基於模糊派翠類神經網路之微電網太陽能系統低電壓穿越控制策略

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姓名

許祖隆(Zu-Long Syu) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

基於模糊派翠類神經網路之微電網太陽能系統低電壓穿越控制策略
(Low-Voltage Ride-Through Control Strategy of Solar Energy Generation System in Microgrid Based on Fuzzy Neural Petri Net)

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至系統瀏覽論文 ( 永不開放)

摘要(中)

本論文提出微電網中太陽能系統於正常情況與低電壓故障情況的運作模式與控制方法，正常情況下以最大功率點追蹤太陽能板的功率輸出峰值，並經由DC-AC轉換器將功率傳輸給負載或者回饋給市電；在低電壓故障期間，由規範所規定再生能源裝置於故障期間內提供一定比例之虛功電流補償以輔助市電渡過短暫之電壓低落狀況，並限制於故障時間內斷路器跳脫之行為，因此調整DC-AC轉換器之輸出功率分配，最後將使用模糊派翠類神經網路取代傳統比例積分控制，以改善響應時間達成更佳的控制效果。
本文使用Matlab/simulink來模擬微電網中太陽能系統架構以及故障之狀況，驗證本文所提出之控制方法的可行性以及模糊派翠類神經網路之改善效果。實驗方面將使用OPAL-RT即時模擬器與德州儀器公司的DSP TMS320F28335實現硬體迴圈架構以及驗證程式之有效性。

摘要(英)

This paper proposes the operation mode and control method of solar energy system in microgrid under normal condition and low voltage fault condition.Normally a solar energy system tracks the peak power output of the solar panel at the maximum power point,and through the DC-AC converter,the power is transmitted to the load or fed back to the grid.During a low voltage fault,the renewable energy device provided by the specification provides a certain proportion of reactive current compensation to assist grid to overcome the short-term voltage drop,and limit the tripping of the circuit breaker during the fault time.Therefore,adjust the output power distribution of the DC-AC converter.Finally,Fuzzy neural Petri net (FNPN) will be used to replace the traditional proportional integral (PI) control to improve the response time and achieve better control effect.
This paper uses Matlab/simulink to simulate the solar energy system architecture and fault conditions in the microgrid.Verify the feasibility of the control method proposed in this paper and the improvement effect of the Fuzzy neural Petri net.In the experiment, the OPAL-RT real-time simulator and the Texas Instruments DSP TMS320F28335 will be used to implement the hardware loop architecture and verify the effectiveness of the program.

關鍵字(中)

★ 太陽能系統
★ 最大功率點追蹤
★ 電網故障
★ 低電壓穿越
★ 模糊派翠類神經網路

關鍵字(英)

★ Solar energy generation system
★ Maximum power point tracking
★ Grid fault
★ Low voltage ride through
★ Fuzzy neural petri net

論文目次

論文摘要 I
Abstract II
目錄 III
圖目錄 VI
表目錄 X
第一章緒論 1
1-1 研究背景與動機 1
1-2 文獻探討 1
1-3 論文大綱 4
第二章微電網太陽能系統介紹 5
2-1 太陽能特性介紹 5
2-2 最大功率點追蹤 6
2-3 微電網控制策略 8
2-3-1三相座標軸轉換 8
2-3-2鎖相迴路 10
2-3-3輸出功率控制 11
第三章低電壓穿越之技術探討 14
3-1 簡介 14
3-2 正負序成分分析 15
3-2-1正負序成分介紹 15
3-2-2正負序成分偵測 16
3-2-3雙二階廣義積分器之鎖相迴路 19
3-3 低電壓穿越控制策略 20
3-3-1低電壓穿越規範 20
3-3-2故障偵測與低電壓穿越 21
第四章模糊派翠類神經網路 24
4-1 模糊理論 24
4-1-1模糊化 24
4-1-2模糊推論引擎 25
4-1-3解模糊化 26
4-2 模糊派翠類神經網路架構 28
4-3 模糊派翠類神經網路線上學習法則 31
第五章系統架構與模擬結果 35
5-1 系統架構 35
5-2 情境之模擬結果 36
5-2-1情境一之模擬結果 37
5-2-2情境二之模擬結果 42
第六章硬體迴圈環境及實驗結果 45
6-1 硬體迴圈測試環境 46
6-2 硬體迴圈實驗結果 50
第七章結論與未來研究方向 57
7-1結論 57
7-2未來研究方向 57
參考文獻 58

參考文獻

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指導教授

陳正一(Cheng-I Chen)

審核日期

2022-8-9

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