隨著全球再生能源發電的佔比日趨擴大，其中太陽能發電更扮演
著舉足輕重的角色。太陽能發電系統裝置量逐年上升，為求發電效率
最大化，開發能夠將太陽能板快速且準確的操作在最大功率輸出點之
最大功率追蹤技術是關鍵的研究方向。太陽能電池之電氣特性為一非
線性曲線，且在不同的照度、溫度條件下，最大功率點都會有所不同，
而由於實際應用下太陽光照射不會是固定照度，因此所有的最大功率
追蹤演算法都會有兩大研究重點：加快追蹤速度以及降低因穩態震盪
所造成之功率損失。而能達成前述目標的最大功率追蹤法則被稱為快
速最大功率追蹤演算法。
本論文基於所建置之模擬與實驗測試平台，並研究與實現文獻中
所提出之十種不同快速最大功率追蹤演算法，藉由所建置之相同測試
環境以達到公平、公正的評測，最後並針對各演算法之優劣進行分析
和比較以提供使用者有效之參考。為驗證所提模擬平台之正確性，本
文亦實際完成一400W 太陽能最大功率追蹤電路，並且在相同的測試
環境下，將各演算法實現至最大功率追蹤硬體電路上，並以實驗結果
展示各演算法之優劣性。

As the proportion of global renewable energy power generation
increases, solar power generation has become an important role. Besides,
the number of solar power generation systems grows year by year. With the
aim to maximize power generation efficiency, it is crucial to develop a
maximum power tracking technology that can rapidly and accurately
operate the solar panel at the maximum power point. The electrical
characteristics of solar cells are non-linear, and the maximum power points
vary under different irradiances and temperature conditions. Moreover,
since the insolation is not constant in practical applications, there are two
major research priorities in all the maximum power tracking algorithms:
accelerating the tracking speed and reducing the power loss caused by
steady-state oscillations. The maximum power tracking algorithm that can
achieve the aforementioned goals is called the fast maximum power
tracking algorithm.
In this study, a simulation and experimental test platform has been
implemented to reproduce ten different fast maximum power tracking
algorithms proposed in the literature. Also, the same test environments
have been built to achieve an impartial evaluation. Finally, the advantages
and disadvantages of each algorithm are analyzed to provide users with
effective references. In addition, a 400W prototyping circuit has been
realized in this study, aiming to verify the correctness of this proposed
simulation platform. Moreover, each algorithm has been implemented on
the actual circuits under the same test environments, and the strengths and
weaknesses of each algorithm are shown in the experimental results.

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