在電力系統中，電力變壓器係藉由電磁轉換的原理，將電壓調整至最適當的電壓等級運轉，使電力系統達到最佳的供電狀況。因此，電力變壓器在電力系統中是非常重要的能源轉換設備。
在正常運轉狀況下，為了使變壓器具有低製造成本及高工作效率的優良性能，一般變壓器鐵心的磁通密度都設計在近乎飽和的狀態。但是，一旦線路發生故障或開關切換而產生的突波干擾時，變壓器鐵心將非常容易就進入飽和的狀態，此時變壓器的磁場的變化方式不再是弦波的變化方式，穩態的電磁轉換原理將不再適用。
本論文從探討鐵磁性材料的磁化機制出發，當鐵磁性材料內各磁域受到外加供應場時，磁域內磁極會產生旋轉，磁域壁會移動等特性作明確的解釋；並對鐵磁性材料之材料參數對磁化作用的影響作出具體的說明。
接著，針對鐵磁性材料之微型結構參數所建立的磁化模型來探討外部有供應場時磁性材料巨觀的磁化響應。目前常用的磁滯模型有Stoner-Wolhfarth (S-W)模型、Jiles-Atherton (J-A)模型、Globus模型和Preisach模型等四種，對每個模型作個簡要的概述，再將每個模型的特性作一比較後發現，J-A磁滯模型是最適用於變壓器鐵心鐵磁性材料所採用的模型。
鐵磁性材料之J-A磁滯模型內共有五個材料參數，分別是飽和磁化強度 、單位體積釘住地點密度常數 、可逆磁化分量常數 、無磁滯曲線常數 以及磁域間耦合常數 等。先就每個參數對磁滯特性的影響作靈敏度分析，以比流器的J-A磁滯模型為例，使用Matlab軟體撰寫程式模擬J-A磁滯模型，來說明各參數的改變對磁滯產生的影響。再說明如何以處罰函數之遺傳基因演算法，估計出J-A磁滯模型參數的最佳值。使用此方法最大的好處是往後只要實驗得知鐵心的磁滯曲線，即可準確的估計出此鐵心J-A磁滯模型的各項參數值。
利用EMTP之TACS功能建立出J-A模型來模擬鐵心的磁滯效應，並結合外部電路，對整個系統作電路模擬分析。這樣的作法，可以克服以往在使用EMTP進行鐵心磁滯曲線的模擬時，必須使用 Type 96非線性電感元件來建立16個片段線性來模擬磁滯曲線。因為，使用 Type 96非線性電感元件來模擬磁滯曲線時，並無法充份反應鐵心飽和時的磁滯特性。所以，並不適用於暫態的模擬或故障分析；而J-A磁滯模型就沒有這方面的問題。
最後，以麥寮供電系統發生單相接地故障的事故分析為例。其中，電力變壓器的磁滯特性採用J-A磁滯模型。將模擬所得之波形與暫態波形記錄器所記錄之波形比較可以得知，變壓器鐵心的磁滯特性採用本論文所提出之J-A磁滯模型是非常適用與準確的。

