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研究生:陳柏廷
研究生(外文):CHEN, PO-TING
論文名稱:基於田口粒子群最佳化法之太陽能光電系統最大功率追蹤器研製
論文名稱(外文):Design and Implementation of a Maximum Power Point Tracker for PV Systems Based on Taguchi-Particle Swarm Optimization
指導教授:余國瑞余國瑞引用關係
指導教授(外文):YU, GWO-RUEY
口試委員:吳財福陳耀銘陳裕愷張淵智
口試委員(外文):WU, TSAI-FUCHEN, YAOW-MINGCHEN, YU-KAIYuan-Chih Chang
口試日期:2017-07-21
學位類別:碩士
校院名稱:國立中正大學
系所名稱:電機工程研究所
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:2017
畢業學年度:105
語文別:中文
論文頁數:129
中文關鍵詞:田口粒子群最佳化法升–降壓轉換器最大功率追蹤器
外文關鍵詞:Taguchi-Particle Swarm OptimizationPhotovoltaic GenerationMaximum Power Point Tracking
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本文提出田口粒子群最佳化法(TPSO),並應用於所研製之具升降壓模式之2kW轉換器與TI控制電路作為太陽光電系統之最大功率追蹤器(MPPT),使太陽能光電板在部分遮陰情況下或者理想情況下皆能達到最大功率輸出。首先利用田口法對粒子群演算法作參數組合,進行太陽能光電板最大功率追蹤電腦模擬,並解決追蹤準確率及追蹤時間權衡問題得到最佳參數組合。接著執行單峰值功率曲線、雙峰值功率曲線、三峰值功率曲線、四峰值功率曲線,以及於不同大氣環境下例如日照變化、溫度變化等模擬以及實驗,驗證TPSO之性能優於PSO。最後利用2kW多晶矽太陽能光電板與所研製之MPPT,進行多天最大功率追蹤實測。經電腦模擬、實機實測驗證之後,TPSO不管於單峰、多峰功率曲線之情況,或在變日照、變溫度之環境,其性能皆為最優異。
This thesis proposes a maximum power point tracking(MPPT) method for photovoltaic (PV) systems based on Taguchi-Particle Swarm Optimization(TPSO). This thesis designs and implements a buck-boost converter with 2kW rated power as a maximum power point tracker. No matter under ideal environmental conditions or partial shading condition(PSC), the converter can operate at maximum power point. We train parameters to be the best for MPPT on computer simulation by using Taguchi method. To verify its performance, we conducted experiment base on single- peak power curve, double-peak power curve, triple-peak power curve, quadruple-peak power curve, insolation variations, and temperature variations. Results show that the proposed TPSO has better performance then PSO.
目錄
中文摘要 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 1
1.2 文獻回顧 2
1.3 論文大綱 6
第二章 太陽能光電板原理與特性 7
2.1 太陽光電板發電原理 7
2.2 太陽能光電板輸出特性 8
2.2.1 太陽能光電板特性曲線 8
2.2.2 日照變化與溫度變化之影響 9
2.2.3 部分遮陰之影響 10
第三章 系統架構與周邊電路介紹 11
3.1 系統架構 11
3.1.1 電路架構 11
3.1.2 動作原理 12
3.2 周邊電路 15
3.2.1 輔助電源 15
3.2.2 緩衝器buffer 15
3.2.3 開關隔離驅動電路 16
3.2.4 電壓回授電路 16
3.2.5 電流回授電路 17
第四章 最大功率追蹤法 19
4.1 粒子群最佳化法 19
4.2 田口粒子群最佳化法 19
第五章 軟體規劃與程式流程 26
5.1 控制晶片介紹 26
5.2 程式流程介紹 26
5.2.1 主程式流程介紹 27
5.2.2 PWM副程式介紹 28
5.2.3 軟體保護副程式介紹 29
5.2.4 升壓/降壓模式判定副程式介紹 30
5.2.5 田口粒子群最佳化法副程式介紹 31
第六章 田口粒子群最佳化法參數訓練 32
6.1 第一回合訓練參數之決定與回應表建立 33
6.2 第二回合之水準表及適應函數權重 36
6.3 第二、三回合回應表與第三回合水準表與適應函數權重 36
6.4 結束田口訓練回合 39
第七章 電腦模擬 41
7.1 模型建立與模擬參數 41
7.2 單峰值功率曲線(最大功率點為升壓模式) 42
7.3 單峰值功率曲線(最大功率點為降壓模式) 45
7.4 雙峰值功率曲線(最大功率點為升壓模式) 47
7.5 雙峰值功率曲線(最大功率點為降壓模式) 50
7.6 三峰值功率曲線(最大功率點為升壓模式) 52
7.7 三峰值功率曲線(最大功率點為降壓模式) 55
7.8 四峰值功率曲線(最大功率點為升壓模式) 57
7.9 四峰值功率曲線(最大功率點為降壓模式) 60
7.10 日照強度變化 62
7.11 溫度變化 66
第八章 實驗與實測結果 70
8.1 電氣規格 70
8.2 實驗結果 72
8.2.1 單峰值功率曲線(最大功率點為升壓模式) 73
8.2.2 單峰值功率曲線(最大功率點為降壓模式) 75
8.2.3 雙峰值功率曲線(最大功率點為升壓模式) 77
8.2.4 雙峰值功率曲線(最大功率點為降壓模式) 80
8.2.5 三峰值功率曲線(最大功率點為升壓模式) 82
8.2.6 三峰值功率曲線(最大功率點為降壓模式) 85
8.2.7 四峰值功率曲線(最大功率點為升壓模式) 87
8.2.8 四峰值功率曲線(最大功率點為降壓模式) 90
8.2.9 日照強度變化 92
8.2.10 溫度變化 95
8.3 實測結果 97
8.3.1 第一天全天取樣實測統計 98
8.3.2 第二天全天取樣實測統計 99
8.3.3 第三天全天取樣實測統計 99
8.3.4 第四天全天取樣實測統計 100
8.3.5 全天實測數據整理與比較 101
8.4 硬體轉換效率 106
第九章 結論與未來研究方向 107
9.1 結論 107
9.2 未來研究方向 107
參考文獻 108


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