臺灣博碩士論文加值系統

近年來，愈來愈多的太陽光電系統進入市場，然而，以目前的科技，不論是太陽能板、遮蔭或者電路問題，依舊在發電方面存在能量損失的問題，進而直接導致經濟效益損失，降低了面對傳統方法的競爭力。因此，本論文開發了一種新穎的方法來增進太陽能電池的發電效率，並且於任何時間都能使太陽能電池操作在最大功率點，同時也會隨環境的變化做相對應的變動。事實上，已有許多文獻提出各種最大功率追蹤的方法，但是這些方法的追蹤速度及準確度並不高。因此本論文提出了一種基於灰狼最佳化演算法的新方法，利用了操作點的責任週期及電壓電流數據來定義太陽能電池的瞬間阻抗值，接著透過灰狼最佳化法的疊代，即可使用比傳統方法更短的時間完成最大功率追蹤。為了評估本論文所提之方法，已對系統及電路做了基本測試，結果證實輕微遮蔭時可將疊代次數由10次縮減為5次，減少了原本方法一半的運算時間，同時解決傳統方法於部分遮蔭時失效的問題。

In recent years, increasing numbers of photovoltaic (PV) generation system have entered the market. However with the current engineering technology, including solar panels, shading, circuit issues, it still causes a lot of energy losses in the generation process, resulting in direct economic benefits of the overall system that cannot competed with the traditional system. Thus, in this thesis, it is aimed to develop a novel circuit method to improve the efficiency of the photovoltaic generation operation. Resulting from its intrinsic characteristics, power generated by the solar panel leans on the operational condition at any given time, and the maximum power can be extracted from it varies accordingly. In fact, many maximum power point tracking methods exist in the literature. But those methods are reported not providing a faster tracking speed and accuracy under various environmental conditions. Therefore in this thesis, a new method based on the grey wolf optimization is proposed. This method utilizes the previous working duty cycles and their corresponding voltage and current data to define the instantaneous impedance value of solar cells. Then, by a progressive renewal of the iteration of grey wolf optimizer algorithm, the optimal MPP of solar panel can be found faster than the traditional. In order to assess the performance of this proposed method, it has been tested on the simple realization of system circuit. The preliminary results help consolidate the feasibility and practicability of the approach for the applications considered.

摘要 I
ABSTRACT II
致謝 III
目次 V
表目次 VIII
圖目次 X
第一章 緒論 1
1-1 研究背景與動機 1
1-2 文獻回顧 3
1-3 研究方法 5
1-4 內容大綱 6
第二章 太陽光電發電系統介紹 7
2-1 太陽能電池簡介 7
2-2 太陽能電池特性 11
2-2-1 太陽能電池等效電路 11
2-2-2 太陽能電池特性曲線 13
2-2-3 太陽能電池遮蔭狀況 16
2-3 太陽能系統的分類 16
2-4 最大功率追蹤技術 20
2-5 灰狼最佳化演算法 25
2-5-1 灰狼的習性與狩獵行為 25
2-5-2 灰狼最佳化 25
2-5-3 應用灰狼最佳化演算法於最大功率追蹤 30
第三章 系統規劃及硬體電路設計 33
3-1簡介 33
3-2主電路分析介紹 35
3-3脈衝寬度調變元件 38
3-3-1切換頻率設定 40
3-3-2輸出相位移 40
3-3-3空乏時間 42
3-3-4非相移式脈波寬調變轉換 43
3-4 電壓電流取樣電路設計 44
3-5微控制器與數位類比轉換晶片 45
3-5-1微控制器 45
3-5-2數位類比轉換晶片 47
3-6改良灰狼最佳化演算法 48
3-6-1太陽能板阻抗偵測 50
3-6-2直接攻擊灰狼最佳化演算法 53
第四章 實驗結果 56
4-1簡介 56
4-2 PWM控制訊號 58
4-3 灰狼演算法與傳統方法比較 59
4-3-1輕微遮蔭MPPT比較 60
4-3-2嚴重遮蔭MPPT比較 63
4-4 改良灰狼最佳化演算法最大功率追蹤 66
4-4-1無遮蔭時太陽能板之驗證 66
4-4-2輕微遮蔭太陽能板之驗證 67
4-4-3嚴重遮蔭太陽能板之驗證 69
第五章 結論與未來研究方向 71
5-1結論 71
5-2未來研究方向 72
參考文獻 73

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