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研究生:陳怡縈
研究生(外文):Chen, Yi-Ying
論文名稱:以同步擠壓轉換為基礎之混合方法進行電壓閃爍評估
論文名稱(外文):A Synchrosqueezing Transform-based Hybrid Approach for Voltage Flicker Assessment
指導教授:張文恭
指導教授(外文):Chang, Wen-Kung
口試委員:盧展南張忠良劉志文楊宏澤黃世杰吳元康張文恭
口試委員(外文):Lu, Zhan-NanChang, Zhong-LiangLiu, Chih-WenYang, Hong-ZeHuang, Shi-JieWu, Yuan-KangChang, Wen-Kung
口試日期:2017-06-30
學位類別:博士
校院名稱:國立中正大學
系所名稱:電機工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:95
中文關鍵詞:電力品質電壓波動閃爍IEC規範 61000-4-15希爾伯特轉換同步擠壓轉換均值移動聚類法
外文關鍵詞:power qualityvoltage fluctuationflickerIEC Standard 61000-4-15Hilbert transformsynchrosqueezing transformmean shift
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隨著電力系統中非線性負載使用量逐漸增加,使得各項電力品質問題日趨嚴重,電壓閃爍是電力品質的重要指標之一。由於電力系統中具有快速變動的負載造成了電壓變動,而電壓變動不但會造成電子儀器設備功能失常,更會影響照明燈具輸出的穩定度,燈光閃爍會造成視覺干擾、視覺疲勞甚至傷害視力。準確的量測為改善電力品質問題的首要工作,因此該如何建立有效且正確的數據分析是相當重要的。
IEC 61000-4-15電壓閃爍量測方法係以模擬視覺對光線變化之反應,評估閃爍的嚴重程度,其設計涵蓋了多項功能方塊以模擬人眼對燈光閃爍以及產生之腦部響應,並且以統計方式計算電壓閃爍之短期與長期閃爍指標。目前為最多國家所採用的標準。本論文提出一套以同步擠壓轉換為基礎之分析方法來計算出閃爍汙染問題的嚴重度,利用IEC 61000-4-15規範中所制定的閃爍分析儀量測功能方塊圖做為基本架構,並針對其中解調出電壓包絡線的方塊加以改良。
本論文提出之方法以希爾伯特轉換擷取電壓變動之包絡線,再以同步擠壓轉換與均值移動聚類法分析電壓變動源之閃爍頻率成份,透過帶通濾波器組求得精確之閃爍頻率之振幅,模擬與量測之結果皆顯示提出之方法在電壓閃爍的量測相當正確且有效。

With the widespread existence of nonlinear loads in the power system, the power quality disturbances are increasingly present. Flicker is one of the major power quality event. The impacts of flicker disturbance have been commonly seen in the power distribution networks nowadays. Voltage fluctuations caused by rapid reactive power consumption of loads and photovoltaic or wind generator output variations may produce flickers and cause undesired effects on electric power components and human eyes.
IEC 61000-4-15 is the most popular flickermeter standard providing basic information for the design based on human eye-brain perception intended to indicate the correct flicker perception level for all practical voltage fluctuation waveforms, furthermore, performing an on-line statistical analysis of the flicker level.
This dissertation presents a hybrid approach for voltage flicker assessment by using synchrosqueezing transform-based algorithm. The approach is an improved demodulation method to extract the voltage envelope which can replace the squaring demodulation suggested by IEC 61000-4-15. The proposed method firstly gives characterization of voltage fluctuations through accurate extraction of the measured voltage envelope by Hilbert transform. The synchrosqueezing transform and an unsupervised clustering method called mean shift, are then applied to determine the number of frequency components and corresponding frequencies. It is followed by the implementation of the bandpass filters to accurately detect the magnitude of each flicker component. The proposed hybrid method is tested by both simulations and field measurements validation. Results compared with other commonly seen methods show that the proposed method provides a more accurate flicker assessment.

ACKNOWLEDGMENTS I
摘 要 II
ABSTRACT III
LIST OF FIGURES VIII
LIST OF TABLES XI
I. INTRODUCTION 1
1.1 Background 1
1.2 Literature Review of Voltage Fluctuation Assessment Methods 1
1.3 Research Motivation 2
1.4 Organization of the Dissertation 3
II. OVERVIEW OF VOLTAGE FLUCTUATION 5
2.1 Definition of Flicker 5
2.2 Causes of Flicker 7
2.3 Standards Associated with Voltage Fluctuations 9
2.3.1 IEEE Flicker Standard 9
2.3.2 Short Circuit Voltage Depression Ratio 10
2.3.3 CRIEPI 13
2.3.4 IEC Flicker Standard 15
III. SYNCHROSQUEEZING TRANSFORM 21
3.1 Introduction of Time-Frequency Analysis 21
3.2 Short-Time Fourier Transform 22
3.2.1 Continuous Short-Time Fourier Transform 23
3.2.2 Discrete Short-Time Fourier Transform 23
3.3 Wavelet Transform 24
3.3.1 Continuous Wavelet Transform 25
3.3.2 Discrete Wavelet Transform 26
3.4 S-Tranform 26
3.5 Synchrosqueezing Transform 29
3.6 Comparison of Different TF methods 34
3.6.1 Case 1: Effect of Multiple frequency-modulated detection 34
3.6.2 Case 2: Effect of Time-Varying Multifrequency Modulation 37
3.6.3 Case 3: Effect of Noise 38
3.6.4 Summary of Comparison Results 40
IV. MEAN SHIFT CLUSTERING 42
4.1 The Overview of Clustering Algorithms 42
4.2 k-Nearest Neighbor 45
4.3 Mean Shift 47
4.4 K-Means 51
4.5 The Performance of Different Clustering Algorithms 54
4.5.1 Comparison of the Charateristic between k-Nearest Neighbor, Mean Shift, and K-means 54
4.5.2 Summary 57
V. SOLUTION PROCEDURE OF THE PROPOSED APPROACH 59
5.1 Voltage Flicker Signal Modeling 60
5.2 Extraction of Voltage Envelope by Hilbert Transform 60
5.3 Synchrosqueezing-based Method for Flicker Envelope Analysis 62
5.4 Accurate Frequency Calculation of Each Flicker Component by Mean Shift Algorithm 63
VI. CASE STUDIES 66
6.1 Multi-frequency Modulated Voltage 66
6.2 Accuracy of Demodulation Methods 69
6.3 Impact of White Noise Existing in the Measured Voltage Signal 71
6.4 Effects of Harmonics/Interharmonics on Measured Voltage 72
6.5 Time-varying Frequency Detection 74
6.6 Transfer Coefficients of Flicker Over a Transmission Network 75
VII. CONCLUSIONS AND FUTURE WORKS 84
7.1 Conclusions 84
7.2 Future Works 86
REFERENCES 87
VITA 96

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