High-Resolution SVD Method for Waveform Processing by Using Down-Sampling Technique

• Main Authors: Cheng-Yi Chen, 陳正一
• Other Authors: Gary W. Chang
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/61294498412067880118

碩士 === 國立中正大學 === 電機工程研究所 === 94 === ABSTRACT With the widespread use of nonlinear loads in the power system, harmonic distortion causes a serious pollution of power quality. Besides, the power unbalance between the generation and the load demand would make the fundamental frequency varying with time. These disturbances may introduce operational problems of power system equipment. Therefore, improving the power quality has become a great concern for both utilities and customers. The frequency-domain methods have been widely used for the signal processing because of its computational efficiency. In addition, most power meters adopt FFT-based algorithm to analyze the harmonics and to show the frequency spectra. However, the FFT-based algorithm is less accurate if the system frequency varies and the frequency resolution decreases. The analytic results will show errors caused by the leakage and picket-fence effects. Although increasing the sampling data can mitigate the undesired effects, this will impede the computational efficiency. Therefore, how to achieve both the high resolution and efficiency is worth investigating. According to aforementioned facts, this thesis proposes a Prony-based improved singular value decomposition (SVD) algorithm for harmonics and interharmonics measurement. Not only the calculation time is reduced, but also the result is with a better accuracy, even if the power signals contain frequency variations and non-integer harmonic components. Finally, the thesis applies LabVIEW and the dedicated hardware to design a simple setup for measuring power quality signals. The performance of improved algorithm is validated by testing the synthesized and actual signals.