited for analysis of harmonic components [20]. Here the decomposition is done into six levels only.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Wavelet based Power Quality Monitoring in Grid Connected Wind Energy Conversion System

Jain¹,

Jain²,

Nema³

2014

IJCA

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Recently renewable energy resources especially wind power integration has been far increased in the electric power distribution system. To utilize wind power more effectively, wind energy conversion system is interfaced to grid through power electronics interfaces. In this paper, monitoring of various power quality disturbances at the point of common coupling in grid connected wind energy conversion system have been done. Discrete wavelet transform and wavelet energy function are used for detection of power quality disturbances. The grid connected wind energy conversion system is simulated in MATLAB environment. Power quality disturbances such as voltage sag, voltage swell, interruption and harmonics are investigated. A new diagnostic method in which signal is processed using discrete wavelet transform and wavelet energy function is proposed. Simulation results show the usefulness of the proposed method to find out the power quality disturbances in grid-connected wind energy conversion system accurately and quickly. Voltage signal extracted directly at the point of common coupling is used for detection of power quality disturbances. KeywordsDiscrete wavelet transforms (DWT), power quality (PQ), total harmonic distortion (THD), wavelet energy, wind energy conversion system (WECS).

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Wavelet based Power Quality Monitoring in Grid Connected Wind Energy Conversion System

Jain¹,

Jain²,

Nema³

2014

IJCA

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“…Most commonly, methods based on the Discrete Fourier Transform (DFT) are used but, for example, the Discrete Wavelet Transform (DWT) is also sometimes applied as well (Pham & Wong, 1999), (Gaouda et al, 2002). In Section 3.1, the application of the DFT for harmonic estimation according to the standard (IEC 61000-4-7, 2009) is described.…”

Section: Frequency Domain Methodsmentioning

confidence: 99%

Methods for Estimation of Voltage Harmonic Components

Radil¹,

Ramos²

2011

Power Quality

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“…The WT is able to extract time and frequency information at the same time from the original signal [23][24][25][26]. The Discrete Wavelet Transform (DWT) of a signal is defined as: The Results of DWT depend on the mother wavelet.…”

Section: Wavelet Transformmentioning

confidence: 99%

Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection

Lee¹,

Kim²,

Oh³

et al. 2015

Journal of Electrical Engineering and Technology

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-An algorithm for fault detection and classification method for wide-area protection in Korean transmission systems is proposed. The modeling of 345-kV and 765-kV Korean power system transmission networks using the Electro Magnetic Transient Program -Restructured Version (EMTP-RV) is presented and the algorithm for fault detection and classification in transmission lines is developed. The proposed algorithm uses the Wavelet Transform (WT) and Singular Value Decomposition (SVD). The Singular value of Approximation coefficient (SA) and part Sum of Detail coefficient (SD) are introduced. The characteristics of the SA and SD at the fault conditions are analyzed and used in the algorithm for fault detection and classification. The validation of the proposed algorithm is verified by various simulation results.

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Wavelet-transform-based algorithm for harmonic analysis of power system waveforms

Cited by 154 publications

References 9 publications

Wavelet based Power Quality Monitoring in Grid Connected Wind Energy Conversion System

Wavelet based Power Quality Monitoring in Grid Connected Wind Energy Conversion System

Methods for Estimation of Voltage Harmonic Components

Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection

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