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研究生:林俊佑
研究生(外文):Chun-Yu Lin
論文名稱:適應性主動式低頻漣波控制設計於潔淨能源電力調節裝置
論文名稱(外文):Adaptive Active Low-Frequency Ripple Control Design for Clean-Energy Power-Conditioning Mechanism
指導教授:魏榮宗
學位類別:碩士
校院名稱:元智大學
系所名稱:電機工程學系
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:2010
畢業學年度:99
語文別:中文
論文頁數:81
中文關鍵詞:主動式低頻漣波控制適應性全域滑動模式控制器潔淨能源類神經濾波器電力調節
外文關鍵詞:Active low-frequency ripple control circuit (ALFRCC)adaptive total sliding-mode control (ATSMC)clean energyneural filterpower condition
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本論文主要發展適應性主動式低頻漣波控制機制於潔淨能源電力調節技術研究,其目標在於同時達成潔淨能源(太陽光電,燃料電池等)低頻漣波抑制及其電力調節器輸出之交流電力品質改善。首先介紹整體系統週邊電路(第二章),接者提出主動式低頻漣波控制機制(第三章),運用所提出簡化電路、類神經濾波器及全域滑動模式控制器,可有效操控主動式低頻漣波控制電路,成功改善電力調節器高壓匯流排之低頻電流漣波現象。另一方面,因應潔淨能源電力調節器於電感性及非線性負載操作下,電力調節器輸出端存在虛功及諧波成分現象,本論文進一步發展適應性主動式低頻漣波控制機制(第四章),其中運用所提出簡化電路、搭配雙類神經濾波器及適應性全域滑動模式控制器,可同時有效即時操控雙主動式低頻漣波控制電路對電力調節器高壓匯流排及輸出端電流進行電流補償。最後對本論文所提出系統及其性能數值模擬及實作結果進行討論,並提供未來研究可繼續深入探討之要點(第五章)。

This thesis focuses on the design of adaptive active low-frequency ripple controls for a clean-energy power-conditioning mechanism with an aim to achieve both the alleviation of the low-frequency current-ripple of clean-energy sources (e.g., solar photovoltaics, fuel cells, etc), and the improvement of the ac power quality of a power conditioner. First, system descriptions in chapter 2 are given to provide the detailed presentation of experimental equipments. Then, an active low-frequency ripple control for a clean-energy power-conditioning mechanism investigated in chapter 3, which includes a simplified circuit, a neural filter and a total sliding-mode controller (TSMC), can effectively manipulate an active low-frequency ripple control circuit (ALFRCC) to improve the low-frequency ripple phenomena on the bus terminal of the power conditioner. On the other hand, in order to alleviate the power quality pollution of reactive power and harmonic component on the output terminal of the power conditioner under inductive and nonlinear loads, this thesis further develops a dual active low-frequency ripple control for a clean-energy power-conditioning mechanism in chapter 4, which includes a simplified circuit, two neural filters and an adaptive total sliding-mode controller (ATSMC). It can effectively manipulate a dual active low-frequency ripple control circuit (DALFRCC) to improve the low-frequency ripple phenomena on the bus terminal and the output terminal of the power conditioner. Finally, some discussions of numerical simulations and experiment results are given, and some suggestions in the future research are also provided in chapter 5.

書名頁 I
論文口試委員審定書 II
授權書 III
中文摘要 IV
Abstract V
誌謝 VII
Contents VIII
List of Figures XI
List of Tables XV
Chapter 1 Introduction 1
Chapter 2 System Descriptions 6
2.1 Overview 6
2.2 Digital Signal Processor 7
2.3 Intelligent Power Module 8
2.4 Driving Subsystem 9
2.5 Feedback Subsystem 9
2.6 Clean-Energy Power-Conditioning Mechanism 11
Chapter 3 Active Low-Frequency Ripple Control 13
3.1 Overview 13
3.2 Low-Frequency Current-Ripple Phenomenon inside Clean-Energy Power Conditioner 13
3.2.1 General Clean-Energy Power Conditioner 13
3.2.2 Simplified Circuit 14
3.3 Active Low-Frequency Ripple Control Circuit 15
3.3.1 Dynamic Analyses 17
3.3.2 Neural Filter 18
3.3.3 Total Sliding-Mode Controller 20
3.4 Numerical Simulations and Experimental Results 23
3.4.1 Numerical Simulations 25
3.4.2 Experimental Results 29
3.5 Conclusions 34
Chapter 4 Dual Active Low-Frequency Ripple Control 36
4.1 Overview 36
4.2 Low-Frequency Current Ripple Phenomenon of Clean-nergy Power Conditioner 36
4.2.1 General Clean-Energy Power Conditioner 36
4.2.2 General Power Conditioner with Proposed DALFRCC 37
4.2.3 Simplified Circuit 38
4.3 Dual Active Low-Frequency Ripple Control Circuit41
4.3.1 Dynamic Analyses 41
4.3.2 Neural Filters 43
4.3.3 Adaptive Total Sliding-Mode Controller 48
4.4 Numerical Simulations and Experimental Results 53
4.4.1 Numerical Simulations 56
4.4.2 Experimental Results 58
4.5 Conclusions 70
Chapter 5 Discussions and Suggestions for Future Research 71
5.1 Discussions 71
5.2 Suggestions for Future Research 74
References 77
Biographical Sketch 80
Publication List 81

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[17]M. A. Mofd Radzi and N. A. Rahim, “Neural network and bandless hysteresis approach to control switched capacitor active power filter for reduction of harmonics,” IEEE Trans. Ind. Electron., vol. 56, no. 5, pp. 1477-1484, 2009.
[18]D. O. Abdeslam, P.Wira, J. Mercklé, D. Flieller, and Y Chapuis, “A unified artificial neural network architecture for active power filters,” IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 61-76, 2007.
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