利用智慧型控制之三相主動式電力濾波器的研製

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姓名

陳俊豪(Jun-Hao Chen) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

利用智慧型控制之三相主動式電力濾波器的研製
(Design and Implementation of Three-Phase Active Power Filters with Intelligent Control)

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摘要(中)

本文建構一以三相三臂變流器為電路架構之主動式電力濾波器，以補償市電因非線性負載所引起的諧波電流，使得市電電流可補償為正弦波波形，而為提升諧波補償成效與改善非線性負載變動時直流鏈電壓的暫態響應，本文提出一非對稱歸屬函數之遞迴式機率模糊類神經網路控制器取代傳統的比例積分控制器。另一方面，本論文亦建構一以三相四臂變流器為電路架構之主動式電力濾波器，以補償市電因三相不平衡負載所引起的三相不平衡電流，使得市電電流可補償為三相平衡電流且抑制中性線電流，此外，為提升不平衡補償效果與改善三相不平衡負載變動時直流鏈電壓的暫態響應，亦提出一派翠機率模糊類神經網路控制器取代比例積分控制器。再者，本文將分別詳細介紹所提出之二種新式智慧型控制器的網路架構與線上學習法則，並且分別證明其收斂性。最後，本研究利用Texas Instruments TMS320F28335數位訊號處理器完成所提出的主動式電力濾波器，並且利用實驗結果證明主動式電力濾波器結合所提出之智慧型控制之補償成效及可行性。

摘要(英)

A three-phase three-arm active power filter (APF) is proposed to compensate harmonic current under nonlinear load conditions in grid-connected operation in this study. In order to improve the regulation control of the DC-link voltage in the shunt APF under the variation of nonlinear load and to compensate the currents harmonic effectively, a novel recurrent probabilistic fuzzy neural network with an asymmetric membership function(RPFNN-AMF) controller is proposed to replace traditional proportional-integral (PI) controller. Moreover, a three-phase four-arm inverter-based active power filter is also proposed to compensate three-phase unbalanced currents under unbalanced load conditions in grid-connected operation in this study. Furthermore, to improve the regulation control of the DC-link voltage in the APF under the variation of three-phase unbalanced load and to compensate the three-phase unbalanced currents effectively, a novel Petri probabilistic fuzzy neural network (PPFNN) controller is proposed to replace traditional PI controller. In addition, the network structure, online learning algorithms and convergence analysis of the proposed two intelligent controllers are represented respectively in detail. Finally, the proposed two intelligent controllers to control the APF are implemented by the control platform using the Texas Instruments digital signal processor (DSP) TMS320F28335, and the effectiveness and the feasibility are verified by some experimental results.

關鍵字(中)

★ 主動式電力濾波器
★ 非對稱歸屬函數之遞迴式機率模糊類神經網路
★ 派翠機率模糊類神經網路
★ 直流鏈電壓控制
★ 負載變動

關鍵字(英)

★ active power filter
★ recurrent probabilistic fuzzy neural network with an asymmetric membership function
★ Petri probabilistic fuzzy neural network
★ DC-link voltage control
★ load changing

論文目次

摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VII
表目錄 XIII
第一章緒論 1
1.1 研究動機與目的 1
1.2 文獻回顧 2
1.3 論文大綱 5
1.4 論文貢獻 6
第二章主動式電力濾波器概論 7
2.1 前言 7
2.2 依儲能元件分類 7
2.3 依與系統連接之架構分類 8
2.3.1 串聯型主動式電力濾波器 8
2.3.2 並聯型主動式電力濾波器 9
2.3.3 混合型主動式電力濾波器 10
2.3.4 整合型電力品質調節器 12
2.4 主動式電力濾波器之選擇 12
第三章系統架構與控制策略 14
3.1 前言 14
3.2 三相座標軸轉換 14
3.3 市電角度估測 15
3.4 負載瞬時實功率與虛功率計算 16
3.5 非線性負載補償之架構與控制策略 17
3.5.1 補償電流計算 18
3.5.2 直流鏈電壓控制 19
3.5.3 整體控制策略 20
3.6 不平衡負載補償之架構與控制策略 21
3.6.1 補償電流計算 21
3.6.2 直流鏈電壓控制 22
3.6.3 整體控制策略 22
第四章非對稱歸屬函數之遞迴式機率模糊類神經網路 24
4.1 前言 24
4.2 非對稱歸屬函數之遞迴式機率模糊類神經網路架構 25
4.3 非對稱歸屬函數之遞迴式機率模糊類神經網路線上學習法則 27
4.4 非對稱歸屬函數之遞迴式機率模糊類神經網路收斂性分析 30
第五章派翠機率模糊類神經網路 33
5.1 前言 33
5.2 派翠機率模糊類神經網路架構 34
5.3 派翠機率模糊類神經網路線上學習法則 36
5.4 派翠機率模糊類神經網路收斂性分析 38
第六章硬體規劃與設計 40
6.1 前言 40
6.2 硬體規劃 40
6.2.1 非線性負載補償之硬體規劃 40
6.2.2 不平衡負載補償之硬體規劃 41
6.3 周邊電路設計 42
6.3.1 交流電流回授電路 43
6.3.2 交流電壓回授電路 43
6.3.3 直流電壓回授電路 44
6.3.4 保護電路 44
6.3.5 互鎖電路 45
6.4 數位訊號處理器 45
第七章模擬與實驗結果 48
7.1 前言 48
7.2 模擬結果 48
7.2.1 非線性負載補償之模擬結果 48
7.2.2 不平衡負載補償之模擬結果 54
7.3 實驗結果 60
7.3.1 非線性負載補償之實驗結果 60
7.3.2 不平衡補償之實驗結果 72
第八章結論與未來研究方向 84
8.1 結論 84
8.2 未來研究方向 85
附錄 86
IEEE Std 519 - 2014 86
參考文獻 88
作者簡歷 95

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指導教授

林法正(Faa-Jeng Lin)

審核日期

2017-8-18

推文