對各國電力公司而言配電系統架空線高阻抗故障的保護是當前所面臨的一個重要的問題。當發生高阻抗故障時於掉落的導線與接觸地面間通常伴隨有電弧的存在，這個電弧火花可能會引起火災造成人員生命財產的威脅。本論文成功地開發一種新的智慧型高阻抗故障偵測器，它利用3I0零序電流偵測架空線的高阻抗故障。首先採用卡方分布及95%信賴區間自動設定3I0零序電流的臨界值，用以檢測3I0零序電流的變異程度，接下來利用小波轉換做為特徵信號的解析並將此特徵信號利用神經網路加以分類辨識，整體的架構具有能明確地分辨高阻抗故障及開關切換暫態。所提出的智慧型高阻抗故障偵測器具有三種有別於以往演算法的特色；分別是(1)以3I0零序電流做為故障判斷的依據而不是傳統的三相電流。(2)3I0零序電流作小波分析後高頻係數及低頻係數同時應用作為高阻抗故障判斷的依據。(3)“疑似高阻抗故障”的功能大大地改善故障判讀的“安全性”及“可靠性”問題。“安全性”及“可靠性”的考量、取捨對於高阻抗故障的偵測是一件很重要的工作。經由軟體模擬的結果，可以清楚顯示所提出的故障偵測技術可以正確地辨識配電系統中的高阻抗故障及負載或電容組切換暫態。為了將理論與實務相互結合，另外執行兩次的高阻抗人工故障試驗，用以驗證所提出的演算法的實際可行性並評估其性能的優劣。另外利用故障試驗記錄資料，對於文獻上所提出的其他偵測演算法也一併檢討，最後將他們對故障偵測的能力與所提出的智慧型高阻抗故障偵測器比較。綜合所有的比較結果，顯示本文所提出的智慧型高阻抗故障偵測器具有十分優良的性能。

Protection of aerial lines from high impedance faults (HIFs) is a signification topic for worldwide electric utilities. Arcing phenomena between a fallen conductor and the ground are usually linked with HIFs, which may lead to a fire hazard or endanger beings. This work successfully develops a new intelligent HIF detector that adopts 3I0 zero sequence current to solve HIF problems in aerial lines. A self-turning scheme based on the chi-square distribution and 95％ confidence interval is first applied to set the threshold level automatically for the 3I0 zero sequence current variances examined. The feature extraction scheme based on wavelet transform and the pattern recognition technique found on neural networks are then applied to discriminate effectively between HIFs and switching operations. The proposed approach has three distinct features. First, the input signal of this algorithm is 3I0 zero sequence current, rather than the conventional three individual phase currents. Secondly, it is different from the literatures; the details and the approximations of 3I0 zero sequence current are utilized for HIFs identification. Thirdly, the function of the “suspected HIF” improves the performance of security and reliability of HIFs identification. Security and reliability are very important issues in HIFs detection. The results of software simulation clearly show that the proposed technique can accurately identify the HIFs from the switching transient of load or capacitor banks in the distribution feeder. For combining theory with practice, two staged fault tests were performed to study the feasibility of the proposed algorithm and evaluate its performance. The performance of other relaying algorithms existing in the literature was also compared with proposed intelligent HIF detector based on the staged fault records. Experimental results reveal that the proposed intelligent relay is feasible performance well.

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