Abided by the principle of power system, power transformer via electro-magnetic converting theory adjusts voltage to the most optimal level for best operational condition and brings forth most ideal electricity supply condition to the power system. Consequently, power transformer places a significant role as energy converting equipment in power system.
In order transformer possesses advantages of low production cost and high work efficiency under normal operational situation, the operational point of flux density for core of transformer are nearly achieving saturated status in general designs. Once circuit faults or interferences caused by power switch, it easily forces core of transformer into saturated status. At then, alternating method of magnetic field in transformer has no longer responded as sine waves; hence, it is reasonable steady magnetic converting principle has no longer been useful.
This study aims to discussing magnetization mechanism of ferro-magnetic material. During ferro-magnetic material is pressed against external applied field, magnetic dipole within magnetic domain will cause rotation and magnetic domain wall will move. These above features have been done a further explanation. This study also presents a detailed description regarding the special parameters of ferro-magnetic material and its influences to magnetization.
Later on, with a focus on magnetization model built upon micro-structure parameters of ferro-magnetic material, it discusses the mass scope magnetization response of ferro-magnetic material with external applied field. Popular four kinds of these hysteresis models include Stoner-Wolhfarth (S-W) model, Jiles-Atherton (J-A) model, Globus model, and Preisach model. Firstly the working principle of per model have done a brief introduction, and then a comparison for magnetization features of per model would draw a conclusion that J-A hysteresis model is most ideal to core hysteresis model of transformer.
The entire J-A hysteresis model contains five significant material parameters, which are saturation magnetization, unit volume pinning location density constant, reversible magnetization constant, anhysteresis curve constant, and magnetic domains coupling constant. This study begins with running sensitivity analysis for per parameter of J-A hysteresis model to hysteresis influences. Such as current transformer J-A hysteresis model, it uses Matlab software to simulate J-A hysteresis model, and describes per parameter change to hysteresis influences. Then it interprets using generic algorithm with penalty function to calculate the optimal parameter values of J-A hysteresis model. The biggest advantage of using this method is it only requires core hysteresis data from exciting magnetic experiments, and then a precise estimation of per parameter of core J-A hysteresis model can be obtained.
Availing TACS function within EMTP, it establishes J-A model that simulates core hysteresis effect and combines external circuit and performs circuit simulation analysis to the entire system. Follow this way of method; it overcomes the disadvantages for using Type 96 non-linear electrical elements to build 16 linear pieces of hysteresis effect. Because using Type 96 non-linear induction elements simulate hysteresis effect, it can not fully answer to core hysteresis saturation features. Consequently, this model is not suitable for a transient simulation or failure analysis; however J-A hysteresis model would ignore this restraint.
At last, taking single-phase ground fault accident analysis of Mailiao power supply system as an example, it proves the accessibility of core J-A hysteresis model. In the entire power system simulation circuit, hysteresis features of power transformer are described by J-A hysteresis model. Initiate a comparison for simulated waveform and transient waveform recorded waveform, and then it leads to a conclusion that using J-A hysteresis model to analyze core hysteresis features of transformer is most applicable and exact.

Abstaract (Chinese) i
Abstaract (English) iii
Acknowledgement vi
Contents vii
Figure Captions ix
Table Captions xiii

Chapter 1 Introduction 1
1.1 Research Motives and Purposes 1
1.2 Major Contributions 3
1.3 Introductory Discussions 4
Chapter 2 Ferro-Magnetic Material and Its Magnetization Character 6
2.1 Magnetization 6
2.2 Magnetic Domains 9
2.3 Domain Wall 16
2.4 Hard Magnetic and Soft Magnetic Materials 18
Chapter 3 Magnetization Model of Ferro-Magnetic Material 22
3.1 Stoner-Wolhfarth (S-W) Model 23
3.2 Jiles-Atherton (J-A) Model 26
3.3 Globus Model 31
3.4 Preisach Model 36
Chapter 4 Parameter Optimization of J-A Hysteresis Model 44
4.1 Parameter Sensitivity Analysis of J-A Hysteresis Model 44
4.2 Generic Algorithm with Penalty Function 52
4.3 Estimation of the Optimal Parameter Values of Core J-A Hysteresis Model 55
4.4 Result and Evidence 56
Chapter 5 Foundation of Core J-A Hysteresis Model 60
5.1 Establishment of Core J-A Hysteresis Model of CT 61
5.2 Transient Testing for Core J-A Hysteresis Model of CT 62
5.3 Case Study - Accidental Simulation Analysis of Mailiao Power Supply System 69
5.3.1 Measuring Data Resolution 72
5.3.2 Simulation and Result Analysis 78
Chapter 6 Conclusions 88
References 90
Publications 94
Biography 97

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