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研究生:詹智貿
研究生(外文):Chih-Mao Chan
論文名稱:使用基因最佳化模糊控制器於太陽能最大功率點追蹤
論文名稱(外文):Maximum Power Point Tracking of Photovoltaic Generation by using Genetic Optimization Fuzzy Controller
指導教授:洪麟
指導教授(外文):Lin Hong
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
畢業學年度:100
語文別:中文
論文頁數:87
中文關鍵詞:太陽能發電最大功率點追蹤模糊邏輯控制基因演算法部分遮蔽
外文關鍵詞:Photovoltaic generationMaximum power point tracking (MPPT)Fuzzy logic control (FLC)Genetic algorithms (GA)Partially shading
相關次數:
  • 被引用被引用:4
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  • 下載下載:18
  • 收藏至我的研究室書目清單書目收藏:0
把太陽能發電作為一種再生能源已變的越來越重要了,因為它具備無燃料成本、不被汙染、需要很少的維護量以及無噪音產生等等優點。然而,太陽能電池陣列輸出功率是會受到溫度與照度的影響。因此,為了獲得太陽能系統最大效率,其最大功率點追蹤是必要的。本論文提出了基因模糊最佳化最大功率點追蹤演算法,使用基因演算法去調整模糊控制器的輸入與輸出比例因子,得到的不只在快速改變大氣條件下有很快的響應同時也比傳統試誤法節省了大量時間與精力。與傳統的擾動觀察法和增量電導法比較下,本論文所提出的演算法可以同時大大的改善最大功率點追蹤響應速度以及降低最大功率點時的震盪情況。模擬結果可驗證其可行性。
另一方面,由於太陽能電池陣列有時候會受到雲、樹或是建築物陰影的影響,而造成太陽能電池表面部分面積受到遮蔽。當部分遮蔽發生時,太陽能電池所受到的影響不只是發電效率降低同時也使太陽能電池產生許多的局部最佳解。因此本論文同時針對部分遮蔽的問題做分析,並將本文所提出之演算法運用在部分遮蔽情況下做最大功率點之追蹤,模擬結果同樣顯是具有效性,故可供後續研究者在設計最大功率點追蹤控制器上作為參考。
Photovoltaic (PV) generation is becoming increasingly important as a renewable source, since it offers the merits of incurring no fuel costs, not being polluted, requiring little maintenance, and emitting no noise, among other advantages. However, the output power induced in the photovoltaic arrays is influenced by temperature and illumination. Therefore, to obtain maximum efficiency of photovoltaic system, it is necessary to track the maximum power point. In this paper, the genetic algorithms (GA) fuzzy optimize MPPT algorithm is proposed. By using a genetic algorithm to adjust the inputs and output scaling factors of fuzzy controller, it has the effects of not only get fast response under rapidly changing atmospheric condition but also can save much time and effort than that of conventional trial-and-error method. In comparing with the conventional perturb and observe (P&O) and incremental conductance (INC) methods, the proposed algorithms can greatly improve the MPPT response speed and oscillation at the maximum power point simultaneously. Simulation results had verified its feasibility.
On the other hand, the performances of photovoltaic arrays are also influenced by the environments such as cloud, tree or building shadows. Partially shading of photovoltaic arrays surface caused not only the reduction of generation efficiency but also produced a number of local optima, which make the maximum power point tracking more difficult. In this paper, the analysis of partially shading problems are also made, and the proposed algorithm being used as the testing controller. Simulation results had shown its effectiveness as well. This may offer as a reference for future researcher.
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
一、緒論 1
1.1 研究動機 1
1.2 文獻回顧 3
1.3 論文架構 4
二、太陽能電力系統簡介 5
2.1 系統架構 5
2.2 太陽能電池 6
2.2.1 太陽能電池轉換原理 6
2.2.2 太陽能電池特性 8
2.2.3 太陽能電池種類 12
2.3 DC-DC升壓轉換器 12
2.4 最大功率點追蹤控制器 17
2.4.1 開路電壓法 18
2.4.2 短路電流法 18
2.4.3 擾動觀察法 18
2.4.4 增量電導法 21
三、最佳化模糊邏輯控制演算法 23
3.1 模糊控制理論 23
3.1.1 模糊理論基本原理 23
3.1.2 模糊控制器的基本架構 24
3.1.3 模糊模式 34
3.2 最佳化演算法 35
3.2.1 基因演算法基本理論 35
3.2.2 基因演算法之探討 41
四、結合基因演算法與模糊控制於太陽能系統 43
4.1 基因模糊最佳化控制 43
4.1.1 太陽能電池陣列 43
4.1.2 模糊控制器 46
4.1.3 基因演算法 48
4.1.4 結合基因法則找尋模糊控制最佳比例因子 50
4.2 傳統演算法與GA模糊控制演算法響應分析 51
4.3 部分遮蔽問題分析 58
4.3.1 部分遮蔽模擬結果 59
4.3.2 旁路二極體對太陽能陣列受遮蔽之影響 74
4.4 GA模糊控制演算法用於部分遮蔽問題分析 78
五、結論及未來研究之方向 83
參考文獻 84
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