摘要

台電系統於民國73年首次出現低頻振盪現象，低頻振盪的發生降低供電品質，甚而危害系統安全。民國80年期間，台電公司進行電力系統強化之後，自發性低頻振盪現象已不復出現，但因台電系統具有先天性的長距離輸電特性以及區域的電力供需失衡，低頻振盪仍為台電系統的一項潛在問題。電力系統的大型擾動(跳機或跳線等故障)，亦會造成變電所間的相角差以及電功率的短暫振盪現象，其振盪通常並非平穩且含有變動性的直流偏移量。
本論文結合可變視窗型離散傅立葉轉換及離散小波轉換分析低頻振盪信號，計算振盪信號之主要自然頻率及阻尼常數，用以評估系統之動態穩定度。對於含有定值直流偏移量之自發性低頻振盪，採用偵測三個波峰值的直流濾除方法結合可變視窗型離散傅立葉轉換，進行計算；至於大型擾動所激發的短暫振盪信號，由於內含非定值的直流偏移量，本論文提出以小波分解法，萃取其中屬於低頻振盪頻率範圍的信號，再進行可變視窗型離散傅立葉轉換分析。
小波函數的選用方面，本研究測試七種小波函數，經測試台電系統的記錄波形，建議選用db10小波函數及dmey小波函數，並結合可變視窗型離散傅立葉轉換，用於監測台電系統的低頻振盪參數。

Abstract

Low frequency oscillation phenomena first appeared in Taipower system in 1984. The phenomena not only deteriorated power supply quality but also threatened the system security. During 1990’s, Taiwan Power (Taipower) Company had strengthened its transmission system. Thus the spontaneous low frequency oscillation phenomena have not appeared again. However, because of the inherent longitudinal structure of transmission network and the regional power supply and demand imbalance, the low frequency oscillation is still a potential problem in the Taipower system. The large-scale perturbations caused by machine or transmission line trippings in the power system will still lead to the transient oscillations of power angle and power flow between substations. Such oscillations are normally unsteady and thus contain the variational DC offsets.
A method integrating the discrete Fourier transform at a variable size of sampling window and the discrete wavelet transform is proposed to analyze the signals of low frequency oscillations, including the calculation for the oscillation parameters such as the main natural frequency and the damping constant, based on them to assess the system dynamic stability. For the spontaneous low frequency oscillations with the constant DC offsets, it is proposed in this thesis to apply the DC offset filtering method by detecting the three waveform peaks, and then apply the discrete Fourier transform at the variable window size to the calculation for the oscillation parameters. As to the transient oscillatory signals having a variable DC offset which are usually excited by the large-scale perturbations, a process is proposed which applies the wavelet decomposition to extract the low frequency oscillation signal components, and then applies the same discrete Fourier transform as for the spontaneous low frequency oscillations.
Seven kinds of mother wavelets all integrated with the discrete Fourier transform at a variable window size have been tested on the Taipower system data. Among them, the db10 wavelet and the dmey wavelet functions have been chosen and suggested to use for monitoring the low frequency oscillation parameters of Taipower system.

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