博碩士論文 100521088 詳細資訊




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姓名 柯廷翰(Ting-Han Ke)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 考慮配電系統三相故障之具低電壓穿越能力之智慧型太陽光電系統
(Intelligent PV System with LVRT under Grid Faults for Distribution System)
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摘要(中) 本論文提出兩種併網型太陽光電系統於故障期間之實虛功智慧型控制法,此二智慧型控制法皆同時符合再生能源併網低電壓穿越規範與變流器之最大電流限制。所提之二智慧型控制器分別為機率小波模糊類神經網路控制器,以及非對稱歸屬函數之TSK型機率模糊類神經網路控制器。論文中將詳細介紹兩種智慧型控制器的架構與線上學習法則,並證明其收斂性分析。當併網型太陽光電系統發生電壓故障時,控制器會依據低壓穿越規範所規範的虛功補償參考值,調整注入市電系統之虛功量,並能使太陽光電系統所產生的實功與注入市電的實功維持平衡。此外,本研究還提出兩種雙模式控制策略可於故障期間消除直流鏈電壓的波動。還有,在故障期間,注入市電系統電流大小加入了最大電流限制以降低過電流發生的風險。最後展示一些實驗結果以驗證所提方法之成效。
摘要(英) Two active and reactive power control schemes using intelligent control for grid-connected three-phase photovoltaic (PV) system during grid faults are proposed in this study. The control schemes are based on a ratio between active and reactive power which meet the low voltage ride through (LVRT) regulations and inverter maximum current limit simultaneously. Moreover, two intelligent controls based on probabilistic wavelet fuzzy neural network (PWFNN) and Takagi-Sugeno-Kang type probabilistic fuzzy neural network with asymmetric membership function (TSKPFNN-AMF) are developed to control the reactive power injected into the grid and balance the active power between the power generated by the PV and the power delivered into the grid under grid faults. The intelligent controllers regulate the value of reactive power to a new reference value which complies with the requirements of LVRT under grid faults. Furthermore, two dual-mode operation control strategies, which can eliminate the fluctuation of DC-link bus voltage under grid faults, are also discussed. In addition, to reduce the risk of over-current during the LVRT operation, a current limit is predefined in current injection. Finally, some experimental results are presented in order to validate the effectiveness of the proposed control.
關鍵字(中) ★ 配電系統三相故障
★ 低電壓穿越
★ 太陽光電系統
★ 虛功控制
★ 機 率小波模糊類神經網路
★ 非歸屬函數之TSK型機率模糊類神經網路
關鍵字(英) ★ Photovoltaic system
★ PWFNN
★ TSKPFNN-AMF
★ low voltage ride through
★ grid faults
★ reactive power control
論文目次 中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 xi
第 1 章 緒論 1
1.1 研究背景 1
1.2 文獻回顧 3
1.3 論文大綱 6
1.4 本文貢獻 6
第 2 章 太陽光電系統簡介 7
2.1 簡介 7
2.2 太陽能電池特性簡介 7
2.3 太陽能電池最大功率點追蹤 11
2.4 三相座標軸轉換之分析 12
2.4.1 靜止座標軸 14
2.4.2 同步旋轉座標軸 15
2.4.3 三相功率計算 16
2.5 市電角度偵測策略 17
2.5.1 三相線電壓軸轉換法 17
2.5.2 三相電壓濾波法 18
2.5.3 三相鎖相迴路法 19
2.6 變流器之實虛功控制與電流控制 20
2.7 硬體設備 22
2.7.1 可程控直流電源供應器(具太陽能電池陣列模擬功能) 23
2.7.2 升壓轉換器、變流器 25
2.7.3 三相變壓器 27
2.7.4 交流電源供應器 28
2.7.5 資料擷取卡 30
第 3 章 配電系統三相故障分析 32
3.1 簡介 32
3.2 故障型態分析 32
3.3 正負序分析 37
3.4 正負序偵測 40
3.5 故障電壓偵測與低電壓穿越規範 48
第 4 章 機率小波模糊類神經網路之太陽光電系統 51
4.1 系統簡介 51
4.2 升壓轉換器雙模式控制策略 52
4.3 機率小波模糊類神經網路架構 55
4.4 機率小波模糊類神經網路線上學習法則 58
4.5 機率小波模糊類神經網路之收斂性分析 60
4.6 實作與討論 62
4.6.1 配電系統單相對地故障(Mode I) 62
4.6.2 配電系統單相對地故障(Mode II) 65
4.6.3 配電系統兩相之間故障(Mode II) 68
第 5 章 非對稱歸屬函數之TSK型機率模糊類神經網路之太陽光電系統 71
5.1 簡介 71
5.2 雙模式控制策略 72
5.3 非對稱歸屬函數之TSK型機率模糊類神經網路架構 74
5.4 非對稱歸屬函數之TSK型機率模糊類神經網路線上學習法則 77
5.5 非對稱歸屬函數之TSK型機率模糊類神經網路之收斂性分析 80
5.6 實作與討論 82
5.6.1 配電系統兩相對地故障(Mode I) 83
5.6.2 配電系統兩相對地故障(Mode II) 86
5.6.3 配電系統兩相對地故障(Mode II) 89
第 6 章 結論與未來研究方向 92
6.1 結論 92
6.2 未來研究方向 92
參考文獻 93
作者簡歷 98
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指導教授 林法正(Faa-Jeng Lin) 審核日期 2013-8-9
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