在電力品質的改善與控制中，測量與分析為兩大重要課題，本論文首先提出虛擬儀測方法的應用，以探測電力品質擾動資料。在所提之儀測系統中，資料擷取介面連同數位演算法並輔以LabVIEW軟體予以實現。本文之儀測系統係研究不同之擾動，其中包括諧波、閃爍與三相不平衡，且透過某一期間之擾動監測與紀錄，可協助掌握信號走勢變化與相關統計之資訊。
另於測量技術方面，本論文則提出以連續小波轉換計算電壓閃爍成份，並設計出小波直接解調演算法，且與以快速傅立葉為基礎之解調法及間接解調法相比較，其中完成的特性評估計包括：(1)閃爍頻率響應及(2)頻率偏移的效應。且為證實本文所提方法之可行性，本論文係以實際電弧爐負載為測試對象，並經由設計之儀測系統予以實現電壓閃爍之測量。
此外，本論文並應用連續小波轉換方法予以檢測突波與陷波之電力訊號，並藉由嵌入B-spline小波函式，可協助突波與陷波之暫態信號之辨認，及突波與陷波之起始點與終點之定位，同時計算突波與陷波的深度、寬度及面積之參數，測試結果均佐證本文在突波與陷波訊號偵測能力之提昇。
至於在資料分析方面，本文係針對電弧爐整個熔煉期之閃爍特性予以估測，其中所探討之統計資訊包含靜態性資訊、常態性資訊及相關係數，而藉由變化取樣間隔評估基本的統計機率及閃爍特性之分析結果並顯示：(1)大多數閃爍特性於熔煉期間係歸屬為靜態分佈或弱靜態分佈，而其機率密度函數大部分為非常態分佈，(2)同相間之電壓與電流變動有高相關性，(3)當取樣週期減少至12秒以下，閃爍估測之變動量將收斂到以3秒取樣間隔所得之估測值的±5%偏差量內。

Electrical power signal measurement and analysis are two important aspects in power quality. In this dissertation, an application of virtual instrument approach for probing the data of power quality disturbances is first proposed. In the proposed instrumentation system, a data acquisition interface is implemented along with digital algorithms developed by LabVIEW tools. The proposed system can be applied to investigate different disturbances that include voltage harmonics, voltage flickers and three-phase voltage unbalances. Through a certain period of disturbance monitoring and recording, the trend-of-variation and the related statistical information of disturbances would be examined and analyzed. Results of simulated and actual data help confirm the feasibility of the method.
As for measurement techniques, a continuous wavelet transform-based approach is proposed to assist the measurement of voltage flickering. A wavelet-direct demodulation (WDD) method is derived that is also compared with the fast Fourier transform covering frequency-domain direct demodulation (FDD) and indirect demodulation (IDD) methods, where the computation performances of each method were presently assessed based on the flicker-frequency response and system frequency deviation. Besides, to validate the practicality of the proposed method, the utility data measured near the arc furnace were also evaluated to support the method.
Furthermore, by embodying the B-spline wavelet function, this dissertation also investigate the detection of the notch and spike signals. In addition to localizing the start and end point of the notch and spike signals, the proposed method also grasped the depth, width and area parameters of the encountered signals. Test results further solidify the proposed method in good agreement.
Finally, as for the analysis of measured data, the estimation of the stochastic flicker characteristics for an electric arc furnace over a complete heat is examined thoroughly in this dissertation. These characteristics include stationarity, normality and correlation. Meanwhile, several fundamental statistical features were assessed at a different sampling periods. Test results for a typical AC arc furnace indicate that (1) most flicker characteristics are stationary or weakly stationary during different periods of a heat cycle, but most of their probability density functions are not normally distributed, (2) the voltage and current fluctuations in the same phase are highly correlated, (3) the flicker converges at a value with a ±5% deviations from the value based on a basic sampling period, if the sampling period is decreased below 12 seconds.

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