基於遞迴式小波模糊派翠類神經網路控制策略之多微電網多模式動態電壓補償器設計

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姓名

戴于竣(Yu-Jun Dai) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

基於遞迴式小波模糊派翠類神經網路控制策略之多微電網多模式動態電壓補償器設計
(Design of Multi-Mode Dynamic Voltage Restorer for Multiple Microgrids Based on Recurrent Wavelet Fuzzy Neural Petri Network Control Strategy)

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至系統瀏覽論文 ( 永不開放)

摘要(中)

本文提出一多模式動態電壓補償器(Multi-Mode Dynamic Voltage Restorer, MMDVR)透過與主動式濾波器性能相結合，在電力事件發生時透過電壓補償以及孤島模式(Island Mode)控制，穩定各區域內負載側的供電品質。另外為了解決電網系統在控制上之動態響應，本文提出一遞迴式小波模糊派翠類神經網路智慧型控制器，透過遞迴結構的鑑別能力搭配類神經的線上學習結構可有效解決系統非線性參數及外部干擾，最後結合解耦合雙同步參考軸鎖相迴路，以改善傳統比例積分控制器之響應結果。
本文使用MATLAB/Simulink模擬本文所提出之多模式動態電壓補償器架構應用於以三區微電網之分散式架構來取代傳統電力系統，相較於傳統個別微電網，其特點為輸出電力可自給自發電，降低輸配電線路的損失。並比較傳統比例積分控制器與本文提出之遞迴式小波模糊派翠類神經網路在系統控制上之動態響應結果的不同。最後，透過模擬軟體、比較結果驗證了本文所提出之多模式動態電壓補償器搭配智慧型控制器能有效增強電網韌性與動態響應性能。

摘要(英)

This thesis proposes the multi-mode dynamic voltage restorer (MMDVR) by combining the performance of the series active power filter, through voltage compensation and island mode control when a power event occurs, to stabilize the power supply quality at the load. In addition, in order to solve the dynamic response of the power grid system in the control, this paper propose the Recursive Wavelet Fuzzy Neural Petri Network (RWFNPN) intelligent controller, which can effectively solve the nonlinear parameters and external disturbances of the system through the discrimination ability of the recursive structure and the online learning structure of the neural network. Finally, combined with the Decoupling Dual Synchronous Reference Frame Phase Lock Loop (DDSRF-PLL) to improve the response results.
This thesis use MATLAB/Simulink to simulate the proposed multi-mode dynamic voltage compensator structure proposed in this paper, which is applied to replace the traditional power system with the distributed structure of the three-zone microgrids. Compare with the traditional individual microgrid, it’s characteristic is that the output power can be self-generated, reducing the loss of distribution lines. And compare the dynamic response results of the traditional PI controller and the RWFNPN control. Finally, verified that the multi-mode dynamic voltage restorer can effectively enhance the resilience and dynamic response performance of the power grid.

關鍵字(中)

★ 動態電壓補償器
★ 多重微電網
★ 電力品質

關鍵字(英)

★ Dynamic Voltage Restorer
★ Multiple-Microgrids
★ Power Quality

論文目次

論文摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VIII
表目錄 XIV
第一章緒論 1
1-1 研究目的與動機 1
1-2 文獻探討 2
1-3 論文大綱 4
第二章相關電力品質事件規範 6
2-1 對稱型故障 7
2-2 不對稱型故障 10
2-3 電壓閃爍分析 12
2-4 電壓諧波汙染分析 14
2-5 電力中斷 18
第三章電網電壓鎖相迴路相位偵測技術 20
3-1系統補償策略 20
3-1-1相位同步補償法 20
3-1-2驟降預測補償法 22
3-1-3能量優化注入補償法 23
3-2電壓相位偵測方法 26
3-2-1同步參考軸鎖相迴路 26
3-2-2電壓相序分析 28
3-2-3雙二階廣義積分器 30
3-3解耦合雙同步參考軸鎖相迴路 33
第四章多重微電網之動態電壓補償器 39
4-1系統簡介 39
4-2系統硬體架構 39
4-3電網模式調節分析 42
4-4補償電壓工作分析 44
4-5電網補償相關控制策略 45
4-5-1儲能鏈穩壓控制 45
4-5-2實虛功電流控制模式 46
4-5-3電壓控制孤島模式 48
4-5-4動態電壓補償模式控制 50
4-5-5電力事件模式切換分析 52
4-6電網整體系統模式切換流程介紹 53
第五章遞迴式小波模糊派翠類神經網路 56
5-1模糊推論理論(Fuzzy Theory) 56
5-1-1模糊化介面(Fuzzification) 58
5-1-2 模糊規則庫(Fuzzy Rule Base) 59
5-1-3 模糊推論工廠 61
5-1-4 解模糊化界面(Defuzzification) 61
5-2 派翠網路 64
5-3 遞迴式結構 65
5-4 小波轉換分析 66
5-5 遞迴式小波模糊派翠類神經網路架構 66
5-6 遞迴式小波模糊派翠類神經網路線上學習法則 72
5-7 遞迴式小波模糊派翠類神經網路收斂規則分析 76
第六章系統模擬與實驗結果 79
6-1系統環境介紹 79
6-2模擬環境情境控制結果 81
6-2-1儲能系統直流鏈穩壓控制 81
6-2-2系統控制分析與電力事件參數設定 84
6-3情境1-各區微電網儲能SOC正常且無電力事件發生 86
6-4情境2-微電網(一)儲能SOC過低且市電端對稱驟降 96
6-5情境3-各區微電網儲能SOC正常且市電端電壓閃爍 116
第七章未來研究目標方向 126
7-1結論 126
7-2未來研究目標方向 127
參考文獻 129

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指導教授

陳正一(Cheng-I Chen)

審核日期

2023-7-19

推文