Artificial neural network application for identification of harmonic disturbance / Nurhasliza Hashim
Both electric utilities and end users of electric power are becoming increasingly concerned about the quality of power. The term Power Quality (PQ) can be best defined as any power problem manifested in voltage, current or disopnation of customer equipment. In response to this dilemma, the waveform...
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| Format: | Thesis |
| Language: | en |
| Published: |
2004
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/78052/1/78052.pdf https://ir.uitm.edu.my/id/eprint/78052/ |
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| Summary: | Both electric utilities and end users of electric power are becoming increasingly concerned about the quality of power. The term Power Quality (PQ) can be best defined as any power problem manifested in voltage, current or disopnation of customer equipment. In response to this dilemma, the waveform contains the harmonics will be identified. In this project, the Feedforward Neural Network (FFNN) is proposed to identify and classify the power quality disturbances and simulated with MATLAB software. The harmonic signals and spectrum are determined by the application of a Fast Fourier Transform (FFT). |
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