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研究生:賴宏奇
研究生(外文):Hung-Chi Lai
論文名稱:自適應粒子群最佳化演算法應用於太陽能發電系統之最大功率點追蹤
論文名稱(外文):Maximum Power Point Tracking for Photovoltaic Systems Based on Adaptive Particle Swarm Optimization
指導教授:蘇德仁蘇德仁引用關係
指導教授(外文):Te-Jen Su
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電子工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:100
畢業學年度:100
語文別:中文
論文頁數:90
中文關鍵詞:自適應粒子最佳化演算法太陽能電力系統最大功率點慣性權重擾動觀察法
外文關鍵詞:adaptive particle swarm optimization algorithmphotovoltaic systemmaximum power pointinertia weightperturbation and observation
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本論文使用自適應粒子群最佳化演算法(Adaptive Particle Swarm Optimization, APSO),以改善太陽能電力系統之最大功率點追蹤時間。即使日照強度發生改變或溫度有所變化,此追蹤法亦可追蹤至太陽能電池之最大功率點。
由於APSO具有簡單的結構特性,而當中的慣性權重又能夠使整體與局部之間的搜尋達到的一個適當的平衡,因此可以減少目標搜尋的時間並可縮小陷入局部最佳解的機率。使用MATLAB模擬最大功率點追蹤,以APSO進行追蹤所需的CPU運算時間,相較粒子群最佳化演算法(PSO)和擾動觀察法(P&O)約節省19%~65%的時間,由此顯示該方法較其他方法有較佳的搜尋功能。
In this thesis, we propose an adaptive particle swarm optimization (APSO) approach to a photovoltaic system for reducing the time of tracking the maximum power point (MPP). Even illumination or temperature changes, the proposed method can track the MPP of photovoltaic systems.
The adaptive inertia weight of APSO algorithm can balance the result of global and local search, and an adaptive mutation is developed to improve the performance of jumping out of the local optima. By using MATLAB to simulate the MPP tracking, the time of CPU spent which using APSO is saved about 19%~65% tracking time than particle swarm optimization (PSO) and perturbation / observation (P&O). It shows the proposed method has better performance than other methods.
中文摘要 ---------------------------------------------------------------------------------- I
英文摘要 ---------------------------------------------------------------------------------- II
致謝----------------------------------------------------------------------------------------- III
目錄 ---------------------------------------------------------------------------------------- IV
圖目錄 ------------------------------------------------------------------------------------- VI
表目錄 ------------------------------------------------------------------------------------- IX
符號說明 ---------------------------------------------------------------------------------- X

一、緒論----------------------------------------------------------------------------------- 1
1.1 前言------------------------------------------------------------------------------------ 1
1.2 研究動機------------------------------------------------------------------------------ 2
1.3 文獻回顧------------------------------------------------------------------------------ 3
1.4 論文架構------------------------------------------------------------------------------ 5

二、太陽能電力系統-------------------------------------------------------------------- 6
2.1 太陽能電池之原理------------------------------------------------------------------ 7
2.2 太陽能電池種類--------------------------------------------------------------------- 9
2.2.1 單晶矽太陽能電池--------------------------------------------------------------- 12
2.2.2 多晶矽太陽能電池--------------------------------------------------------------- 12
2.2.3 非晶矽太陽能電池--------------------------------------------------------------- 13
2.3 太陽能電池之等效電路------------------------------------------------------------ 14
2.4 太陽能電池之特性曲線------------------------------------------------------------ 18
2.4.1 太陽日照強度之影響------------------------------------------------------------ 19
2.4.2 溫度變化之影響------------------------------------------------------------------ 20

三、系統流程與智慧型演算法-------------------------------------------------------- 23
3.1 系統規格及架構--------------------------------------------------------------------- 23
3.2 DC/DC 升壓轉換器----------------------------------------------------------------- 24
3.2.1 開關閉合之分析------------------------------------------------------------------- 27
3.2.2 開關打開之分析------------------------------------------------------------------- 29
3.3 最大功率的追蹤法則--------------------------------------------------------------- 31
3.3.1 擾動觀察法與登山法------------------------------------------------------------- 31
3.3.2 增量電導法------------------------------------------------------------------------- 36
3.3.3 斜率攀爬法------------------------------------------------------------------------- 39
3.3.4 比例電壓法與比例電流法------------------------------------------------------- 43
3.4 粒子群最佳化演算法---------------------------------------------------------------- 44
3.4.1 粒子群最佳化演算法的背景----------------------------------------------------- 44
3.4.2 粒子群最佳化演算法的法則----------------------------------------------------- 45
3.4.3 粒子群最佳化演算法的演化流程----------------------------------------------- 47
3.4.4 自適應粒子群最佳化演算法之運算-------------------------------------------- 50
3.5 最大功率點追蹤技術的考量-------------------------------------------------------- 51

四、模擬結果------------------------------------------------------------------------------- 53
4.1 最佳化演算法參數設計-------------------------------------------------------------- 54
4.2 擾動觀察法搜尋模擬----------------------------------------------------------------- 56
4.3 粒子群最佳化演算法搜尋模擬----------------------------------------------------- 59
4.4 自適應粒子群最佳化演算法搜尋模擬-------------------------------------------- 60
4.5 環境條件變化搜尋模擬-------------------------------------------------------------- 61
4.6 模擬結果比較-------------------------------------------------------------------------- 63

五、結論及未來展望---------------------------------------------------------------------- 67
5.1 結論-------------------------------------------------------------------------------------- 67
5.2 未來展望-------------------------------------------------------------------------------- 67

參考文獻 ------------------------------------------------------------------------------------- 68
發表論文 ------------------------------------------------------------------------------------- 72
自述 ------------------------------------------------------------------------------------------- 73
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