Classification real power quality disturbance analysis using wavelet / Mohd Faisal Zulkapli
Power quality monitoring is an important thing to the electric utilities and many industrial power customers. Service reliability and quality of power has become an important concern for many industrial facilities, especially with the increasing sensitivity of electronic equipment and automated cont...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2007
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| Online Access: | https://ir.uitm.edu.my/id/eprint/84560/1/84560.pdf |
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| Summary: | Power quality monitoring is an important thing to the electric utilities and many industrial power customers. Service reliability and quality of power has become an important concern for many industrial facilities, especially with the increasing sensitivity of electronic equipment and automated controls. Power quality may occur in each of machinery equipments manifested in voltage, current or mal-operation in devices. Power Quality can be best defined as any power problem manifested in voltage, current, or disoperation of customer equipment. In response to this dilemma, the waveform contains the event will be classified. This is done by using the wavelet technique to doing the classification. This project was focus on three famous types of power quality disturbance which is voltage sag, transient and harmonic. This project also include the software development which is the program have the ability to detect automatically the type of power quality disturbance. This project will discuss the wavelet transformation in attempt to determine power quality disturbance according to the resulting original waveform from the Wavelet application. In the response of this problem waveform contains the event will be transform into wavelet signal to doing the classification process. Real data of power quality disturbance have been used in this project. After tested the real data the rules have been made to make the classification of type's power quality disturbance automatically. The important part of transformation process is a with choosing the appropriate detail and types of wavelet signal which for this project the Daubechies families have been choose as the types of wavelet. The result of this project has shown 86% accuracy. |
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