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研究生: 范智凱
Zhi-Kai Fan
論文名稱: 以大白鯊演算法進行太陽能最大功率追蹤控制以克服局部遮蔽問題
A White Shark Optimization Based MPPT Control for Partial Shading Conditions
指導教授: 連國龍
Kuo-Lung Lian
口試委員: 黃維澤
Wei-Tzer Huang
吳啟瑞
Chi-Jui Wu
連國龍
Kuo-Lung Lian
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 60
中文關鍵詞: 大白鯊演算法最大功率追蹤光伏系統局部遮蔽
外文關鍵詞: White Shark Optimizer, Maximum Power Point Tracking, Photovoltaic System, Partial Shading
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List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix 1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Research Background and Motivation . . . . . . . . . . . . . . . . . . . . . . 1 1.1.1 Linear Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Artificial Intelligence Method . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.3 Meta-Heuristic Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1.4 Hybrid Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 PHOTOVOLTAIC MODEL and PARTIAL SHADING CONDITION PROBLEM . . . . . . . . . . . . 5 2.1 One Diode Model of Photovoltaic Model . . . . . . . . . . . . . . . . . . . . . 5 2.2 The PSC Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3 WHITE SHARK OPTIMIZER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2 Mathematical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2.1 Movement speed towards prey . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2.2 Movement towards optimal prey . . . . . . . . . . . . . . . . . . . . . . . 10 3.2.3 Movement towards the best white shark . . . . . . . . . . . . . . . . . . . 11 3.2.4 Fish school behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 HYBRID ALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 4.1 Particle Swarm Optimizer . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 4.2 Differential Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.3 Grey Wolf Optimizer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 5 SIMULATION SETUP and RESULT . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.1.1 Initial Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.1.2 Algorithms Renew Process . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.1.3 Convergence Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.1.4 P-V Curve Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 5.2 Simulation Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 6 EXPERIMENTAL SETUP and RESULT . . . . . . . . . . . . . . . . . . . . . . . . . 27 6.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 6.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6.2.1 Static Case Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6.2.2 Dynamic Case Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 7 CONCLUSION and FUTURE WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 7.1 conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 REFERENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

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全文公開日期 2121/02/04 (國家圖書館:臺灣博碩士論文系統)
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