Power quality detection and classification using wavelet transform-multiresolution analysis / Mohd Shaihan Jusoh
This thesis presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The main objective of this thesis is to classify and categorize the power quality disturbances by establishing its unique pattern of power quality disturbances from the...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/79528/1/79528.PDF |
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| Summary: | This thesis presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The main objective of this thesis is to classify and categorize the power quality disturbances by establishing its unique pattern of power quality disturbances from the deviation of energy curves. Wavelet transform and multiresolution analysis is one of the techniques to classify and categorize power quality disturbance. Even though the main concern of this project is to classify and categorize power quality problems, it is being concentrated with sag and swell problems. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal. Wavelet transform will be used to detect the power quality disturbance while the multiresolution analysis will categorize and classify them. |
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